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every field may be controlled by a policy\n public = Policy.public()\n meta_only = Policy.context("email", re.compile(".+@metatype.dev"))\n public_write_only = Policy.on(create=public, read=meta_only)\n\n # define runtimes where your queries are executed\n github = HttpRuntime("https://api.github.com")\n db = PrismaRuntime("demo", "POSTGRES_CONN")\n\n # a feedback object stored in Postgres\n feedback = t.struct(\n {\n "id": t.uuid(as_id=True, config=["auto"]),\n "email": t.email().with_policy(public_write_only),\n "message": t.string(min=1, max=2000),\n },\n name="feedback",\n )\n\n # a stargazer object from Github\n stargazer = t.struct(\n {\n "login": t.string(),\n # link with the feedback across runtimes\n "user": github.get(\n "/users/{user}",\n t.struct({"user": t.string().from_parent("login")}),\n t.struct({"name": t.string().optional()}),\n ),\n }\n )\n\n # out of the box authenfication support\n g.auth(Auth.oauth2_github("openid email"))\n\n # expose part of the graph for queries\n g.expose(\n public,\n stargazers=github.get(\n "/repos/metatypedev/metatype/stargazers?per_page=2",\n t.struct({}),\n t.list(stargazer),\n ),\n # automatically generate crud operations\n send_feedback=db.create(feedback),\n list_feedback=db.find_many(feedback),\n )',path:"../examples/typegraphs/index.py"}},48623:e=>{e.exports={content:'typegraph(\n {\n name: "homepage",\n },\n (g) => {\n // every field may be controlled by a policy\n const pub = Policy.public();\n const metaOnly = Policy.context("email", /.+@metatype.dev/);\n const publicWriteOnly = Policy.on({ create: pub, read: metaOnly });\n\n // define runtimes where your queries are executed\n const github = new HttpRuntime("https://api.github.com");\n const db = new PrismaRuntime("demo", "POSTGRES_CONN");\n\n // a feedback object stored in Postgres\n const feedback = t.struct(\n {\n id: t.uuid({ asId: true, config: { auto: true } }),\n email: t.email().withPolicy(publicWriteOnly),\n message: t.string({ min: 1, max: 2000 }, {}),\n },\n { name: "feedback" },\n );\n\n // a stargazer object from Github\n const stargazer = t.struct({\n login: t.string({}),\n // link with the feedback across runtimes\n user: github.get(\n t.struct({ user: t.string().fromParent("login") }),\n t.struct({ name: t.string().optional() }),\n { path: "/users/{user}" },\n ),\n });\n\n g.auth(Auth.oauth2Github("openid email"));\n\n // expose part of the graph for queries\n g.expose(\n {\n stargazers: github.get(t.struct({}), t.list(stargazer), {\n path: "/repos/metatypedev/metatype/stargazers?per_page=2",\n }),\n // automatically generate crud operations\n send_feedback: db.create(feedback),\n list_feedback: db.findMany(feedback),\n },\n pub,\n );\n },\n);',path:"../examples/typegraphs/index.ts"}}}]); \ No newline at end of file diff --git a/assets/js/4f68146b.5e4b72b1.js b/assets/js/4f68146b.3a54c1b3.js similarity index 85% rename from assets/js/4f68146b.5e4b72b1.js rename to assets/js/4f68146b.3a54c1b3.js index 3aae2b5f8d..60f1e377a7 100644 --- a/assets/js/4f68146b.5e4b72b1.js +++ b/assets/js/4f68146b.3a54c1b3.js @@ -1 +1 @@ -"use strict";(self.webpackChunkwebsite=self.webpackChunkwebsite||[]).push([[1732],{53919:(e,n,r)=>{r.r(n),r.d(n,{assets:()=>d,contentTitle:()=>l,default:()=>u,frontMatter:()=>a,metadata:()=>c,toc:()=>h});var t=r(86070),s=r(25710),i=r(27676),o=r(65480);const a={},l="Distributed execution flow paradigms",c={permalink:"/blog/2024/08/27/distributed-execution-flow-paradigms",editUrl:"https://github.com/metatypedev/metatype/tree/main/docs/metatype.dev/blog/2024-08-27-distributed-execution-flow-paradigms/index.mdx",source:"@site/blog/2024-08-27-distributed-execution-flow-paradigms/index.mdx",title:"Distributed execution flow paradigms",description:"In this age of cloud development and microservices architecture, problems start to arise with the increased workloads that run in the system. Imagine an e-commerce platform where a customer places an order for a product during a high-demand sale event. The order triggers a series of interconnected processes: payment processing, inventory checks, packaging, shipping, and final delivery. Each of these processes might be handled by different microservices, potentially running on different servers or even in different data centers. What happens if the payment service goes down right after the payment is authorized but before the inventory is updated? Or if the packaging service fails just after the inventory is deducted but before the item is packed? Without a robust mechanism to ensure that each step in the workflow completes successfully and that failures are properly handled, you could end up with unhappy customers, lost orders, and inventory discrepancies.",date:"2024-08-27T00:00:00.000Z",tags:[],readingTime:10.93,hasTruncateMarker:!1,authors:[],frontMatter:{},unlisted:!1,nextItem:{title:"Python on WebAssembly: How?",permalink:"/blog/2024/08/26/python-on-webassembly"}},d={authorsImageUrls:[]},h=[{value:"1. Event-Driven Architecture with Message Queues",id:"1-event-driven-architecture-with-message-queues",level:3},{value:"Advantages",id:"advantages",level:4},{value:"Challenges",id:"challenges",level:4},{value:"2. The Saga Pattern",id:"2-the-saga-pattern",level:3},{value:"Advantages",id:"advantages-1",level:4},{value:"Drawbacks",id:"drawbacks",level:4},{value:"3. Stateful Orchestrators",id:"3-stateful-orchestrators",level:3},{value:"Advantages",id:"advantages-2",level:4},{value:"Challenges",id:"challenges-1",level:4},{value:"4. Durable Execution",id:"4-durable-execution",level:3},{value:"Advantages",id:"advantages-3",level:4},{value:"Challenges",id:"challenges-2",level:4}];function p(e){const n={a:"a",admonition:"admonition",code:"code",h3:"h3",h4:"h4",img:"img",li:"li",p:"p",pre:"pre",strong:"strong",ul:"ul",...(0,s.R)(),...e.components},{Details:a}=n;return a||function(e,n){throw new Error("Expected "+(n?"component":"object")+" `"+e+"` to be defined: you likely forgot to import, pass, or provide it.")}("Details",!0),(0,t.jsxs)(t.Fragment,{children:[(0,t.jsx)(n.p,{children:"In this age of cloud development and microservices architecture, problems start to arise with the increased workloads that run in the system. Imagine an e-commerce platform where a customer places an order for a product during a high-demand sale event. The order triggers a series of interconnected processes: payment processing, inventory checks, packaging, shipping, and final delivery. Each of these processes might be handled by different microservices, potentially running on different servers or even in different data centers. What happens if the payment service goes down right after the payment is authorized but before the inventory is updated? Or if the packaging service fails just after the inventory is deducted but before the item is packed? Without a robust mechanism to ensure that each step in the workflow completes successfully and that failures are properly handled, you could end up with unhappy customers, lost orders, and inventory discrepancies."}),"\n",(0,t.jsx)(n.p,{children:"Having multiple components in your system introduces more failure points, which is a common phenomenon in complex systems. But one important behavior any application must ensure is that the execution flow reaches its completion. As systems grow in features and complexity, the likelihood of long-running processes increases. To ensure these processes complete as intended, several solutions have been introduced over the last few decades.\nLet's explore some of the solutions that have been proposed to achieve workflow completeness."}),"\n",(0,t.jsx)(n.h3,{id:"1-event-driven-architecture-with-message-queues",children:"1. Event-Driven Architecture with Message Queues"}),"\n",(0,t.jsx)(n.p,{children:"This architecture relies heavily on services communicating by publishing and subscribing to events using message queues. Message queues are persistent storages that ensure data is not lost during failures or service unavailability. Components in a distributed system synchronize by using events/messages through these independent services. While this approach offers service decomposability and fault tolerance, it has some shortcomings. For example, using message queues comes with the overhead of managing messages (e.g., deduplication and message ordering). It also isn\u2019t ideal for systems requiring immediate consistency across components. Some technologies and patterns that utilize this architecture include:"}),"\n",(0,t.jsxs)(n.ul,{children:["\n",(0,t.jsx)(n.li,{children:(0,t.jsx)(n.a,{href:"https://www.rabbitmq.com/",children:"RabbitMQ"})}),"\n",(0,t.jsx)(n.li,{children:(0,t.jsx)(n.a,{href:"https://aws.amazon.com/sqs/",children:"Amazon SQS"})}),"\n"]}),"\n",(0,t.jsx)(n.p,{children:(0,t.jsx)(n.img,{src:r(16676).A+""})}),"\n",(0,t.jsx)("div",{style:{marginLeft:"5em"},children:(0,t.jsx)(n.p,{children:"Fig. Event Driven Architecture with Message Queues - RabbitMQ"})}),"\n",(0,t.jsx)(n.h4,{id:"advantages",children:"Advantages"}),"\n",(0,t.jsxs)(n.ul,{children:["\n",(0,t.jsx)(n.li,{children:"Improved Scalability"}),"\n",(0,t.jsx)(n.li,{children:"Enhanced Responsiveness"}),"\n",(0,t.jsx)(n.li,{children:"Enhanced Fault Tolerance"}),"\n",(0,t.jsx)(n.li,{children:"Simplified Complex Workflows"}),"\n",(0,t.jsx)(n.li,{children:"Real-Time Data Processing"}),"\n"]}),"\n",(0,t.jsx)(n.h4,{id:"challenges",children:"Challenges"}),"\n",(0,t.jsxs)(n.ul,{children:["\n",(0,t.jsx)(n.li,{children:"Event Ordering"}),"\n",(0,t.jsx)(n.li,{children:"Data Consistency"}),"\n",(0,t.jsx)(n.li,{children:"Monitoring and Debugging"}),"\n",(0,t.jsx)(n.li,{children:"Event Deduplication"}),"\n"]}),"\n",(0,t.jsx)(n.p,{children:"You can mitigate or reduce these challenges by following best practices like Event Sourcing, Idempotent Processing, CQRS (Command Query Responsibility Segregation), and Event Versioning."}),"\n",(0,t.jsxs)(n.h3,{id:"2-the-saga-pattern",children:["2. The ",(0,t.jsx)(n.a,{href:"https://microservices.io/patterns/data/saga.html",children:"Saga Pattern"})]}),"\n",(0,t.jsx)(n.p,{children:"This design pattern aims to achieve consistency across different services in a distributed system by breaking complex transactions spanning multiple components into a series of local transactions. Each of these transactions triggers an event or message that starts the next transaction in the sequence. If any local transaction fails to complete, a series of compensating actions roll back the effects of preceding transactions. While the orchestration of local transactions can vary, the pattern aims to achieve consistency in a microservices-based system. Events are designed to be stored in durable storage systems or logs, providing a trail to reconstruct the system to a state after a failure. While the saga pattern is an effective way to ensure consistency, it can be challenging to implement timer/timeout-based workflows and to design and implement the compensating actions for local transactions."}),"\n",(0,t.jsxs)(n.p,{children:[(0,t.jsx)(n.strong,{children:"Note"}),": In the Saga pattern, a compensating transaction must be idempotent and retryable. These principles ensure that transactions can be managed without manual intervention."]}),"\n",(0,t.jsx)(n.p,{children:(0,t.jsx)(n.img,{src:r(35936).A+""})}),"\n",(0,t.jsx)("div",{style:{marginLeft:"10em"},children:(0,t.jsx)(n.p,{children:"Fig. The Saga Pattern for Order delivery system"})}),"\n",(0,t.jsx)(n.h4,{id:"advantages-1",children:"Advantages"}),"\n",(0,t.jsxs)(n.ul,{children:["\n",(0,t.jsx)(n.li,{children:"Ensures data consistency in a distributed system without tight coupling."}),"\n",(0,t.jsx)(n.li,{children:"Provides Roll back if one of the operations in the sequence fails."}),"\n"]}),"\n",(0,t.jsx)(n.h4,{id:"drawbacks",children:"Drawbacks"}),"\n",(0,t.jsxs)(n.ul,{children:["\n",(0,t.jsx)(n.li,{children:"Might be challenging to implement initially."}),"\n",(0,t.jsx)(n.li,{children:"Hard to debug."}),"\n",(0,t.jsx)(n.li,{children:"Compensating transactions don\u2019t always work."}),"\n"]}),"\n",(0,t.jsxs)(n.h3,{id:"3-stateful-orchestrators",children:["3. ",(0,t.jsx)(n.a,{href:"https://docs.oracle.com/en/applications/jd-edwards/cross-product/9.2/eotos/creating-a-stateful-orchestration-release-9-2-8-3.html#u30249073",children:"Stateful Orchestrators"})]}),"\n",(0,t.jsx)(n.p,{children:"Stateful orchestrators provide a solution for long-running workflows by maintaining the state of each step in a workflow. Each step in a workflow represents a task, and these tasks are represented as states inside workflows. Workflows are defined as state machines or directed acyclic graphs (DAGs). In this approach, an orchestrator handles task execution order, transitioning, handling retries, and maintaining state. In the event of a failure, the system can recover from the persisted state. Stateful orchestrators offer significant value in fault tolerance, consistency, and observability. It\u2019s one of the solutions proven effective in modern distributed computing. Some well-known services that provide this solution include:"}),"\n",(0,t.jsxs)(n.ul,{children:["\n",(0,t.jsx)(n.li,{children:(0,t.jsx)(n.a,{href:"https://airflow.apache.org/docs/apache-airflow/stable/core-concepts/overview.html",children:"Apache Airflow"})}),"\n",(0,t.jsx)(n.li,{children:(0,t.jsx)(n.a,{href:"https://azure.microsoft.com/en-us/products/logic-apps",children:"Azure Logic Apps"})}),"\n"]}),"\n",(0,t.jsx)(n.h4,{id:"advantages-2",children:"Advantages"}),"\n",(0,t.jsxs)(n.ul,{children:["\n",(0,t.jsxs)(n.li,{children:[(0,t.jsx)(n.strong,{children:"High Resiliency"}),": Stateful orchestrators provide high resiliency in case of outages, ensuring that workflows can continue from where they left off."]}),"\n",(0,t.jsxs)(n.li,{children:[(0,t.jsx)(n.strong,{children:"Data Persistence"}),": They allow you to keep, review, or reference data from previous events, which is useful for long-running processes."]}),"\n",(0,t.jsxs)(n.li,{children:[(0,t.jsx)(n.strong,{children:"Extended Runtime"}),": Stateful workflows can continue running for much longer than stateless workflows, making them suitable for complex and long-running tasks."]}),"\n"]}),"\n",(0,t.jsx)(n.h4,{id:"challenges-1",children:"Challenges"}),"\n",(0,t.jsxs)(n.ul,{children:["\n",(0,t.jsxs)(n.li,{children:[(0,t.jsx)(n.strong,{children:"Additional Complexity"}),": They introduce additional complexity, requiring you to manage issues such as load balancing, CPU and memory usage, and networking."]}),"\n",(0,t.jsxs)(n.li,{children:[(0,t.jsx)(n.strong,{children:"Cost"}),": With stateful workflows, you pay for the VMs that are running in the cluster, whereas with stateless workflows, you pay only for the actual compute resources consumed."]}),"\n"]}),"\n",(0,t.jsx)(n.h3,{id:"4-durable-execution",children:"4. Durable Execution"}),"\n",(0,t.jsx)(n.p,{children:"Durable execution refers to the ability of a system to preserve the state of an application and persist execution despite failures or interruptions. Durable execution ensures that for every task, its inputs, outputs, call stack, and local variables are persisted. These constraints, or rather features, allow a system to automatically retry or continue running in the face of infrastructure or system failures, ultimately ensuring completion."}),"\n",(0,t.jsx)(n.p,{children:"Durable execution isn\u2019t a completely distinct solution from the ones listed above but rather incorporates some of their strengths while presenting a more comprehensive approach to achieving consistency, fault tolerance, data integrity, resilience for long-running processes, and observability."}),"\n",(0,t.jsx)("img",{src:"/images/blog/execution-flow-paradigms/durable-exec.svg",alt:"Durable workflow engine - Temporal"}),"\n",(0,t.jsx)("div",{style:{marginLeft:"15em"},children:"Fig. Durable workflow engine"}),"\n",(0,t.jsx)(n.h4,{id:"advantages-3",children:"Advantages"}),"\n",(0,t.jsxs)(n.ul,{children:["\n",(0,t.jsxs)(n.li,{children:[(0,t.jsx)(n.strong,{children:"Reduced Manual Intervention"}),": Minimizes the need for human intervention by handling retries and failures programmatically."]}),"\n",(0,t.jsxs)(n.li,{children:[(0,t.jsx)(n.strong,{children:"Improved Observability"}),": Provides a clear audit trail and visibility into the state of workflows, which aids in debugging and monitoring."]}),"\n",(0,t.jsxs)(n.li,{children:[(0,t.jsx)(n.strong,{children:"Scalability"}),": Scales efficiently across distributed systems while maintaining workflow integrity."]}),"\n"]}),"\n",(0,t.jsx)(n.h4,{id:"challenges-2",children:"Challenges"}),"\n",(0,t.jsxs)(n.ul,{children:["\n",(0,t.jsxs)(n.li,{children:[(0,t.jsx)(n.strong,{children:"Resource Intensive"}),": Persistent state storage and management can consume significant resources, especially in large-scale systems."]}),"\n",(0,t.jsxs)(n.li,{children:[(0,t.jsx)(n.strong,{children:"Latency"}),": The need to persist state and handle retries can introduce latency in the execution flow."]}),"\n"]}),"\n",(0,t.jsx)(n.p,{children:"As durable execution grows to be a fundamental driver of distributed computing, some of the solutions which use this architecture are"}),"\n",(0,t.jsxs)(n.ul,{children:["\n",(0,t.jsx)(n.li,{children:(0,t.jsx)(n.a,{href:"https://temporal.io/",children:"Temporal"})}),"\n",(0,t.jsx)(n.li,{children:(0,t.jsx)(n.a,{href:"https://cadenceworkflow.io/",children:"Uber Cadence"})}),"\n"]}),"\n",(0,t.jsxs)(n.p,{children:["Among these, ",(0,t.jsx)(n.a,{href:"https://temporal.io/",children:"Temporal"})," has grown in influence, used by companies like SnapChat, HashiCorp, Stripe, DoorDash, and DataDog. Its success is driven by its practical application in real-world scenarios and the expertise of its founders."]}),"\n",(0,t.jsxs)(n.p,{children:["At Metatype, we recognize the value of durable execution and are committed to making it accessible. Our ",(0,t.jsx)(n.a,{href:"/docs/reference/runtimes/temporal",children:"Temporal Runtime"})," integrates seamlessly into our declarative API development platform, enabling users to harness the power of Temporal directly within Metatype. For those interested in exploring further, our documentation provides a detailed guide on getting started with ",(0,t.jsx)(n.a,{href:"/docs/reference/runtimes/temporal",children:"Temporal Runtime"}),"."]}),"\n",(0,t.jsx)(n.p,{children:"Below is an example of how you can build a simple API to interact with an order delivery temporal workflow within Metatype."}),"\n",(0,t.jsx)(n.admonition,{type:"note",children:(0,t.jsxs)(n.p,{children:["If you are new to Metatype or haven\u2019t set it up yet in your development environment. You can follow this ",(0,t.jsx)(n.a,{href:"/docs/tutorials/quick-start",children:"guideline"}),"."]})}),"\n",(0,t.jsx)(n.p,{children:"For this example, the order delivery system will have few components/services such as Payment, Inventory and Delivery."}),"\n",(0,t.jsx)(n.p,{children:"Your temporal workflow definition should look similar to the one below."}),"\n",(0,t.jsxs)(o.Ay,{children:[(0,t.jsxs)(i.A,{value:"typescript",children:[(0,t.jsxs)(a,{children:[(0,t.jsxs)("summary",{children:["Activities definition inside ",(0,t.jsx)(n.code,{children:"src/activities.ts"}),":`"]}),(0,t.jsx)(n.pre,{children:(0,t.jsx)(n.code,{className:"language-typescript",children:'async function sleep(time: number) {\n return new Promise((resolve) => {\n setTimeout(resolve, time);\n });\n}\n\nexport async function processPayment(orderId: string): Promise {\n console.log(`Processing payment for order ${orderId}`);\n // Simulate payment processing logic\n await sleep(2);\n return "Payment processed";\n}\n\nexport async function checkInventory(orderId: string): Promise {\n console.log(`Checking inventory for order ${orderId}`);\n // Simulate inventory check logic\n await sleep(2);\n return "Inventory available";\n}\n\nexport async function deliverOrder(orderId: string): Promise {\n console.log(`Delivering order ${orderId}`);\n // Simulate delivery logic\n await sleep(5);\n return "Order delivered";\n}\n'})})]}),(0,t.jsxs)(a,{children:[(0,t.jsxs)("summary",{children:["Workflow definition inside ",(0,t.jsx)(n.code,{children:"src/workflows.ts"}),":"]}),(0,t.jsx)(n.pre,{children:(0,t.jsx)(n.code,{className:"language-typescript",metastring:'import {proxyActivities} from "@temporalio/workflow";',children:'\nexport const { processPayment, checkInventory, deliverOrder } =\n proxyActivities<{\n processPayment(orderId: string): Promise;\n checkInventory(orderId: string): Promise;\n deliverOrder(orderId: string): Promise;\n }>({\n startToCloseTimeout: "10 seconds",\n });\n\nexport async function OrderWorkflow(orderId: string): Promise {\n const paymentResult = await processPayment(orderId);\n const inventoryResult = await checkInventory(orderId);\n const deliveryResult = await deliverOrder(orderId);\n return `Order ${orderId} completed with results: ${paymentResult}, ${inventoryResult}, ${deliveryResult}`;\n}\n'})})]}),(0,t.jsxs)(a,{children:[(0,t.jsxs)("summary",{children:["Worker definintion inside ",(0,t.jsx)(n.code,{children:"src/worker.ts"}),":"]}),(0,t.jsx)(n.pre,{children:(0,t.jsx)(n.code,{className:"language-typescript",children:'import { NativeConnection, Worker } from "@temporalio/worker";\nimport * as activities from "./activities";\nimport { TASK_QUEUE_NAME } from "./shared";\n\nasync function run() {\n const connection = await NativeConnection.connect({\n address: "localhost:7233",\n });\n\n const worker = await Worker.create({\n connection,\n namespace: "default",\n taskQueue: TASK_QUEUE_NAME,\n workflowsPath: require.resolve("./workflows"),\n activities,\n });\n\n await worker.run();\n}\n\nrun().catch((err) => {\n console.error(err);\n process.exit(1);\n});\n'})})]}),(0,t.jsxs)(n.p,{children:["After you have setup the above components, now you need a client to start of any ",(0,t.jsx)(n.code,{children:"OrderWorkflow"}),". Here is where metatype comes in, through the simple APIs ",(0,t.jsx)(n.a,{href:"/docs/reference/runtimes/temporal",children:"Temporal Runtime"})," exposes, you can communicate with your temporal cluster.\nDown below is the workflow communication bridge for this system expressed within a ",(0,t.jsx)(n.a,{href:"/docs/reference/typegraph",children:"typegraph"})," which includes endpoints to start a new workflow and describe an existing one."]}),(0,t.jsx)(n.pre,{children:(0,t.jsx)(n.code,{className:"language-typescript",children:'import { Policy, t, typegraph } from "@typegraph/sdk/index.ts";\nimport { TemporalRuntime } from "@typegraph/sdk/providers/temporal.ts";\n\ntypegraph(\n {\n name: "order_delivery",\n },\n (g: any) => {\n const pub = Policy.public();\n\n const temporal = new TemporalRuntime({\n name: "order_delivery",\n hostSecret: "HOST",\n namespaceSecret: "NAMESPACE",\n });\n\n const workflow_id = "order-delivery-1";\n\n const order_id = t.string();\n\n g.expose(\n {\n start: temporal.startWorkflow("OrderWorkflow", order_id),\n describe: workflow_id\n ? temporal.describeWorkflow().reduce({ workflow_id })\n : temporal.describeWorkflow(),\n },\n pub,\n );\n },\n);\n'})})]}),(0,t.jsxs)(i.A,{value:"python",children:[(0,t.jsxs)(a,{children:[(0,t.jsxs)("summary",{children:["Activities definition inside ",(0,t.jsx)(n.code,{children:"activities.py"}),"."]}),(0,t.jsx)(n.pre,{children:(0,t.jsx)(n.code,{className:"language-python",children:'from temporalio import activity\nimport time\n\n@activity.defn\nasync def process_payment(order_id: str) -> str:\n print(f"Processing payment for order {order_id}")\n # Simulate payment processing logic\n time.sleep(5)\n return "Payment processed"\n\n@activity.defn\nasync def check_inventory(order_id: str) -> str:\n print(f"Checking inventory for order {order_id}")\n # Simulate inventory check logic\n time.sleep(4)\n return "Inventory available"\n\n@activity.defn\nasync def deliver_order(order_id: str) -> str:\n print(f"Delivering order {order_id}")\n time.sleep(8)\n # Simulate delivery logic\n return "Order delivered"\n'})})]}),(0,t.jsxs)(a,{children:[(0,t.jsxs)("summary",{children:["Worker defintion inside ",(0,t.jsx)(n.code,{children:"run_worker.py"}),"."]}),(0,t.jsx)(n.pre,{children:(0,t.jsx)(n.code,{className:"language-python",children:'import asyncio\n\nfrom temporalio.client import Client\nfrom temporalio.worker import Worker\n\nfrom activities import process_payment, deliver_order, check_inventory\nfrom shared import ORDER_DELIVERY_QUEUE\nfrom workflows import OrderWorkflow\n\n\nasync def main() -> None:\n client: Client = await Client.connect("localhost:7233", namespace="default")\n worker: Worker = Worker(\n client,\n task_queue=ORDER_DELIVERY_QUEUE,\n workflows=[OrderWorkflow],\n activities=[process_payment, check_inventory, deliver_order],\n )\n await worker.run()\n\n\nif __name__ == "__main__":\n asyncio.run(main())\n'})})]}),(0,t.jsxs)(n.p,{children:["After you have setup the above components, now you need a client to start of any ",(0,t.jsx)(n.code,{children:"OrderWorkflow"}),". Here is where metatype comes in, through the simple APIs ",(0,t.jsx)(n.a,{href:"/docs/reference/runtimes/temporal",children:"Temporal Runtime"})," exposes, you can communicate with your temporal cluster.\nDown below is the workflow communication bridge for this system expressed within a ",(0,t.jsx)(n.a,{href:"/docs/reference/typegraph",children:"typegraph"})," which includes endpoints to start a new workflow and describe an existing one."]}),(0,t.jsx)(n.pre,{children:(0,t.jsx)(n.code,{className:"language-python",children:'from typegraph import t, typegraph, Policy, Graph\nfrom typegraph.providers.temporal import TemporalRuntime\n\n\n@typegraph()\ndef example(g: Graph):\n public = Policy.public()\n\n temporal = TemporalRuntime(\n "example", "HOST", namespace_secret="NAMESPACE"\n )\n\n workflow_id = "order-delivery-1"\n\n order_id = t.string()\n\n g.expose(\n public,\n start=temporal.start_workflow("OrderWorkflow", order_id),\n describe=temporal.describe_workflow().reduce({"workflow_id": workflow_id})\n if workflow_id\n else temporal.describe_workflow(),\n )\n'})})]})]}),"\n",(0,t.jsxs)(n.p,{children:["You need to add the secrets ",(0,t.jsx)(n.code,{children:"HOST"})," and ",(0,t.jsx)(n.code,{children:"NAMESPACE"})," under your typegraph name inside the ",(0,t.jsx)(n.code,{children:"metatype.yaml"})," file. These secrets are important to connect with your temporal cluster and can be safely stored in the config file as shown below."]}),"\n",(0,t.jsxs)(a,{children:[(0,t.jsx)("summary",{children:"metatype.yaml"}),(0,t.jsx)(n.pre,{children:(0,t.jsx)(n.code,{className:"language-yaml",children:'typegate:\n dev:\n url: "http://localhost:7890"\n username: admin\n password: password\n secrets:\n example:\n POSTGRES: "postgresql://postgres:password@postgres:5432/db"\n MONGO: "mongodb://root:password@mongo:27017/db"\n HOST: "http://localhost:7233"\n NAMESPACE: "default"\n'})})]}),"\n",(0,t.jsxs)(n.p,{children:["You need to add only the last two lines as the others are auto-generated. Note that secrets are defined under the ",(0,t.jsx)(n.code,{children:"example"})," parent, which is the name of your typegraph. If the name doesn't match, you will face secret not found issues when deploying your typegraph."]}),"\n",(0,t.jsxs)(n.p,{children:["Before deploying the above typegraph, you need to start the temporal server and the worker. You need to have ",(0,t.jsx)(n.a,{href:"https://learn.temporal.io/getting_started/typescript/dev_environment/#set-up-a-local-temporal-service-for-development-with-temporal-cli",children:"temporal"})," installed on your machine."]}),"\n",(0,t.jsxs)(a,{children:[(0,t.jsx)("summary",{children:"Boot up temporal"}),(0,t.jsx)(n.p,{children:"Start the temporal server."}),(0,t.jsx)(n.pre,{children:(0,t.jsx)(n.code,{className:"language-bash",children:"temporal server start-dev\n"})}),(0,t.jsx)(n.p,{children:"Start the worker."}),(0,t.jsxs)(o.Ay,{children:[(0,t.jsx)(i.A,{value:"typescript",children:(0,t.jsx)(n.p,{children:(0,t.jsx)(n.code,{children:"typescript npx ts-node src/worker.ts "})})}),(0,t.jsx)(i.A,{value:"python",children:(0,t.jsx)(n.code,{children:"python python run_worker.py "})})]})]}),"\n",(0,t.jsxs)(n.p,{children:["After booting the temporal server, run the command down below to get a locally spinning ",(0,t.jsx)(n.a,{href:"/docs/reference/typegate",children:"typegate"})," instance with your typegraph deployed."]}),"\n",(0,t.jsx)(n.pre,{children:(0,t.jsx)(n.code,{className:"language-bash",children:"meta dev\n"})}),"\n",(0,t.jsxs)(n.p,{children:["After completing the above steps, you can access the web GraphQL client of the typegate at ",(0,t.jsx)(n.a,{href:"http://localhost:7890/example",children:(0,t.jsx)(n.code,{children:"http://localhost:7890/example"})}),". Run this query inside the client to start your workflow."]}),"\n",(0,t.jsx)(n.pre,{children:(0,t.jsx)(n.code,{className:"language-graphql",children:'mutation {\n start(\n workflow_id: "order-delivery-3"\n task_queue: "order-delivery-queue"\n args: ["order12"]\n )\n}\n'})}),"\n",(0,t.jsxs)(n.p,{children:["After a successful run, you will get the following result which includes the ",(0,t.jsx)(n.code,{children:"run_id"})," of the workflow which has just been started."]}),"\n",(0,t.jsx)("img",{src:"/images/blog/execution-flow-paradigms/start-workflow-result.png",alt:"Query result"}),"\n",(0,t.jsx)(n.p,{children:"You can also check the temporal web UI to monitor your workflows and you should see a result similar to this one."}),"\n",(0,t.jsx)("img",{src:"/images/blog/execution-flow-paradigms/temporal-web-ui.png",alt:"Workflows dashboard"}),"\n",(0,t.jsxs)(n.p,{children:["You can explore the ",(0,t.jsx)(n.a,{href:"/docs/reference/runtimes/temporal",children:"Temporal Runtime"})," for more info."]}),"\n",(0,t.jsx)(n.p,{children:"This wraps up the blog, thanks for reading until the end :)"})]})}function u(e={}){const{wrapper:n}={...(0,s.R)(),...e.components};return n?(0,t.jsx)(n,{...e,children:(0,t.jsx)(p,{...e})}):p(e)}},65480:(e,n,r)=>{r.d(n,{Ay:()=>o,gc:()=>a});r(30758);var t=r(3733),s=r(56315),i=r(86070);function o(e){let{children:n}=e;const[r,o]=(0,t.e)();return(0,i.jsx)(s.mS,{choices:{typescript:"Typescript SDK",python:"Python SDK"},choice:r,onChange:o,children:n})}function a(e){let{children:n}=e;const[r]=(0,t.e)();return(0,i.jsx)(s.q9,{choices:{typescript:"Typescript SDK",python:"Python SDK"},choice:r,children:n})}},16676:(e,n,r)=>{r.d(n,{A:()=>t});const t=r.p+"assets/images/eda.drawio-9d730aef7e9f00ffed737626d602be5c.svg"},35936:(e,n,r)=>{r.d(n,{A:()=>t});const t=r.p+"assets/images/saga.drawio-6f492c8332ead1021dde63fa7daf0efd.svg"}}]); \ No newline at end of file +"use strict";(self.webpackChunkwebsite=self.webpackChunkwebsite||[]).push([[1732],{53919:(e,n,r)=>{r.r(n),r.d(n,{assets:()=>d,contentTitle:()=>l,default:()=>u,frontMatter:()=>a,metadata:()=>c,toc:()=>h});var t=r(86070),s=r(25710),i=r(27676),o=r(65480);const a={},l="Distributed execution flow paradigms",c={permalink:"/blog/2024/08/27/distributed-execution-flow-paradigms",editUrl:"https://github.com/metatypedev/metatype/tree/main/docs/metatype.dev/blog/2024-08-27-distributed-execution-flow-paradigms/index.mdx",source:"@site/blog/2024-08-27-distributed-execution-flow-paradigms/index.mdx",title:"Distributed execution flow paradigms",description:"In this age of cloud development and microservices architecture, problems start to arise with the increased workloads that run in the system. Imagine an e-commerce platform where a customer places an order for a product during a high-demand sale event. The order triggers a series of interconnected processes: payment processing, inventory checks, packaging, shipping, and final delivery. Each of these processes might be handled by different microservices, potentially running on different servers or even in different data centers. What happens if the payment service goes down right after the payment is authorized but before the inventory is updated? Or if the packaging service fails just after the inventory is deducted but before the item is packed? Without a robust mechanism to ensure that each step in the workflow completes successfully and that failures are properly handled, you could end up with unhappy customers, lost orders, and inventory discrepancies.",date:"2024-08-27T00:00:00.000Z",tags:[],readingTime:10.92,hasTruncateMarker:!1,authors:[],frontMatter:{},unlisted:!1,nextItem:{title:"Python on WebAssembly: How?",permalink:"/blog/2024/08/26/python-on-webassembly"}},d={authorsImageUrls:[]},h=[{value:"1. Event-Driven Architecture with Message Queues",id:"1-event-driven-architecture-with-message-queues",level:3},{value:"Advantages",id:"advantages",level:4},{value:"Challenges",id:"challenges",level:4},{value:"2. The Saga Pattern",id:"2-the-saga-pattern",level:3},{value:"Advantages",id:"advantages-1",level:4},{value:"Drawbacks",id:"drawbacks",level:4},{value:"3. Stateful Orchestrators",id:"3-stateful-orchestrators",level:3},{value:"Advantages",id:"advantages-2",level:4},{value:"Challenges",id:"challenges-1",level:4},{value:"4. Durable Execution",id:"4-durable-execution",level:3},{value:"Advantages",id:"advantages-3",level:4},{value:"Challenges",id:"challenges-2",level:4}];function p(e){const n={a:"a",admonition:"admonition",code:"code",h3:"h3",h4:"h4",img:"img",li:"li",p:"p",pre:"pre",strong:"strong",ul:"ul",...(0,s.R)(),...e.components},{Details:a}=n;return a||function(e,n){throw new Error("Expected "+(n?"component":"object")+" `"+e+"` to be defined: you likely forgot to import, pass, or provide it.")}("Details",!0),(0,t.jsxs)(t.Fragment,{children:[(0,t.jsx)(n.p,{children:"In this age of cloud development and microservices architecture, problems start to arise with the increased workloads that run in the system. Imagine an e-commerce platform where a customer places an order for a product during a high-demand sale event. The order triggers a series of interconnected processes: payment processing, inventory checks, packaging, shipping, and final delivery. Each of these processes might be handled by different microservices, potentially running on different servers or even in different data centers. What happens if the payment service goes down right after the payment is authorized but before the inventory is updated? Or if the packaging service fails just after the inventory is deducted but before the item is packed? Without a robust mechanism to ensure that each step in the workflow completes successfully and that failures are properly handled, you could end up with unhappy customers, lost orders, and inventory discrepancies."}),"\n",(0,t.jsx)(n.p,{children:"Having multiple components in your system introduces more failure points, which is a common phenomenon in complex systems. But one important behavior any application must ensure is that the execution flow reaches its completion. As systems grow in features and complexity, the likelihood of long-running processes increases. To ensure these processes complete as intended, several solutions have been introduced over the last few decades.\nLet's explore some of the solutions that have been proposed to achieve workflow completeness."}),"\n",(0,t.jsx)(n.h3,{id:"1-event-driven-architecture-with-message-queues",children:"1. Event-Driven Architecture with Message Queues"}),"\n",(0,t.jsx)(n.p,{children:"This architecture relies heavily on services communicating by publishing and subscribing to events using message queues. Message queues are persistent storages that ensure data is not lost during failures or service unavailability. Components in a distributed system synchronize by using events/messages through these independent services. While this approach offers service decomposability and fault tolerance, it has some shortcomings. For example, using message queues comes with the overhead of managing messages (e.g., deduplication and message ordering). It also isn\u2019t ideal for systems requiring immediate consistency across components. Some technologies and patterns that utilize this architecture include:"}),"\n",(0,t.jsxs)(n.ul,{children:["\n",(0,t.jsx)(n.li,{children:(0,t.jsx)(n.a,{href:"https://www.rabbitmq.com/",children:"RabbitMQ"})}),"\n",(0,t.jsx)(n.li,{children:(0,t.jsx)(n.a,{href:"https://aws.amazon.com/sqs/",children:"Amazon SQS"})}),"\n"]}),"\n",(0,t.jsx)(n.p,{children:(0,t.jsx)(n.img,{src:r(16676).A+""})}),"\n",(0,t.jsx)("div",{style:{marginLeft:"5em"},children:(0,t.jsx)(n.p,{children:"Fig. Event Driven Architecture with Message Queues - RabbitMQ"})}),"\n",(0,t.jsx)(n.h4,{id:"advantages",children:"Advantages"}),"\n",(0,t.jsxs)(n.ul,{children:["\n",(0,t.jsx)(n.li,{children:"Improved Scalability"}),"\n",(0,t.jsx)(n.li,{children:"Enhanced Responsiveness"}),"\n",(0,t.jsx)(n.li,{children:"Enhanced Fault Tolerance"}),"\n",(0,t.jsx)(n.li,{children:"Simplified Complex Workflows"}),"\n",(0,t.jsx)(n.li,{children:"Real-Time Data Processing"}),"\n"]}),"\n",(0,t.jsx)(n.h4,{id:"challenges",children:"Challenges"}),"\n",(0,t.jsxs)(n.ul,{children:["\n",(0,t.jsx)(n.li,{children:"Event Ordering"}),"\n",(0,t.jsx)(n.li,{children:"Data Consistency"}),"\n",(0,t.jsx)(n.li,{children:"Monitoring and Debugging"}),"\n",(0,t.jsx)(n.li,{children:"Event Deduplication"}),"\n"]}),"\n",(0,t.jsx)(n.p,{children:"You can mitigate or reduce these challenges by following best practices like Event Sourcing, Idempotent Processing, CQRS (Command Query Responsibility Segregation), and Event Versioning."}),"\n",(0,t.jsxs)(n.h3,{id:"2-the-saga-pattern",children:["2. The ",(0,t.jsx)(n.a,{href:"https://microservices.io/patterns/data/saga.html",children:"Saga Pattern"})]}),"\n",(0,t.jsx)(n.p,{children:"This design pattern aims to achieve consistency across different services in a distributed system by breaking complex transactions spanning multiple components into a series of local transactions. Each of these transactions triggers an event or message that starts the next transaction in the sequence. If any local transaction fails to complete, a series of compensating actions roll back the effects of preceding transactions. While the orchestration of local transactions can vary, the pattern aims to achieve consistency in a microservices-based system. Events are designed to be stored in durable storage systems or logs, providing a trail to reconstruct the system to a state after a failure. While the saga pattern is an effective way to ensure consistency, it can be challenging to implement timer/timeout-based workflows and to design and implement the compensating actions for local transactions."}),"\n",(0,t.jsxs)(n.p,{children:[(0,t.jsx)(n.strong,{children:"Note"}),": In the Saga pattern, a compensating transaction must be idempotent and retryable. These principles ensure that transactions can be managed without manual intervention."]}),"\n",(0,t.jsx)(n.p,{children:(0,t.jsx)(n.img,{src:r(35936).A+""})}),"\n",(0,t.jsx)("div",{style:{marginLeft:"10em"},children:(0,t.jsx)(n.p,{children:"Fig. The Saga Pattern for Order delivery system"})}),"\n",(0,t.jsx)(n.h4,{id:"advantages-1",children:"Advantages"}),"\n",(0,t.jsxs)(n.ul,{children:["\n",(0,t.jsx)(n.li,{children:"Ensures data consistency in a distributed system without tight coupling."}),"\n",(0,t.jsx)(n.li,{children:"Provides Roll back if one of the operations in the sequence fails."}),"\n"]}),"\n",(0,t.jsx)(n.h4,{id:"drawbacks",children:"Drawbacks"}),"\n",(0,t.jsxs)(n.ul,{children:["\n",(0,t.jsx)(n.li,{children:"Might be challenging to implement initially."}),"\n",(0,t.jsx)(n.li,{children:"Hard to debug."}),"\n",(0,t.jsx)(n.li,{children:"Compensating transactions don\u2019t always work."}),"\n"]}),"\n",(0,t.jsxs)(n.h3,{id:"3-stateful-orchestrators",children:["3. ",(0,t.jsx)(n.a,{href:"https://docs.oracle.com/en/applications/jd-edwards/cross-product/9.2/eotos/creating-a-stateful-orchestration-release-9-2-8-3.html#u30249073",children:"Stateful Orchestrators"})]}),"\n",(0,t.jsx)(n.p,{children:"Stateful orchestrators provide a solution for long-running workflows by maintaining the state of each step in a workflow. Each step in a workflow represents a task, and these tasks are represented as states inside workflows. Workflows are defined as state machines or directed acyclic graphs (DAGs). In this approach, an orchestrator handles task execution order, transitioning, handling retries, and maintaining state. In the event of a failure, the system can recover from the persisted state. Stateful orchestrators offer significant value in fault tolerance, consistency, and observability. It\u2019s one of the solutions proven effective in modern distributed computing. Some well-known services that provide this solution include:"}),"\n",(0,t.jsxs)(n.ul,{children:["\n",(0,t.jsx)(n.li,{children:(0,t.jsx)(n.a,{href:"https://airflow.apache.org/docs/apache-airflow/stable/core-concepts/overview.html",children:"Apache Airflow"})}),"\n",(0,t.jsx)(n.li,{children:(0,t.jsx)(n.a,{href:"https://azure.microsoft.com/en-us/products/logic-apps",children:"Azure Logic Apps"})}),"\n"]}),"\n",(0,t.jsx)(n.h4,{id:"advantages-2",children:"Advantages"}),"\n",(0,t.jsxs)(n.ul,{children:["\n",(0,t.jsxs)(n.li,{children:[(0,t.jsx)(n.strong,{children:"High Resiliency"}),": Stateful orchestrators provide high resiliency in case of outages, ensuring that workflows can continue from where they left off."]}),"\n",(0,t.jsxs)(n.li,{children:[(0,t.jsx)(n.strong,{children:"Data Persistence"}),": They allow you to keep, review, or reference data from previous events, which is useful for long-running processes."]}),"\n",(0,t.jsxs)(n.li,{children:[(0,t.jsx)(n.strong,{children:"Extended Runtime"}),": Stateful workflows can continue running for much longer than stateless workflows, making them suitable for complex and long-running tasks."]}),"\n"]}),"\n",(0,t.jsx)(n.h4,{id:"challenges-1",children:"Challenges"}),"\n",(0,t.jsxs)(n.ul,{children:["\n",(0,t.jsxs)(n.li,{children:[(0,t.jsx)(n.strong,{children:"Additional Complexity"}),": They introduce additional complexity, requiring you to manage issues such as load balancing, CPU and memory usage, and networking."]}),"\n",(0,t.jsxs)(n.li,{children:[(0,t.jsx)(n.strong,{children:"Cost"}),": With stateful workflows, you pay for the VMs that are running in the cluster, whereas with stateless workflows, you pay only for the actual compute resources consumed."]}),"\n"]}),"\n",(0,t.jsx)(n.h3,{id:"4-durable-execution",children:"4. Durable Execution"}),"\n",(0,t.jsx)(n.p,{children:"Durable execution refers to the ability of a system to preserve the state of an application and persist execution despite failures or interruptions. Durable execution ensures that for every task, its inputs, outputs, call stack, and local variables are persisted. These constraints, or rather features, allow a system to automatically retry or continue running in the face of infrastructure or system failures, ultimately ensuring completion."}),"\n",(0,t.jsx)(n.p,{children:"Durable execution isn\u2019t a completely distinct solution from the ones listed above but rather incorporates some of their strengths while presenting a more comprehensive approach to achieving consistency, fault tolerance, data integrity, resilience for long-running processes, and observability."}),"\n",(0,t.jsx)("img",{src:"/images/blog/execution-flow-paradigms/durable-exec.svg",alt:"Durable workflow engine - Temporal"}),"\n",(0,t.jsx)("div",{style:{marginLeft:"15em"},children:"Fig. Durable workflow engine"}),"\n",(0,t.jsx)(n.h4,{id:"advantages-3",children:"Advantages"}),"\n",(0,t.jsxs)(n.ul,{children:["\n",(0,t.jsxs)(n.li,{children:[(0,t.jsx)(n.strong,{children:"Reduced Manual Intervention"}),": Minimizes the need for human intervention by handling retries and failures programmatically."]}),"\n",(0,t.jsxs)(n.li,{children:[(0,t.jsx)(n.strong,{children:"Improved Observability"}),": Provides a clear audit trail and visibility into the state of workflows, which aids in debugging and monitoring."]}),"\n",(0,t.jsxs)(n.li,{children:[(0,t.jsx)(n.strong,{children:"Scalability"}),": Scales efficiently across distributed systems while maintaining workflow integrity."]}),"\n"]}),"\n",(0,t.jsx)(n.h4,{id:"challenges-2",children:"Challenges"}),"\n",(0,t.jsxs)(n.ul,{children:["\n",(0,t.jsxs)(n.li,{children:[(0,t.jsx)(n.strong,{children:"Resource Intensive"}),": Persistent state storage and management can consume significant resources, especially in large-scale systems."]}),"\n",(0,t.jsxs)(n.li,{children:[(0,t.jsx)(n.strong,{children:"Latency"}),": The need to persist state and handle retries can introduce latency in the execution flow."]}),"\n"]}),"\n",(0,t.jsx)(n.p,{children:"As durable execution grows to be a fundamental driver of distributed computing, some of the solutions which use this architecture are"}),"\n",(0,t.jsxs)(n.ul,{children:["\n",(0,t.jsx)(n.li,{children:(0,t.jsx)(n.a,{href:"https://temporal.io/",children:"Temporal"})}),"\n",(0,t.jsx)(n.li,{children:(0,t.jsx)(n.a,{href:"https://cadenceworkflow.io/",children:"Uber Cadence"})}),"\n"]}),"\n",(0,t.jsxs)(n.p,{children:["Among these, ",(0,t.jsx)(n.a,{href:"https://temporal.io/",children:"Temporal"})," has grown in influence, used by companies like SnapChat, HashiCorp, Stripe, DoorDash, and DataDog. Its success is driven by its practical application in real-world scenarios and the expertise of its founders."]}),"\n",(0,t.jsxs)(n.p,{children:["At Metatype, we recognize the value of durable execution and are committed to making it accessible. Our ",(0,t.jsx)(n.a,{href:"/docs/reference/runtimes/temporal",children:"Temporal Runtime"})," integrates seamlessly into our declarative API development platform, enabling users to harness the power of Temporal directly within Metatype. For those interested in exploring further, our documentation provides a detailed guide on getting started with ",(0,t.jsx)(n.a,{href:"/docs/reference/runtimes/temporal",children:"Temporal Runtime"}),"."]}),"\n",(0,t.jsx)(n.p,{children:"Below is an example of how you can build a simple API to interact with an order delivery temporal workflow within Metatype."}),"\n",(0,t.jsx)(n.admonition,{type:"note",children:(0,t.jsxs)(n.p,{children:["If you are new to Metatype or haven\u2019t set it up yet in your development environment. You can follow this ",(0,t.jsx)(n.a,{href:"/docs/tutorials/quick-start",children:"guideline"}),"."]})}),"\n",(0,t.jsx)(n.p,{children:"For this example, the order delivery system will have few components/services such as Payment, Inventory and Delivery."}),"\n",(0,t.jsx)(n.p,{children:"Your temporal workflow definition should look similar to the one below."}),"\n",(0,t.jsxs)(o.Ay,{children:[(0,t.jsxs)(i.A,{value:"typescript",children:[(0,t.jsxs)(a,{children:[(0,t.jsxs)("summary",{children:["Activities definition inside ",(0,t.jsx)(n.code,{children:"src/activities.ts"}),":`"]}),(0,t.jsx)(n.pre,{children:(0,t.jsx)(n.code,{className:"language-typescript",children:'async function sleep(time: number) {\n return new Promise((resolve) => {\n setTimeout(resolve, time);\n });\n}\n\nexport async function processPayment(orderId: string): Promise {\n console.log(`Processing payment for order ${orderId}`);\n // Simulate payment processing logic\n await sleep(2);\n return "Payment processed";\n}\n\nexport async function checkInventory(orderId: string): Promise {\n console.log(`Checking inventory for order ${orderId}`);\n // Simulate inventory check logic\n await sleep(2);\n return "Inventory available";\n}\n\nexport async function deliverOrder(orderId: string): Promise {\n console.log(`Delivering order ${orderId}`);\n // Simulate delivery logic\n await sleep(5);\n return "Order delivered";\n}\n'})})]}),(0,t.jsxs)(a,{children:[(0,t.jsxs)("summary",{children:["Workflow definition inside ",(0,t.jsx)(n.code,{children:"src/workflows.ts"}),":"]}),(0,t.jsx)(n.pre,{children:(0,t.jsx)(n.code,{className:"language-typescript",metastring:'import {proxyActivities} from "@temporalio/workflow";',children:'\nexport const { processPayment, checkInventory, deliverOrder } =\n proxyActivities<{\n processPayment(orderId: string): Promise;\n checkInventory(orderId: string): Promise;\n deliverOrder(orderId: string): Promise;\n }>({\n startToCloseTimeout: "10 seconds",\n });\n\nexport async function OrderWorkflow(orderId: string): Promise {\n const paymentResult = await processPayment(orderId);\n const inventoryResult = await checkInventory(orderId);\n const deliveryResult = await deliverOrder(orderId);\n return `Order ${orderId} completed with results: ${paymentResult}, ${inventoryResult}, ${deliveryResult}`;\n}\n'})})]}),(0,t.jsxs)(a,{children:[(0,t.jsxs)("summary",{children:["Worker definintion inside ",(0,t.jsx)(n.code,{children:"src/worker.ts"}),":"]}),(0,t.jsx)(n.pre,{children:(0,t.jsx)(n.code,{className:"language-typescript",children:'import { NativeConnection, Worker } from "@temporalio/worker";\nimport * as activities from "./activities";\nimport { TASK_QUEUE_NAME } from "./shared";\n\nasync function run() {\n const connection = await NativeConnection.connect({\n address: "localhost:7233",\n });\n\n const worker = await Worker.create({\n connection,\n namespace: "default",\n taskQueue: TASK_QUEUE_NAME,\n workflowsPath: require.resolve("./workflows"),\n activities,\n });\n\n await worker.run();\n}\n\nrun().catch((err) => {\n console.error(err);\n process.exit(1);\n});\n'})})]}),(0,t.jsxs)(n.p,{children:["After you have setup the above components, now you need a client to start of any ",(0,t.jsx)(n.code,{children:"OrderWorkflow"}),". Here is where metatype comes in, through the simple APIs ",(0,t.jsx)(n.a,{href:"/docs/reference/runtimes/temporal",children:"Temporal Runtime"})," exposes, you can communicate with your temporal cluster.\nDown below is the workflow communication bridge for this system expressed within a ",(0,t.jsx)(n.a,{href:"/docs/reference/typegraph",children:"typegraph"})," which includes endpoints to start a new workflow and describe an existing one."]}),(0,t.jsx)(n.pre,{children:(0,t.jsx)(n.code,{className:"language-typescript",children:'import { Policy, t, typegraph } from "@typegraph/sdk/index.ts";\nimport { TemporalRuntime } from "@typegraph/sdk/providers/temporal.ts";\n\ntypegraph(\n {\n name: "order_delivery",\n },\n (g: any) => {\n const pub = Policy.public();\n\n const temporal = new TemporalRuntime({\n name: "order_delivery",\n hostSecret: "HOST",\n namespaceSecret: "NAMESPACE",\n });\n\n const workflow_id = "order-delivery-1";\n\n const order_id = t.string();\n\n g.expose(\n {\n start: temporal.startWorkflow("OrderWorkflow", order_id),\n describe: workflow_id\n ? temporal.describeWorkflow().reduce({ workflow_id })\n : temporal.describeWorkflow(),\n },\n pub,\n );\n },\n);\n'})})]}),(0,t.jsxs)(i.A,{value:"python",children:[(0,t.jsxs)(a,{children:[(0,t.jsxs)("summary",{children:["Activities definition inside ",(0,t.jsx)(n.code,{children:"activities.py"}),"."]}),(0,t.jsx)(n.pre,{children:(0,t.jsx)(n.code,{className:"language-python",children:'from temporalio import activity\nimport time\n\n@activity.defn\nasync def process_payment(order_id: str) -> str:\n print(f"Processing payment for order {order_id}")\n # Simulate payment processing logic\n time.sleep(5)\n return "Payment processed"\n\n@activity.defn\nasync def check_inventory(order_id: str) -> str:\n print(f"Checking inventory for order {order_id}")\n # Simulate inventory check logic\n time.sleep(4)\n return "Inventory available"\n\n@activity.defn\nasync def deliver_order(order_id: str) -> str:\n print(f"Delivering order {order_id}")\n time.sleep(8)\n # Simulate delivery logic\n return "Order delivered"\n'})})]}),(0,t.jsxs)(a,{children:[(0,t.jsxs)("summary",{children:["Worker defintion inside ",(0,t.jsx)(n.code,{children:"run_worker.py"}),"."]}),(0,t.jsx)(n.pre,{children:(0,t.jsx)(n.code,{className:"language-python",children:'import asyncio\n\nfrom temporalio.client import Client\nfrom temporalio.worker import Worker\n\nfrom activities import process_payment, deliver_order, check_inventory\nfrom shared import ORDER_DELIVERY_QUEUE\nfrom workflows import OrderWorkflow\n\n\nasync def main() -> None:\n client: Client = await Client.connect("localhost:7233", namespace="default")\n worker: Worker = Worker(\n client,\n task_queue=ORDER_DELIVERY_QUEUE,\n workflows=[OrderWorkflow],\n activities=[process_payment, check_inventory, deliver_order],\n )\n await worker.run()\n\n\nif __name__ == "__main__":\n asyncio.run(main())\n'})})]}),(0,t.jsxs)(n.p,{children:["After you have setup the above components, now you need a client to start of any ",(0,t.jsx)(n.code,{children:"OrderWorkflow"}),". Here is where metatype comes in, through the simple APIs ",(0,t.jsx)(n.a,{href:"/docs/reference/runtimes/temporal",children:"Temporal Runtime"})," exposes, you can communicate with your temporal cluster.\nDown below is the workflow communication bridge for this system expressed within a ",(0,t.jsx)(n.a,{href:"/docs/reference/typegraph",children:"typegraph"})," which includes endpoints to start a new workflow and describe an existing one."]}),(0,t.jsx)(n.pre,{children:(0,t.jsx)(n.code,{className:"language-python",children:'from typegraph import t, typegraph, Policy, Graph\nfrom typegraph.providers.temporal import TemporalRuntime\n\n\n@typegraph()\ndef example(g: Graph):\n public = Policy.public()\n\n temporal = TemporalRuntime(\n "example", "HOST", namespace_secret="NAMESPACE"\n )\n\n workflow_id = "order-delivery-1"\n\n order_id = t.string()\n\n g.expose(\n public,\n start=temporal.start_workflow("OrderWorkflow", order_id),\n describe=temporal.describe_workflow().reduce({"workflow_id": workflow_id})\n if workflow_id\n else temporal.describe_workflow(),\n )\n'})})]})]}),"\n",(0,t.jsxs)(n.p,{children:["You need to add the secrets ",(0,t.jsx)(n.code,{children:"HOST"})," and ",(0,t.jsx)(n.code,{children:"NAMESPACE"})," under your typegraph name inside the ",(0,t.jsx)(n.code,{children:"metatype.yaml"})," file. These secrets are important to connect with your temporal cluster and can be safely stored in the config file as shown below."]}),"\n",(0,t.jsxs)(a,{children:[(0,t.jsx)("summary",{children:"metatype.yaml"}),(0,t.jsx)(n.pre,{children:(0,t.jsx)(n.code,{className:"language-yaml",children:'typegate:\n dev:\n url: "http://localhost:7890"\n username: admin\n password: password\n secrets:\n example:\n POSTGRES: "postgresql://postgres:password@postgres:5432/db"\n HOST: "http://localhost:7233"\n NAMESPACE: "default"\n'})})]}),"\n",(0,t.jsxs)(n.p,{children:["You need to add only the last two lines as the others are auto-generated. Note that secrets are defined under the ",(0,t.jsx)(n.code,{children:"example"})," parent, which is the name of your typegraph. If the name doesn't match, you will face secret not found issues when deploying your typegraph."]}),"\n",(0,t.jsxs)(n.p,{children:["Before deploying the above typegraph, you need to start the temporal server and the worker. You need to have ",(0,t.jsx)(n.a,{href:"https://learn.temporal.io/getting_started/typescript/dev_environment/#set-up-a-local-temporal-service-for-development-with-temporal-cli",children:"temporal"})," installed on your machine."]}),"\n",(0,t.jsxs)(a,{children:[(0,t.jsx)("summary",{children:"Boot up temporal"}),(0,t.jsx)(n.p,{children:"Start the temporal server."}),(0,t.jsx)(n.pre,{children:(0,t.jsx)(n.code,{className:"language-bash",children:"temporal server start-dev\n"})}),(0,t.jsx)(n.p,{children:"Start the worker."}),(0,t.jsxs)(o.Ay,{children:[(0,t.jsx)(i.A,{value:"typescript",children:(0,t.jsx)(n.p,{children:(0,t.jsx)(n.code,{children:"typescript npx ts-node src/worker.ts "})})}),(0,t.jsx)(i.A,{value:"python",children:(0,t.jsx)(n.code,{children:"python python run_worker.py "})})]})]}),"\n",(0,t.jsxs)(n.p,{children:["After booting the temporal server, run the command down below to get a locally spinning ",(0,t.jsx)(n.a,{href:"/docs/reference/typegate",children:"typegate"})," instance with your typegraph deployed."]}),"\n",(0,t.jsx)(n.pre,{children:(0,t.jsx)(n.code,{className:"language-bash",children:"meta dev\n"})}),"\n",(0,t.jsxs)(n.p,{children:["After completing the above steps, you can access the web GraphQL client of the typegate at ",(0,t.jsx)(n.a,{href:"http://localhost:7890/example",children:(0,t.jsx)(n.code,{children:"http://localhost:7890/example"})}),". Run this query inside the client to start your workflow."]}),"\n",(0,t.jsx)(n.pre,{children:(0,t.jsx)(n.code,{className:"language-graphql",children:'mutation {\n start(\n workflow_id: "order-delivery-3"\n task_queue: "order-delivery-queue"\n args: ["order12"]\n )\n}\n'})}),"\n",(0,t.jsxs)(n.p,{children:["After a successful run, you will get the following result which includes the ",(0,t.jsx)(n.code,{children:"run_id"})," of the workflow which has just been started."]}),"\n",(0,t.jsx)("img",{src:"/images/blog/execution-flow-paradigms/start-workflow-result.png",alt:"Query result"}),"\n",(0,t.jsx)(n.p,{children:"You can also check the temporal web UI to monitor your workflows and you should see a result similar to this one."}),"\n",(0,t.jsx)("img",{src:"/images/blog/execution-flow-paradigms/temporal-web-ui.png",alt:"Workflows dashboard"}),"\n",(0,t.jsxs)(n.p,{children:["You can explore the ",(0,t.jsx)(n.a,{href:"/docs/reference/runtimes/temporal",children:"Temporal Runtime"})," for more info."]}),"\n",(0,t.jsx)(n.p,{children:"This wraps up the blog, thanks for reading until the end :)"})]})}function u(e={}){const{wrapper:n}={...(0,s.R)(),...e.components};return n?(0,t.jsx)(n,{...e,children:(0,t.jsx)(p,{...e})}):p(e)}},65480:(e,n,r)=>{r.d(n,{Ay:()=>o,gc:()=>a});r(30758);var t=r(3733),s=r(56315),i=r(86070);function o(e){let{children:n}=e;const[r,o]=(0,t.e)();return(0,i.jsx)(s.mS,{choices:{typescript:"Typescript SDK",python:"Python SDK"},choice:r,onChange:o,children:n})}function a(e){let{children:n}=e;const[r]=(0,t.e)();return(0,i.jsx)(s.q9,{choices:{typescript:"Typescript SDK",python:"Python SDK"},choice:r,children:n})}},16676:(e,n,r)=>{r.d(n,{A:()=>t});const t=r.p+"assets/images/eda.drawio-9d730aef7e9f00ffed737626d602be5c.svg"},35936:(e,n,r)=>{r.d(n,{A:()=>t});const t=r.p+"assets/images/saga.drawio-6f492c8332ead1021dde63fa7daf0efd.svg"}}]); \ No newline at end of file diff --git a/assets/js/6e544dd5.472c1746.js b/assets/js/6e544dd5.67ab3519.js similarity index 85% rename from assets/js/6e544dd5.472c1746.js rename to assets/js/6e544dd5.67ab3519.js index f8f49215a4..c8ce4a4c5c 100644 --- a/assets/js/6e544dd5.472c1746.js +++ b/assets/js/6e544dd5.67ab3519.js @@ -1 +1 @@ -"use strict";(self.webpackChunkwebsite=self.webpackChunkwebsite||[]).push([[3126],{2845:(e,n,r)=>{r.r(n),r.d(n,{assets:()=>d,contentTitle:()=>l,default:()=>u,frontMatter:()=>a,metadata:()=>c,toc:()=>h});var t=r(86070),s=r(25710),i=r(27676),o=r(65480);const a={},l="Distributed execution flow paradigms",c={permalink:"/blog/2024/08/27/distributed-execution-flow-paradigms",editUrl:"https://github.com/metatypedev/metatype/tree/main/docs/metatype.dev/blog/2024-08-27-distributed-execution-flow-paradigms/index.mdx",source:"@site/blog/2024-08-27-distributed-execution-flow-paradigms/index.mdx",title:"Distributed execution flow paradigms",description:"In this age of cloud development and microservices architecture, problems start to arise with the increased workloads that run in the system. Imagine an e-commerce platform where a customer places an order for a product during a high-demand sale event. The order triggers a series of interconnected processes: payment processing, inventory checks, packaging, shipping, and final delivery. Each of these processes might be handled by different microservices, potentially running on different servers or even in different data centers. What happens if the payment service goes down right after the payment is authorized but before the inventory is updated? Or if the packaging service fails just after the inventory is deducted but before the item is packed? Without a robust mechanism to ensure that each step in the workflow completes successfully and that failures are properly handled, you could end up with unhappy customers, lost orders, and inventory discrepancies.",date:"2024-08-27T00:00:00.000Z",tags:[],readingTime:10.93,hasTruncateMarker:!1,authors:[],frontMatter:{},unlisted:!1,nextItem:{title:"Python on WebAssembly: How?",permalink:"/blog/2024/08/26/python-on-webassembly"}},d={authorsImageUrls:[]},h=[{value:"1. Event-Driven Architecture with Message Queues",id:"1-event-driven-architecture-with-message-queues",level:3},{value:"Advantages",id:"advantages",level:4},{value:"Challenges",id:"challenges",level:4},{value:"2. The Saga Pattern",id:"2-the-saga-pattern",level:3},{value:"Advantages",id:"advantages-1",level:4},{value:"Drawbacks",id:"drawbacks",level:4},{value:"3. Stateful Orchestrators",id:"3-stateful-orchestrators",level:3},{value:"Advantages",id:"advantages-2",level:4},{value:"Challenges",id:"challenges-1",level:4},{value:"4. Durable Execution",id:"4-durable-execution",level:3},{value:"Advantages",id:"advantages-3",level:4},{value:"Challenges",id:"challenges-2",level:4}];function p(e){const n={a:"a",admonition:"admonition",code:"code",h3:"h3",h4:"h4",img:"img",li:"li",p:"p",pre:"pre",strong:"strong",ul:"ul",...(0,s.R)(),...e.components},{Details:a}=n;return a||function(e,n){throw new Error("Expected "+(n?"component":"object")+" `"+e+"` to be defined: you likely forgot to import, pass, or provide it.")}("Details",!0),(0,t.jsxs)(t.Fragment,{children:[(0,t.jsx)(n.p,{children:"In this age of cloud development and microservices architecture, problems start to arise with the increased workloads that run in the system. Imagine an e-commerce platform where a customer places an order for a product during a high-demand sale event. The order triggers a series of interconnected processes: payment processing, inventory checks, packaging, shipping, and final delivery. Each of these processes might be handled by different microservices, potentially running on different servers or even in different data centers. What happens if the payment service goes down right after the payment is authorized but before the inventory is updated? Or if the packaging service fails just after the inventory is deducted but before the item is packed? Without a robust mechanism to ensure that each step in the workflow completes successfully and that failures are properly handled, you could end up with unhappy customers, lost orders, and inventory discrepancies."}),"\n",(0,t.jsx)(n.p,{children:"Having multiple components in your system introduces more failure points, which is a common phenomenon in complex systems. But one important behavior any application must ensure is that the execution flow reaches its completion. As systems grow in features and complexity, the likelihood of long-running processes increases. To ensure these processes complete as intended, several solutions have been introduced over the last few decades.\nLet's explore some of the solutions that have been proposed to achieve workflow completeness."}),"\n",(0,t.jsx)(n.h3,{id:"1-event-driven-architecture-with-message-queues",children:"1. Event-Driven Architecture with Message Queues"}),"\n",(0,t.jsx)(n.p,{children:"This architecture relies heavily on services communicating by publishing and subscribing to events using message queues. Message queues are persistent storages that ensure data is not lost during failures or service unavailability. Components in a distributed system synchronize by using events/messages through these independent services. While this approach offers service decomposability and fault tolerance, it has some shortcomings. For example, using message queues comes with the overhead of managing messages (e.g., deduplication and message ordering). It also isn\u2019t ideal for systems requiring immediate consistency across components. Some technologies and patterns that utilize this architecture include:"}),"\n",(0,t.jsxs)(n.ul,{children:["\n",(0,t.jsx)(n.li,{children:(0,t.jsx)(n.a,{href:"https://www.rabbitmq.com/",children:"RabbitMQ"})}),"\n",(0,t.jsx)(n.li,{children:(0,t.jsx)(n.a,{href:"https://aws.amazon.com/sqs/",children:"Amazon SQS"})}),"\n"]}),"\n",(0,t.jsx)(n.p,{children:(0,t.jsx)(n.img,{src:r(16676).A+""})}),"\n",(0,t.jsx)("div",{style:{marginLeft:"5em"},children:(0,t.jsx)(n.p,{children:"Fig. Event Driven Architecture with Message Queues - RabbitMQ"})}),"\n",(0,t.jsx)(n.h4,{id:"advantages",children:"Advantages"}),"\n",(0,t.jsxs)(n.ul,{children:["\n",(0,t.jsx)(n.li,{children:"Improved Scalability"}),"\n",(0,t.jsx)(n.li,{children:"Enhanced Responsiveness"}),"\n",(0,t.jsx)(n.li,{children:"Enhanced Fault Tolerance"}),"\n",(0,t.jsx)(n.li,{children:"Simplified Complex Workflows"}),"\n",(0,t.jsx)(n.li,{children:"Real-Time Data Processing"}),"\n"]}),"\n",(0,t.jsx)(n.h4,{id:"challenges",children:"Challenges"}),"\n",(0,t.jsxs)(n.ul,{children:["\n",(0,t.jsx)(n.li,{children:"Event Ordering"}),"\n",(0,t.jsx)(n.li,{children:"Data Consistency"}),"\n",(0,t.jsx)(n.li,{children:"Monitoring and Debugging"}),"\n",(0,t.jsx)(n.li,{children:"Event Deduplication"}),"\n"]}),"\n",(0,t.jsx)(n.p,{children:"You can mitigate or reduce these challenges by following best practices like Event Sourcing, Idempotent Processing, CQRS (Command Query Responsibility Segregation), and Event Versioning."}),"\n",(0,t.jsxs)(n.h3,{id:"2-the-saga-pattern",children:["2. The ",(0,t.jsx)(n.a,{href:"https://microservices.io/patterns/data/saga.html",children:"Saga Pattern"})]}),"\n",(0,t.jsx)(n.p,{children:"This design pattern aims to achieve consistency across different services in a distributed system by breaking complex transactions spanning multiple components into a series of local transactions. Each of these transactions triggers an event or message that starts the next transaction in the sequence. If any local transaction fails to complete, a series of compensating actions roll back the effects of preceding transactions. While the orchestration of local transactions can vary, the pattern aims to achieve consistency in a microservices-based system. Events are designed to be stored in durable storage systems or logs, providing a trail to reconstruct the system to a state after a failure. While the saga pattern is an effective way to ensure consistency, it can be challenging to implement timer/timeout-based workflows and to design and implement the compensating actions for local transactions."}),"\n",(0,t.jsxs)(n.p,{children:[(0,t.jsx)(n.strong,{children:"Note"}),": In the Saga pattern, a compensating transaction must be idempotent and retryable. These principles ensure that transactions can be managed without manual intervention."]}),"\n",(0,t.jsx)(n.p,{children:(0,t.jsx)(n.img,{src:r(35936).A+""})}),"\n",(0,t.jsx)("div",{style:{marginLeft:"10em"},children:(0,t.jsx)(n.p,{children:"Fig. The Saga Pattern for Order delivery system"})}),"\n",(0,t.jsx)(n.h4,{id:"advantages-1",children:"Advantages"}),"\n",(0,t.jsxs)(n.ul,{children:["\n",(0,t.jsx)(n.li,{children:"Ensures data consistency in a distributed system without tight coupling."}),"\n",(0,t.jsx)(n.li,{children:"Provides Roll back if one of the operations in the sequence fails."}),"\n"]}),"\n",(0,t.jsx)(n.h4,{id:"drawbacks",children:"Drawbacks"}),"\n",(0,t.jsxs)(n.ul,{children:["\n",(0,t.jsx)(n.li,{children:"Might be challenging to implement initially."}),"\n",(0,t.jsx)(n.li,{children:"Hard to debug."}),"\n",(0,t.jsx)(n.li,{children:"Compensating transactions don\u2019t always work."}),"\n"]}),"\n",(0,t.jsxs)(n.h3,{id:"3-stateful-orchestrators",children:["3. ",(0,t.jsx)(n.a,{href:"https://docs.oracle.com/en/applications/jd-edwards/cross-product/9.2/eotos/creating-a-stateful-orchestration-release-9-2-8-3.html#u30249073",children:"Stateful Orchestrators"})]}),"\n",(0,t.jsx)(n.p,{children:"Stateful orchestrators provide a solution for long-running workflows by maintaining the state of each step in a workflow. Each step in a workflow represents a task, and these tasks are represented as states inside workflows. Workflows are defined as state machines or directed acyclic graphs (DAGs). In this approach, an orchestrator handles task execution order, transitioning, handling retries, and maintaining state. In the event of a failure, the system can recover from the persisted state. Stateful orchestrators offer significant value in fault tolerance, consistency, and observability. It\u2019s one of the solutions proven effective in modern distributed computing. Some well-known services that provide this solution include:"}),"\n",(0,t.jsxs)(n.ul,{children:["\n",(0,t.jsx)(n.li,{children:(0,t.jsx)(n.a,{href:"https://airflow.apache.org/docs/apache-airflow/stable/core-concepts/overview.html",children:"Apache Airflow"})}),"\n",(0,t.jsx)(n.li,{children:(0,t.jsx)(n.a,{href:"https://azure.microsoft.com/en-us/products/logic-apps",children:"Azure Logic Apps"})}),"\n"]}),"\n",(0,t.jsx)(n.h4,{id:"advantages-2",children:"Advantages"}),"\n",(0,t.jsxs)(n.ul,{children:["\n",(0,t.jsxs)(n.li,{children:[(0,t.jsx)(n.strong,{children:"High Resiliency"}),": Stateful orchestrators provide high resiliency in case of outages, ensuring that workflows can continue from where they left off."]}),"\n",(0,t.jsxs)(n.li,{children:[(0,t.jsx)(n.strong,{children:"Data Persistence"}),": They allow you to keep, review, or reference data from previous events, which is useful for long-running processes."]}),"\n",(0,t.jsxs)(n.li,{children:[(0,t.jsx)(n.strong,{children:"Extended Runtime"}),": Stateful workflows can continue running for much longer than stateless workflows, making them suitable for complex and long-running tasks."]}),"\n"]}),"\n",(0,t.jsx)(n.h4,{id:"challenges-1",children:"Challenges"}),"\n",(0,t.jsxs)(n.ul,{children:["\n",(0,t.jsxs)(n.li,{children:[(0,t.jsx)(n.strong,{children:"Additional Complexity"}),": They introduce additional complexity, requiring you to manage issues such as load balancing, CPU and memory usage, and networking."]}),"\n",(0,t.jsxs)(n.li,{children:[(0,t.jsx)(n.strong,{children:"Cost"}),": With stateful workflows, you pay for the VMs that are running in the cluster, whereas with stateless workflows, you pay only for the actual compute resources consumed."]}),"\n"]}),"\n",(0,t.jsx)(n.h3,{id:"4-durable-execution",children:"4. Durable Execution"}),"\n",(0,t.jsx)(n.p,{children:"Durable execution refers to the ability of a system to preserve the state of an application and persist execution despite failures or interruptions. Durable execution ensures that for every task, its inputs, outputs, call stack, and local variables are persisted. These constraints, or rather features, allow a system to automatically retry or continue running in the face of infrastructure or system failures, ultimately ensuring completion."}),"\n",(0,t.jsx)(n.p,{children:"Durable execution isn\u2019t a completely distinct solution from the ones listed above but rather incorporates some of their strengths while presenting a more comprehensive approach to achieving consistency, fault tolerance, data integrity, resilience for long-running processes, and observability."}),"\n",(0,t.jsx)("img",{src:"/images/blog/execution-flow-paradigms/durable-exec.svg",alt:"Durable workflow engine - Temporal"}),"\n",(0,t.jsx)("div",{style:{marginLeft:"15em"},children:"Fig. Durable workflow engine"}),"\n",(0,t.jsx)(n.h4,{id:"advantages-3",children:"Advantages"}),"\n",(0,t.jsxs)(n.ul,{children:["\n",(0,t.jsxs)(n.li,{children:[(0,t.jsx)(n.strong,{children:"Reduced Manual Intervention"}),": Minimizes the need for human intervention by handling retries and failures programmatically."]}),"\n",(0,t.jsxs)(n.li,{children:[(0,t.jsx)(n.strong,{children:"Improved Observability"}),": Provides a clear audit trail and visibility into the state of workflows, which aids in debugging and monitoring."]}),"\n",(0,t.jsxs)(n.li,{children:[(0,t.jsx)(n.strong,{children:"Scalability"}),": Scales efficiently across distributed systems while maintaining workflow integrity."]}),"\n"]}),"\n",(0,t.jsx)(n.h4,{id:"challenges-2",children:"Challenges"}),"\n",(0,t.jsxs)(n.ul,{children:["\n",(0,t.jsxs)(n.li,{children:[(0,t.jsx)(n.strong,{children:"Resource Intensive"}),": Persistent state storage and management can consume significant resources, especially in large-scale systems."]}),"\n",(0,t.jsxs)(n.li,{children:[(0,t.jsx)(n.strong,{children:"Latency"}),": The need to persist state and handle retries can introduce latency in the execution flow."]}),"\n"]}),"\n",(0,t.jsx)(n.p,{children:"As durable execution grows to be a fundamental driver of distributed computing, some of the solutions which use this architecture are"}),"\n",(0,t.jsxs)(n.ul,{children:["\n",(0,t.jsx)(n.li,{children:(0,t.jsx)(n.a,{href:"https://temporal.io/",children:"Temporal"})}),"\n",(0,t.jsx)(n.li,{children:(0,t.jsx)(n.a,{href:"https://cadenceworkflow.io/",children:"Uber Cadence"})}),"\n"]}),"\n",(0,t.jsxs)(n.p,{children:["Among these, ",(0,t.jsx)(n.a,{href:"https://temporal.io/",children:"Temporal"})," has grown in influence, used by companies like SnapChat, HashiCorp, Stripe, DoorDash, and DataDog. Its success is driven by its practical application in real-world scenarios and the expertise of its founders."]}),"\n",(0,t.jsxs)(n.p,{children:["At Metatype, we recognize the value of durable execution and are committed to making it accessible. Our ",(0,t.jsx)(n.a,{href:"/docs/reference/runtimes/temporal",children:"Temporal Runtime"})," integrates seamlessly into our declarative API development platform, enabling users to harness the power of Temporal directly within Metatype. For those interested in exploring further, our documentation provides a detailed guide on getting started with ",(0,t.jsx)(n.a,{href:"/docs/reference/runtimes/temporal",children:"Temporal Runtime"}),"."]}),"\n",(0,t.jsx)(n.p,{children:"Below is an example of how you can build a simple API to interact with an order delivery temporal workflow within Metatype."}),"\n",(0,t.jsx)(n.admonition,{type:"note",children:(0,t.jsxs)(n.p,{children:["If you are new to Metatype or haven\u2019t set it up yet in your development environment. You can follow this ",(0,t.jsx)(n.a,{href:"/docs/tutorials/quick-start",children:"guideline"}),"."]})}),"\n",(0,t.jsx)(n.p,{children:"For this example, the order delivery system will have few components/services such as Payment, Inventory and Delivery."}),"\n",(0,t.jsx)(n.p,{children:"Your temporal workflow definition should look similar to the one below."}),"\n",(0,t.jsxs)(o.Ay,{children:[(0,t.jsxs)(i.A,{value:"typescript",children:[(0,t.jsxs)(a,{children:[(0,t.jsxs)("summary",{children:["Activities definition inside ",(0,t.jsx)(n.code,{children:"src/activities.ts"}),":`"]}),(0,t.jsx)(n.pre,{children:(0,t.jsx)(n.code,{className:"language-typescript",children:'async function sleep(time: number) {\n return new Promise((resolve) => {\n setTimeout(resolve, time);\n });\n}\n\nexport async function processPayment(orderId: string): Promise {\n console.log(`Processing payment for order ${orderId}`);\n // Simulate payment processing logic\n await sleep(2);\n return "Payment processed";\n}\n\nexport async function checkInventory(orderId: string): Promise {\n console.log(`Checking inventory for order ${orderId}`);\n // Simulate inventory check logic\n await sleep(2);\n return "Inventory available";\n}\n\nexport async function deliverOrder(orderId: string): Promise {\n console.log(`Delivering order ${orderId}`);\n // Simulate delivery logic\n await sleep(5);\n return "Order delivered";\n}\n'})})]}),(0,t.jsxs)(a,{children:[(0,t.jsxs)("summary",{children:["Workflow definition inside ",(0,t.jsx)(n.code,{children:"src/workflows.ts"}),":"]}),(0,t.jsx)(n.pre,{children:(0,t.jsx)(n.code,{className:"language-typescript",metastring:'import {proxyActivities} from "@temporalio/workflow";',children:'\nexport const { processPayment, checkInventory, deliverOrder } =\n proxyActivities<{\n processPayment(orderId: string): Promise;\n checkInventory(orderId: string): Promise;\n deliverOrder(orderId: string): Promise;\n }>({\n startToCloseTimeout: "10 seconds",\n });\n\nexport async function OrderWorkflow(orderId: string): Promise {\n const paymentResult = await processPayment(orderId);\n const inventoryResult = await checkInventory(orderId);\n const deliveryResult = await deliverOrder(orderId);\n return `Order ${orderId} completed with results: ${paymentResult}, ${inventoryResult}, ${deliveryResult}`;\n}\n'})})]}),(0,t.jsxs)(a,{children:[(0,t.jsxs)("summary",{children:["Worker definintion inside ",(0,t.jsx)(n.code,{children:"src/worker.ts"}),":"]}),(0,t.jsx)(n.pre,{children:(0,t.jsx)(n.code,{className:"language-typescript",children:'import { NativeConnection, Worker } from "@temporalio/worker";\nimport * as activities from "./activities";\nimport { TASK_QUEUE_NAME } from "./shared";\n\nasync function run() {\n const connection = await NativeConnection.connect({\n address: "localhost:7233",\n });\n\n const worker = await Worker.create({\n connection,\n namespace: "default",\n taskQueue: TASK_QUEUE_NAME,\n workflowsPath: require.resolve("./workflows"),\n activities,\n });\n\n await worker.run();\n}\n\nrun().catch((err) => {\n console.error(err);\n process.exit(1);\n});\n'})})]}),(0,t.jsxs)(n.p,{children:["After you have setup the above components, now you need a client to start of any ",(0,t.jsx)(n.code,{children:"OrderWorkflow"}),". Here is where metatype comes in, through the simple APIs ",(0,t.jsx)(n.a,{href:"/docs/reference/runtimes/temporal",children:"Temporal Runtime"})," exposes, you can communicate with your temporal cluster.\nDown below is the workflow communication bridge for this system expressed within a ",(0,t.jsx)(n.a,{href:"/docs/reference/typegraph",children:"typegraph"})," which includes endpoints to start a new workflow and describe an existing one."]}),(0,t.jsx)(n.pre,{children:(0,t.jsx)(n.code,{className:"language-typescript",children:'import { Policy, t, typegraph } from "@typegraph/sdk/index.ts";\nimport { TemporalRuntime } from "@typegraph/sdk/providers/temporal.ts";\n\ntypegraph(\n {\n name: "order_delivery",\n },\n (g: any) => {\n const pub = Policy.public();\n\n const temporal = new TemporalRuntime({\n name: "order_delivery",\n hostSecret: "HOST",\n namespaceSecret: "NAMESPACE",\n });\n\n const workflow_id = "order-delivery-1";\n\n const order_id = t.string();\n\n g.expose(\n {\n start: temporal.startWorkflow("OrderWorkflow", order_id),\n describe: workflow_id\n ? temporal.describeWorkflow().reduce({ workflow_id })\n : temporal.describeWorkflow(),\n },\n pub,\n );\n },\n);\n'})})]}),(0,t.jsxs)(i.A,{value:"python",children:[(0,t.jsxs)(a,{children:[(0,t.jsxs)("summary",{children:["Activities definition inside ",(0,t.jsx)(n.code,{children:"activities.py"}),"."]}),(0,t.jsx)(n.pre,{children:(0,t.jsx)(n.code,{className:"language-python",children:'from temporalio import activity\nimport time\n\n@activity.defn\nasync def process_payment(order_id: str) -> str:\n print(f"Processing payment for order {order_id}")\n # Simulate payment processing logic\n time.sleep(5)\n return "Payment processed"\n\n@activity.defn\nasync def check_inventory(order_id: str) -> str:\n print(f"Checking inventory for order {order_id}")\n # Simulate inventory check logic\n time.sleep(4)\n return "Inventory available"\n\n@activity.defn\nasync def deliver_order(order_id: str) -> str:\n print(f"Delivering order {order_id}")\n time.sleep(8)\n # Simulate delivery logic\n return "Order delivered"\n'})})]}),(0,t.jsxs)(a,{children:[(0,t.jsxs)("summary",{children:["Worker defintion inside ",(0,t.jsx)(n.code,{children:"run_worker.py"}),"."]}),(0,t.jsx)(n.pre,{children:(0,t.jsx)(n.code,{className:"language-python",children:'import asyncio\n\nfrom temporalio.client import Client\nfrom temporalio.worker import Worker\n\nfrom activities import process_payment, deliver_order, check_inventory\nfrom shared import ORDER_DELIVERY_QUEUE\nfrom workflows import OrderWorkflow\n\n\nasync def main() -> None:\n client: Client = await Client.connect("localhost:7233", namespace="default")\n worker: Worker = Worker(\n client,\n task_queue=ORDER_DELIVERY_QUEUE,\n workflows=[OrderWorkflow],\n activities=[process_payment, check_inventory, deliver_order],\n )\n await worker.run()\n\n\nif __name__ == "__main__":\n asyncio.run(main())\n'})})]}),(0,t.jsxs)(n.p,{children:["After you have setup the above components, now you need a client to start of any ",(0,t.jsx)(n.code,{children:"OrderWorkflow"}),". Here is where metatype comes in, through the simple APIs ",(0,t.jsx)(n.a,{href:"/docs/reference/runtimes/temporal",children:"Temporal Runtime"})," exposes, you can communicate with your temporal cluster.\nDown below is the workflow communication bridge for this system expressed within a ",(0,t.jsx)(n.a,{href:"/docs/reference/typegraph",children:"typegraph"})," which includes endpoints to start a new workflow and describe an existing one."]}),(0,t.jsx)(n.pre,{children:(0,t.jsx)(n.code,{className:"language-python",children:'from typegraph import t, typegraph, Policy, Graph\nfrom typegraph.providers.temporal import TemporalRuntime\n\n\n@typegraph()\ndef example(g: Graph):\n public = Policy.public()\n\n temporal = TemporalRuntime(\n "example", "HOST", namespace_secret="NAMESPACE"\n )\n\n workflow_id = "order-delivery-1"\n\n order_id = t.string()\n\n g.expose(\n public,\n start=temporal.start_workflow("OrderWorkflow", order_id),\n describe=temporal.describe_workflow().reduce({"workflow_id": workflow_id})\n if workflow_id\n else temporal.describe_workflow(),\n )\n'})})]})]}),"\n",(0,t.jsxs)(n.p,{children:["You need to add the secrets ",(0,t.jsx)(n.code,{children:"HOST"})," and ",(0,t.jsx)(n.code,{children:"NAMESPACE"})," under your typegraph name inside the ",(0,t.jsx)(n.code,{children:"metatype.yaml"})," file. These secrets are important to connect with your temporal cluster and can be safely stored in the config file as shown below."]}),"\n",(0,t.jsxs)(a,{children:[(0,t.jsx)("summary",{children:"metatype.yaml"}),(0,t.jsx)(n.pre,{children:(0,t.jsx)(n.code,{className:"language-yaml",children:'typegate:\n dev:\n url: "http://localhost:7890"\n username: admin\n password: password\n secrets:\n example:\n POSTGRES: "postgresql://postgres:password@postgres:5432/db"\n MONGO: "mongodb://root:password@mongo:27017/db"\n HOST: "http://localhost:7233"\n NAMESPACE: "default"\n'})})]}),"\n",(0,t.jsxs)(n.p,{children:["You need to add only the last two lines as the others are auto-generated. Note that secrets are defined under the ",(0,t.jsx)(n.code,{children:"example"})," parent, which is the name of your typegraph. If the name doesn't match, you will face secret not found issues when deploying your typegraph."]}),"\n",(0,t.jsxs)(n.p,{children:["Before deploying the above typegraph, you need to start the temporal server and the worker. You need to have ",(0,t.jsx)(n.a,{href:"https://learn.temporal.io/getting_started/typescript/dev_environment/#set-up-a-local-temporal-service-for-development-with-temporal-cli",children:"temporal"})," installed on your machine."]}),"\n",(0,t.jsxs)(a,{children:[(0,t.jsx)("summary",{children:"Boot up temporal"}),(0,t.jsx)(n.p,{children:"Start the temporal server."}),(0,t.jsx)(n.pre,{children:(0,t.jsx)(n.code,{className:"language-bash",children:"temporal server start-dev\n"})}),(0,t.jsx)(n.p,{children:"Start the worker."}),(0,t.jsxs)(o.Ay,{children:[(0,t.jsx)(i.A,{value:"typescript",children:(0,t.jsx)(n.p,{children:(0,t.jsx)(n.code,{children:"typescript npx ts-node src/worker.ts "})})}),(0,t.jsx)(i.A,{value:"python",children:(0,t.jsx)(n.code,{children:"python python run_worker.py "})})]})]}),"\n",(0,t.jsxs)(n.p,{children:["After booting the temporal server, run the command down below to get a locally spinning ",(0,t.jsx)(n.a,{href:"/docs/reference/typegate",children:"typegate"})," instance with your typegraph deployed."]}),"\n",(0,t.jsx)(n.pre,{children:(0,t.jsx)(n.code,{className:"language-bash",children:"meta dev\n"})}),"\n",(0,t.jsxs)(n.p,{children:["After completing the above steps, you can access the web GraphQL client of the typegate at ",(0,t.jsx)(n.a,{href:"http://localhost:7890/example",children:(0,t.jsx)(n.code,{children:"http://localhost:7890/example"})}),". Run this query inside the client to start your workflow."]}),"\n",(0,t.jsx)(n.pre,{children:(0,t.jsx)(n.code,{className:"language-graphql",children:'mutation {\n start(\n workflow_id: "order-delivery-3"\n task_queue: "order-delivery-queue"\n args: ["order12"]\n )\n}\n'})}),"\n",(0,t.jsxs)(n.p,{children:["After a successful run, you will get the following result which includes the ",(0,t.jsx)(n.code,{children:"run_id"})," of the workflow which has just been started."]}),"\n",(0,t.jsx)("img",{src:"/images/blog/execution-flow-paradigms/start-workflow-result.png",alt:"Query result"}),"\n",(0,t.jsx)(n.p,{children:"You can also check the temporal web UI to monitor your workflows and you should see a result similar to this one."}),"\n",(0,t.jsx)("img",{src:"/images/blog/execution-flow-paradigms/temporal-web-ui.png",alt:"Workflows dashboard"}),"\n",(0,t.jsxs)(n.p,{children:["You can explore the ",(0,t.jsx)(n.a,{href:"/docs/reference/runtimes/temporal",children:"Temporal Runtime"})," for more info."]}),"\n",(0,t.jsx)(n.p,{children:"This wraps up the blog, thanks for reading until the end :)"})]})}function u(e={}){const{wrapper:n}={...(0,s.R)(),...e.components};return n?(0,t.jsx)(n,{...e,children:(0,t.jsx)(p,{...e})}):p(e)}},65480:(e,n,r)=>{r.d(n,{Ay:()=>o,gc:()=>a});r(30758);var t=r(3733),s=r(56315),i=r(86070);function o(e){let{children:n}=e;const[r,o]=(0,t.e)();return(0,i.jsx)(s.mS,{choices:{typescript:"Typescript SDK",python:"Python SDK"},choice:r,onChange:o,children:n})}function a(e){let{children:n}=e;const[r]=(0,t.e)();return(0,i.jsx)(s.q9,{choices:{typescript:"Typescript SDK",python:"Python SDK"},choice:r,children:n})}},16676:(e,n,r)=>{r.d(n,{A:()=>t});const t=r.p+"assets/images/eda.drawio-9d730aef7e9f00ffed737626d602be5c.svg"},35936:(e,n,r)=>{r.d(n,{A:()=>t});const t=r.p+"assets/images/saga.drawio-6f492c8332ead1021dde63fa7daf0efd.svg"}}]); \ No newline at end of file +"use strict";(self.webpackChunkwebsite=self.webpackChunkwebsite||[]).push([[3126],{2845:(e,n,r)=>{r.r(n),r.d(n,{assets:()=>d,contentTitle:()=>l,default:()=>u,frontMatter:()=>a,metadata:()=>c,toc:()=>h});var t=r(86070),s=r(25710),i=r(27676),o=r(65480);const a={},l="Distributed execution flow paradigms",c={permalink:"/blog/2024/08/27/distributed-execution-flow-paradigms",editUrl:"https://github.com/metatypedev/metatype/tree/main/docs/metatype.dev/blog/2024-08-27-distributed-execution-flow-paradigms/index.mdx",source:"@site/blog/2024-08-27-distributed-execution-flow-paradigms/index.mdx",title:"Distributed execution flow paradigms",description:"In this age of cloud development and microservices architecture, problems start to arise with the increased workloads that run in the system. Imagine an e-commerce platform where a customer places an order for a product during a high-demand sale event. The order triggers a series of interconnected processes: payment processing, inventory checks, packaging, shipping, and final delivery. Each of these processes might be handled by different microservices, potentially running on different servers or even in different data centers. What happens if the payment service goes down right after the payment is authorized but before the inventory is updated? Or if the packaging service fails just after the inventory is deducted but before the item is packed? Without a robust mechanism to ensure that each step in the workflow completes successfully and that failures are properly handled, you could end up with unhappy customers, lost orders, and inventory discrepancies.",date:"2024-08-27T00:00:00.000Z",tags:[],readingTime:10.92,hasTruncateMarker:!1,authors:[],frontMatter:{},unlisted:!1,nextItem:{title:"Python on WebAssembly: How?",permalink:"/blog/2024/08/26/python-on-webassembly"}},d={authorsImageUrls:[]},h=[{value:"1. Event-Driven Architecture with Message Queues",id:"1-event-driven-architecture-with-message-queues",level:3},{value:"Advantages",id:"advantages",level:4},{value:"Challenges",id:"challenges",level:4},{value:"2. The Saga Pattern",id:"2-the-saga-pattern",level:3},{value:"Advantages",id:"advantages-1",level:4},{value:"Drawbacks",id:"drawbacks",level:4},{value:"3. Stateful Orchestrators",id:"3-stateful-orchestrators",level:3},{value:"Advantages",id:"advantages-2",level:4},{value:"Challenges",id:"challenges-1",level:4},{value:"4. Durable Execution",id:"4-durable-execution",level:3},{value:"Advantages",id:"advantages-3",level:4},{value:"Challenges",id:"challenges-2",level:4}];function p(e){const n={a:"a",admonition:"admonition",code:"code",h3:"h3",h4:"h4",img:"img",li:"li",p:"p",pre:"pre",strong:"strong",ul:"ul",...(0,s.R)(),...e.components},{Details:a}=n;return a||function(e,n){throw new Error("Expected "+(n?"component":"object")+" `"+e+"` to be defined: you likely forgot to import, pass, or provide it.")}("Details",!0),(0,t.jsxs)(t.Fragment,{children:[(0,t.jsx)(n.p,{children:"In this age of cloud development and microservices architecture, problems start to arise with the increased workloads that run in the system. Imagine an e-commerce platform where a customer places an order for a product during a high-demand sale event. The order triggers a series of interconnected processes: payment processing, inventory checks, packaging, shipping, and final delivery. Each of these processes might be handled by different microservices, potentially running on different servers or even in different data centers. What happens if the payment service goes down right after the payment is authorized but before the inventory is updated? Or if the packaging service fails just after the inventory is deducted but before the item is packed? Without a robust mechanism to ensure that each step in the workflow completes successfully and that failures are properly handled, you could end up with unhappy customers, lost orders, and inventory discrepancies."}),"\n",(0,t.jsx)(n.p,{children:"Having multiple components in your system introduces more failure points, which is a common phenomenon in complex systems. But one important behavior any application must ensure is that the execution flow reaches its completion. As systems grow in features and complexity, the likelihood of long-running processes increases. To ensure these processes complete as intended, several solutions have been introduced over the last few decades.\nLet's explore some of the solutions that have been proposed to achieve workflow completeness."}),"\n",(0,t.jsx)(n.h3,{id:"1-event-driven-architecture-with-message-queues",children:"1. Event-Driven Architecture with Message Queues"}),"\n",(0,t.jsx)(n.p,{children:"This architecture relies heavily on services communicating by publishing and subscribing to events using message queues. Message queues are persistent storages that ensure data is not lost during failures or service unavailability. Components in a distributed system synchronize by using events/messages through these independent services. While this approach offers service decomposability and fault tolerance, it has some shortcomings. For example, using message queues comes with the overhead of managing messages (e.g., deduplication and message ordering). It also isn\u2019t ideal for systems requiring immediate consistency across components. Some technologies and patterns that utilize this architecture include:"}),"\n",(0,t.jsxs)(n.ul,{children:["\n",(0,t.jsx)(n.li,{children:(0,t.jsx)(n.a,{href:"https://www.rabbitmq.com/",children:"RabbitMQ"})}),"\n",(0,t.jsx)(n.li,{children:(0,t.jsx)(n.a,{href:"https://aws.amazon.com/sqs/",children:"Amazon SQS"})}),"\n"]}),"\n",(0,t.jsx)(n.p,{children:(0,t.jsx)(n.img,{src:r(16676).A+""})}),"\n",(0,t.jsx)("div",{style:{marginLeft:"5em"},children:(0,t.jsx)(n.p,{children:"Fig. Event Driven Architecture with Message Queues - RabbitMQ"})}),"\n",(0,t.jsx)(n.h4,{id:"advantages",children:"Advantages"}),"\n",(0,t.jsxs)(n.ul,{children:["\n",(0,t.jsx)(n.li,{children:"Improved Scalability"}),"\n",(0,t.jsx)(n.li,{children:"Enhanced Responsiveness"}),"\n",(0,t.jsx)(n.li,{children:"Enhanced Fault Tolerance"}),"\n",(0,t.jsx)(n.li,{children:"Simplified Complex Workflows"}),"\n",(0,t.jsx)(n.li,{children:"Real-Time Data Processing"}),"\n"]}),"\n",(0,t.jsx)(n.h4,{id:"challenges",children:"Challenges"}),"\n",(0,t.jsxs)(n.ul,{children:["\n",(0,t.jsx)(n.li,{children:"Event Ordering"}),"\n",(0,t.jsx)(n.li,{children:"Data Consistency"}),"\n",(0,t.jsx)(n.li,{children:"Monitoring and Debugging"}),"\n",(0,t.jsx)(n.li,{children:"Event Deduplication"}),"\n"]}),"\n",(0,t.jsx)(n.p,{children:"You can mitigate or reduce these challenges by following best practices like Event Sourcing, Idempotent Processing, CQRS (Command Query Responsibility Segregation), and Event Versioning."}),"\n",(0,t.jsxs)(n.h3,{id:"2-the-saga-pattern",children:["2. The ",(0,t.jsx)(n.a,{href:"https://microservices.io/patterns/data/saga.html",children:"Saga Pattern"})]}),"\n",(0,t.jsx)(n.p,{children:"This design pattern aims to achieve consistency across different services in a distributed system by breaking complex transactions spanning multiple components into a series of local transactions. Each of these transactions triggers an event or message that starts the next transaction in the sequence. If any local transaction fails to complete, a series of compensating actions roll back the effects of preceding transactions. While the orchestration of local transactions can vary, the pattern aims to achieve consistency in a microservices-based system. Events are designed to be stored in durable storage systems or logs, providing a trail to reconstruct the system to a state after a failure. While the saga pattern is an effective way to ensure consistency, it can be challenging to implement timer/timeout-based workflows and to design and implement the compensating actions for local transactions."}),"\n",(0,t.jsxs)(n.p,{children:[(0,t.jsx)(n.strong,{children:"Note"}),": In the Saga pattern, a compensating transaction must be idempotent and retryable. These principles ensure that transactions can be managed without manual intervention."]}),"\n",(0,t.jsx)(n.p,{children:(0,t.jsx)(n.img,{src:r(35936).A+""})}),"\n",(0,t.jsx)("div",{style:{marginLeft:"10em"},children:(0,t.jsx)(n.p,{children:"Fig. The Saga Pattern for Order delivery system"})}),"\n",(0,t.jsx)(n.h4,{id:"advantages-1",children:"Advantages"}),"\n",(0,t.jsxs)(n.ul,{children:["\n",(0,t.jsx)(n.li,{children:"Ensures data consistency in a distributed system without tight coupling."}),"\n",(0,t.jsx)(n.li,{children:"Provides Roll back if one of the operations in the sequence fails."}),"\n"]}),"\n",(0,t.jsx)(n.h4,{id:"drawbacks",children:"Drawbacks"}),"\n",(0,t.jsxs)(n.ul,{children:["\n",(0,t.jsx)(n.li,{children:"Might be challenging to implement initially."}),"\n",(0,t.jsx)(n.li,{children:"Hard to debug."}),"\n",(0,t.jsx)(n.li,{children:"Compensating transactions don\u2019t always work."}),"\n"]}),"\n",(0,t.jsxs)(n.h3,{id:"3-stateful-orchestrators",children:["3. ",(0,t.jsx)(n.a,{href:"https://docs.oracle.com/en/applications/jd-edwards/cross-product/9.2/eotos/creating-a-stateful-orchestration-release-9-2-8-3.html#u30249073",children:"Stateful Orchestrators"})]}),"\n",(0,t.jsx)(n.p,{children:"Stateful orchestrators provide a solution for long-running workflows by maintaining the state of each step in a workflow. Each step in a workflow represents a task, and these tasks are represented as states inside workflows. Workflows are defined as state machines or directed acyclic graphs (DAGs). In this approach, an orchestrator handles task execution order, transitioning, handling retries, and maintaining state. In the event of a failure, the system can recover from the persisted state. Stateful orchestrators offer significant value in fault tolerance, consistency, and observability. It\u2019s one of the solutions proven effective in modern distributed computing. Some well-known services that provide this solution include:"}),"\n",(0,t.jsxs)(n.ul,{children:["\n",(0,t.jsx)(n.li,{children:(0,t.jsx)(n.a,{href:"https://airflow.apache.org/docs/apache-airflow/stable/core-concepts/overview.html",children:"Apache Airflow"})}),"\n",(0,t.jsx)(n.li,{children:(0,t.jsx)(n.a,{href:"https://azure.microsoft.com/en-us/products/logic-apps",children:"Azure Logic Apps"})}),"\n"]}),"\n",(0,t.jsx)(n.h4,{id:"advantages-2",children:"Advantages"}),"\n",(0,t.jsxs)(n.ul,{children:["\n",(0,t.jsxs)(n.li,{children:[(0,t.jsx)(n.strong,{children:"High Resiliency"}),": Stateful orchestrators provide high resiliency in case of outages, ensuring that workflows can continue from where they left off."]}),"\n",(0,t.jsxs)(n.li,{children:[(0,t.jsx)(n.strong,{children:"Data Persistence"}),": They allow you to keep, review, or reference data from previous events, which is useful for long-running processes."]}),"\n",(0,t.jsxs)(n.li,{children:[(0,t.jsx)(n.strong,{children:"Extended Runtime"}),": Stateful workflows can continue running for much longer than stateless workflows, making them suitable for complex and long-running tasks."]}),"\n"]}),"\n",(0,t.jsx)(n.h4,{id:"challenges-1",children:"Challenges"}),"\n",(0,t.jsxs)(n.ul,{children:["\n",(0,t.jsxs)(n.li,{children:[(0,t.jsx)(n.strong,{children:"Additional Complexity"}),": They introduce additional complexity, requiring you to manage issues such as load balancing, CPU and memory usage, and networking."]}),"\n",(0,t.jsxs)(n.li,{children:[(0,t.jsx)(n.strong,{children:"Cost"}),": With stateful workflows, you pay for the VMs that are running in the cluster, whereas with stateless workflows, you pay only for the actual compute resources consumed."]}),"\n"]}),"\n",(0,t.jsx)(n.h3,{id:"4-durable-execution",children:"4. Durable Execution"}),"\n",(0,t.jsx)(n.p,{children:"Durable execution refers to the ability of a system to preserve the state of an application and persist execution despite failures or interruptions. Durable execution ensures that for every task, its inputs, outputs, call stack, and local variables are persisted. These constraints, or rather features, allow a system to automatically retry or continue running in the face of infrastructure or system failures, ultimately ensuring completion."}),"\n",(0,t.jsx)(n.p,{children:"Durable execution isn\u2019t a completely distinct solution from the ones listed above but rather incorporates some of their strengths while presenting a more comprehensive approach to achieving consistency, fault tolerance, data integrity, resilience for long-running processes, and observability."}),"\n",(0,t.jsx)("img",{src:"/images/blog/execution-flow-paradigms/durable-exec.svg",alt:"Durable workflow engine - Temporal"}),"\n",(0,t.jsx)("div",{style:{marginLeft:"15em"},children:"Fig. Durable workflow engine"}),"\n",(0,t.jsx)(n.h4,{id:"advantages-3",children:"Advantages"}),"\n",(0,t.jsxs)(n.ul,{children:["\n",(0,t.jsxs)(n.li,{children:[(0,t.jsx)(n.strong,{children:"Reduced Manual Intervention"}),": Minimizes the need for human intervention by handling retries and failures programmatically."]}),"\n",(0,t.jsxs)(n.li,{children:[(0,t.jsx)(n.strong,{children:"Improved Observability"}),": Provides a clear audit trail and visibility into the state of workflows, which aids in debugging and monitoring."]}),"\n",(0,t.jsxs)(n.li,{children:[(0,t.jsx)(n.strong,{children:"Scalability"}),": Scales efficiently across distributed systems while maintaining workflow integrity."]}),"\n"]}),"\n",(0,t.jsx)(n.h4,{id:"challenges-2",children:"Challenges"}),"\n",(0,t.jsxs)(n.ul,{children:["\n",(0,t.jsxs)(n.li,{children:[(0,t.jsx)(n.strong,{children:"Resource Intensive"}),": Persistent state storage and management can consume significant resources, especially in large-scale systems."]}),"\n",(0,t.jsxs)(n.li,{children:[(0,t.jsx)(n.strong,{children:"Latency"}),": The need to persist state and handle retries can introduce latency in the execution flow."]}),"\n"]}),"\n",(0,t.jsx)(n.p,{children:"As durable execution grows to be a fundamental driver of distributed computing, some of the solutions which use this architecture are"}),"\n",(0,t.jsxs)(n.ul,{children:["\n",(0,t.jsx)(n.li,{children:(0,t.jsx)(n.a,{href:"https://temporal.io/",children:"Temporal"})}),"\n",(0,t.jsx)(n.li,{children:(0,t.jsx)(n.a,{href:"https://cadenceworkflow.io/",children:"Uber Cadence"})}),"\n"]}),"\n",(0,t.jsxs)(n.p,{children:["Among these, ",(0,t.jsx)(n.a,{href:"https://temporal.io/",children:"Temporal"})," has grown in influence, used by companies like SnapChat, HashiCorp, Stripe, DoorDash, and DataDog. Its success is driven by its practical application in real-world scenarios and the expertise of its founders."]}),"\n",(0,t.jsxs)(n.p,{children:["At Metatype, we recognize the value of durable execution and are committed to making it accessible. Our ",(0,t.jsx)(n.a,{href:"/docs/reference/runtimes/temporal",children:"Temporal Runtime"})," integrates seamlessly into our declarative API development platform, enabling users to harness the power of Temporal directly within Metatype. For those interested in exploring further, our documentation provides a detailed guide on getting started with ",(0,t.jsx)(n.a,{href:"/docs/reference/runtimes/temporal",children:"Temporal Runtime"}),"."]}),"\n",(0,t.jsx)(n.p,{children:"Below is an example of how you can build a simple API to interact with an order delivery temporal workflow within Metatype."}),"\n",(0,t.jsx)(n.admonition,{type:"note",children:(0,t.jsxs)(n.p,{children:["If you are new to Metatype or haven\u2019t set it up yet in your development environment. You can follow this ",(0,t.jsx)(n.a,{href:"/docs/tutorials/quick-start",children:"guideline"}),"."]})}),"\n",(0,t.jsx)(n.p,{children:"For this example, the order delivery system will have few components/services such as Payment, Inventory and Delivery."}),"\n",(0,t.jsx)(n.p,{children:"Your temporal workflow definition should look similar to the one below."}),"\n",(0,t.jsxs)(o.Ay,{children:[(0,t.jsxs)(i.A,{value:"typescript",children:[(0,t.jsxs)(a,{children:[(0,t.jsxs)("summary",{children:["Activities definition inside ",(0,t.jsx)(n.code,{children:"src/activities.ts"}),":`"]}),(0,t.jsx)(n.pre,{children:(0,t.jsx)(n.code,{className:"language-typescript",children:'async function sleep(time: number) {\n return new Promise((resolve) => {\n setTimeout(resolve, time);\n });\n}\n\nexport async function processPayment(orderId: string): Promise {\n console.log(`Processing payment for order ${orderId}`);\n // Simulate payment processing logic\n await sleep(2);\n return "Payment processed";\n}\n\nexport async function checkInventory(orderId: string): Promise {\n console.log(`Checking inventory for order ${orderId}`);\n // Simulate inventory check logic\n await sleep(2);\n return "Inventory available";\n}\n\nexport async function deliverOrder(orderId: string): Promise {\n console.log(`Delivering order ${orderId}`);\n // Simulate delivery logic\n await sleep(5);\n return "Order delivered";\n}\n'})})]}),(0,t.jsxs)(a,{children:[(0,t.jsxs)("summary",{children:["Workflow definition inside ",(0,t.jsx)(n.code,{children:"src/workflows.ts"}),":"]}),(0,t.jsx)(n.pre,{children:(0,t.jsx)(n.code,{className:"language-typescript",metastring:'import {proxyActivities} from "@temporalio/workflow";',children:'\nexport const { processPayment, checkInventory, deliverOrder } =\n proxyActivities<{\n processPayment(orderId: string): Promise;\n checkInventory(orderId: string): Promise;\n deliverOrder(orderId: string): Promise;\n }>({\n startToCloseTimeout: "10 seconds",\n });\n\nexport async function OrderWorkflow(orderId: string): Promise {\n const paymentResult = await processPayment(orderId);\n const inventoryResult = await checkInventory(orderId);\n const deliveryResult = await deliverOrder(orderId);\n return `Order ${orderId} completed with results: ${paymentResult}, ${inventoryResult}, ${deliveryResult}`;\n}\n'})})]}),(0,t.jsxs)(a,{children:[(0,t.jsxs)("summary",{children:["Worker definintion inside ",(0,t.jsx)(n.code,{children:"src/worker.ts"}),":"]}),(0,t.jsx)(n.pre,{children:(0,t.jsx)(n.code,{className:"language-typescript",children:'import { NativeConnection, Worker } from "@temporalio/worker";\nimport * as activities from "./activities";\nimport { TASK_QUEUE_NAME } from "./shared";\n\nasync function run() {\n const connection = await NativeConnection.connect({\n address: "localhost:7233",\n });\n\n const worker = await Worker.create({\n connection,\n namespace: "default",\n taskQueue: TASK_QUEUE_NAME,\n workflowsPath: require.resolve("./workflows"),\n activities,\n });\n\n await worker.run();\n}\n\nrun().catch((err) => {\n console.error(err);\n process.exit(1);\n});\n'})})]}),(0,t.jsxs)(n.p,{children:["After you have setup the above components, now you need a client to start of any ",(0,t.jsx)(n.code,{children:"OrderWorkflow"}),". Here is where metatype comes in, through the simple APIs ",(0,t.jsx)(n.a,{href:"/docs/reference/runtimes/temporal",children:"Temporal Runtime"})," exposes, you can communicate with your temporal cluster.\nDown below is the workflow communication bridge for this system expressed within a ",(0,t.jsx)(n.a,{href:"/docs/reference/typegraph",children:"typegraph"})," which includes endpoints to start a new workflow and describe an existing one."]}),(0,t.jsx)(n.pre,{children:(0,t.jsx)(n.code,{className:"language-typescript",children:'import { Policy, t, typegraph } from "@typegraph/sdk/index.ts";\nimport { TemporalRuntime } from "@typegraph/sdk/providers/temporal.ts";\n\ntypegraph(\n {\n name: "order_delivery",\n },\n (g: any) => {\n const pub = Policy.public();\n\n const temporal = new TemporalRuntime({\n name: "order_delivery",\n hostSecret: "HOST",\n namespaceSecret: "NAMESPACE",\n });\n\n const workflow_id = "order-delivery-1";\n\n const order_id = t.string();\n\n g.expose(\n {\n start: temporal.startWorkflow("OrderWorkflow", order_id),\n describe: workflow_id\n ? temporal.describeWorkflow().reduce({ workflow_id })\n : temporal.describeWorkflow(),\n },\n pub,\n );\n },\n);\n'})})]}),(0,t.jsxs)(i.A,{value:"python",children:[(0,t.jsxs)(a,{children:[(0,t.jsxs)("summary",{children:["Activities definition inside ",(0,t.jsx)(n.code,{children:"activities.py"}),"."]}),(0,t.jsx)(n.pre,{children:(0,t.jsx)(n.code,{className:"language-python",children:'from temporalio import activity\nimport time\n\n@activity.defn\nasync def process_payment(order_id: str) -> str:\n print(f"Processing payment for order {order_id}")\n # Simulate payment processing logic\n time.sleep(5)\n return "Payment processed"\n\n@activity.defn\nasync def check_inventory(order_id: str) -> str:\n print(f"Checking inventory for order {order_id}")\n # Simulate inventory check logic\n time.sleep(4)\n return "Inventory available"\n\n@activity.defn\nasync def deliver_order(order_id: str) -> str:\n print(f"Delivering order {order_id}")\n time.sleep(8)\n # Simulate delivery logic\n return "Order delivered"\n'})})]}),(0,t.jsxs)(a,{children:[(0,t.jsxs)("summary",{children:["Worker defintion inside ",(0,t.jsx)(n.code,{children:"run_worker.py"}),"."]}),(0,t.jsx)(n.pre,{children:(0,t.jsx)(n.code,{className:"language-python",children:'import asyncio\n\nfrom temporalio.client import Client\nfrom temporalio.worker import Worker\n\nfrom activities import process_payment, deliver_order, check_inventory\nfrom shared import ORDER_DELIVERY_QUEUE\nfrom workflows import OrderWorkflow\n\n\nasync def main() -> None:\n client: Client = await Client.connect("localhost:7233", namespace="default")\n worker: Worker = Worker(\n client,\n task_queue=ORDER_DELIVERY_QUEUE,\n workflows=[OrderWorkflow],\n activities=[process_payment, check_inventory, deliver_order],\n )\n await worker.run()\n\n\nif __name__ == "__main__":\n asyncio.run(main())\n'})})]}),(0,t.jsxs)(n.p,{children:["After you have setup the above components, now you need a client to start of any ",(0,t.jsx)(n.code,{children:"OrderWorkflow"}),". Here is where metatype comes in, through the simple APIs ",(0,t.jsx)(n.a,{href:"/docs/reference/runtimes/temporal",children:"Temporal Runtime"})," exposes, you can communicate with your temporal cluster.\nDown below is the workflow communication bridge for this system expressed within a ",(0,t.jsx)(n.a,{href:"/docs/reference/typegraph",children:"typegraph"})," which includes endpoints to start a new workflow and describe an existing one."]}),(0,t.jsx)(n.pre,{children:(0,t.jsx)(n.code,{className:"language-python",children:'from typegraph import t, typegraph, Policy, Graph\nfrom typegraph.providers.temporal import TemporalRuntime\n\n\n@typegraph()\ndef example(g: Graph):\n public = Policy.public()\n\n temporal = TemporalRuntime(\n "example", "HOST", namespace_secret="NAMESPACE"\n )\n\n workflow_id = "order-delivery-1"\n\n order_id = t.string()\n\n g.expose(\n public,\n start=temporal.start_workflow("OrderWorkflow", order_id),\n describe=temporal.describe_workflow().reduce({"workflow_id": workflow_id})\n if workflow_id\n else temporal.describe_workflow(),\n )\n'})})]})]}),"\n",(0,t.jsxs)(n.p,{children:["You need to add the secrets ",(0,t.jsx)(n.code,{children:"HOST"})," and ",(0,t.jsx)(n.code,{children:"NAMESPACE"})," under your typegraph name inside the ",(0,t.jsx)(n.code,{children:"metatype.yaml"})," file. These secrets are important to connect with your temporal cluster and can be safely stored in the config file as shown below."]}),"\n",(0,t.jsxs)(a,{children:[(0,t.jsx)("summary",{children:"metatype.yaml"}),(0,t.jsx)(n.pre,{children:(0,t.jsx)(n.code,{className:"language-yaml",children:'typegate:\n dev:\n url: "http://localhost:7890"\n username: admin\n password: password\n secrets:\n example:\n POSTGRES: "postgresql://postgres:password@postgres:5432/db"\n HOST: "http://localhost:7233"\n NAMESPACE: "default"\n'})})]}),"\n",(0,t.jsxs)(n.p,{children:["You need to add only the last two lines as the others are auto-generated. Note that secrets are defined under the ",(0,t.jsx)(n.code,{children:"example"})," parent, which is the name of your typegraph. If the name doesn't match, you will face secret not found issues when deploying your typegraph."]}),"\n",(0,t.jsxs)(n.p,{children:["Before deploying the above typegraph, you need to start the temporal server and the worker. You need to have ",(0,t.jsx)(n.a,{href:"https://learn.temporal.io/getting_started/typescript/dev_environment/#set-up-a-local-temporal-service-for-development-with-temporal-cli",children:"temporal"})," installed on your machine."]}),"\n",(0,t.jsxs)(a,{children:[(0,t.jsx)("summary",{children:"Boot up temporal"}),(0,t.jsx)(n.p,{children:"Start the temporal server."}),(0,t.jsx)(n.pre,{children:(0,t.jsx)(n.code,{className:"language-bash",children:"temporal server start-dev\n"})}),(0,t.jsx)(n.p,{children:"Start the worker."}),(0,t.jsxs)(o.Ay,{children:[(0,t.jsx)(i.A,{value:"typescript",children:(0,t.jsx)(n.p,{children:(0,t.jsx)(n.code,{children:"typescript npx ts-node src/worker.ts "})})}),(0,t.jsx)(i.A,{value:"python",children:(0,t.jsx)(n.code,{children:"python python run_worker.py "})})]})]}),"\n",(0,t.jsxs)(n.p,{children:["After booting the temporal server, run the command down below to get a locally spinning ",(0,t.jsx)(n.a,{href:"/docs/reference/typegate",children:"typegate"})," instance with your typegraph deployed."]}),"\n",(0,t.jsx)(n.pre,{children:(0,t.jsx)(n.code,{className:"language-bash",children:"meta dev\n"})}),"\n",(0,t.jsxs)(n.p,{children:["After completing the above steps, you can access the web GraphQL client of the typegate at ",(0,t.jsx)(n.a,{href:"http://localhost:7890/example",children:(0,t.jsx)(n.code,{children:"http://localhost:7890/example"})}),". Run this query inside the client to start your workflow."]}),"\n",(0,t.jsx)(n.pre,{children:(0,t.jsx)(n.code,{className:"language-graphql",children:'mutation {\n start(\n workflow_id: "order-delivery-3"\n task_queue: "order-delivery-queue"\n args: ["order12"]\n )\n}\n'})}),"\n",(0,t.jsxs)(n.p,{children:["After a successful run, you will get the following result which includes the ",(0,t.jsx)(n.code,{children:"run_id"})," of the workflow which has just been started."]}),"\n",(0,t.jsx)("img",{src:"/images/blog/execution-flow-paradigms/start-workflow-result.png",alt:"Query result"}),"\n",(0,t.jsx)(n.p,{children:"You can also check the temporal web UI to monitor your workflows and you should see a result similar to this one."}),"\n",(0,t.jsx)("img",{src:"/images/blog/execution-flow-paradigms/temporal-web-ui.png",alt:"Workflows dashboard"}),"\n",(0,t.jsxs)(n.p,{children:["You can explore the ",(0,t.jsx)(n.a,{href:"/docs/reference/runtimes/temporal",children:"Temporal Runtime"})," for more info."]}),"\n",(0,t.jsx)(n.p,{children:"This wraps up the blog, thanks for reading until the end :)"})]})}function u(e={}){const{wrapper:n}={...(0,s.R)(),...e.components};return n?(0,t.jsx)(n,{...e,children:(0,t.jsx)(p,{...e})}):p(e)}},65480:(e,n,r)=>{r.d(n,{Ay:()=>o,gc:()=>a});r(30758);var t=r(3733),s=r(56315),i=r(86070);function o(e){let{children:n}=e;const[r,o]=(0,t.e)();return(0,i.jsx)(s.mS,{choices:{typescript:"Typescript SDK",python:"Python SDK"},choice:r,onChange:o,children:n})}function a(e){let{children:n}=e;const[r]=(0,t.e)();return(0,i.jsx)(s.q9,{choices:{typescript:"Typescript SDK",python:"Python SDK"},choice:r,children:n})}},16676:(e,n,r)=>{r.d(n,{A:()=>t});const t=r.p+"assets/images/eda.drawio-9d730aef7e9f00ffed737626d602be5c.svg"},35936:(e,n,r)=>{r.d(n,{A:()=>t});const t=r.p+"assets/images/saga.drawio-6f492c8332ead1021dde63fa7daf0efd.svg"}}]); \ No newline at end of file diff --git a/assets/js/ad5e0346.8ab824fd.js b/assets/js/ad5e0346.8ab824fd.js new file mode 100644 index 0000000000..c1f8ccdb35 --- /dev/null +++ b/assets/js/ad5e0346.8ab824fd.js @@ -0,0 +1 @@ +(self.webpackChunkwebsite=self.webpackChunkwebsite||[]).push([[11],{14344:(e,n,t)=>{"use strict";t.d(n,{Ay:()=>s,RM:()=>r});var a=t(86070),i=t(25710);const r=[];function o(e){const n={a:"a",admonition:"admonition",code:"code",li:"li",p:"p",pre:"pre",ul:"ul",...(0,i.R)(),...e.components};return(0,a.jsxs)(a.Fragment,{children:[(0,a.jsx)(n.admonition,{type:"info",children:(0,a.jsxs)(n.p,{children:["Metatype is only supported on macOS and Linux. Windows users should use ",(0,a.jsx)(n.a,{href:"https://learn.microsoft.com/windows/wsl/install",children:"Linux on Windows with WSL"}),"."]})}),"\n",(0,a.jsxs)(n.p,{children:["You can download the binary from the\n",(0,a.jsx)(n.a,{href:"https://github.com/metatypedev/metatype/releases/",children:"releases page"}),", make it\nexecutable and add it to your ",(0,a.jsx)(n.code,{children:"PATH"})," or use the automated method below."]}),"\n",(0,a.jsxs)(n.ul,{children:["\n",(0,a.jsxs)(n.li,{children:["\n",(0,a.jsx)(n.p,{children:"An installer script is also provided for the CLI in our repository. Curl and install in it with the following one-liner. The installer may ask for your password."}),"\n",(0,a.jsx)(n.pre,{children:(0,a.jsx)(n.code,{className:"language-bash",children:"curl -fsSL https://raw.githubusercontent.com/metatypedev/metatype/main/installer.sh | bash\n"})}),"\n"]}),"\n"]}),"\n",(0,a.jsx)(n.admonition,{type:"info",children:(0,a.jsxs)(n.ul,{children:["\n",(0,a.jsxs)(n.li,{children:["\n",(0,a.jsxs)(n.p,{children:["For later use, you can run the following command to upgrade ",(0,a.jsx)(n.code,{children:"Meta CLI"})," to a newer version. If your Meta CLI is up to date, you will get an ",(0,a.jsx)(n.code,{children:"Already up to date!"})," response."]}),"\n",(0,a.jsx)(n.pre,{children:(0,a.jsx)(n.code,{className:"language-bash",children:"meta upgrade\n"})}),"\n"]}),"\n"]})}),"\n",(0,a.jsxs)(n.p,{children:["That's it! You are done installing ",(0,a.jsx)(n.code,{children:"Meta CLI"}),"."]})]})}function s(e={}){const{wrapper:n}={...(0,i.R)(),...e.components};return n?(0,a.jsx)(n,{...e,children:(0,a.jsx)(o,{...e})}):o(e)}},95459:(e,n,t)=>{"use strict";t.r(n),t.d(n,{assets:()=>u,contentTitle:()=>c,default:()=>m,frontMatter:()=>d,metadata:()=>l,toc:()=>p});var a=t(86070),i=t(25710),r=t(65480),o=t(27676),s=t(65671);t(14344),t(7871);const d={sidebar_position:3},c="Metatype Basics",l={id:"tutorials/metatype-basics/index",title:"Metatype Basics",description:"This page will walk you through a real world API with data storage and authorization.",source:"@site/docs/tutorials/metatype-basics/index.mdx",sourceDirName:"tutorials/metatype-basics",slug:"/tutorials/metatype-basics/",permalink:"/docs/tutorials/metatype-basics/",draft:!1,unlisted:!1,editUrl:"https://github.com/metatypedev/metatype/tree/main/docs/metatype.dev/docs/tutorials/metatype-basics/index.mdx",tags:[],version:"current",sidebarPosition:3,frontMatter:{sidebar_position:3},sidebar:"docs",previous:{title:"Quick-start",permalink:"/docs/tutorials/quick-start/"},next:{title:"Custom functions",permalink:"/docs/guides/external-functions/"}},u={},p=[{value:"What are you building?",id:"what-are-you-building",level:2},{value:"Setup",id:"setup",level:2},{value:"Create a new project",id:"create-a-new-project",level:3},{value:"Launch typegate",id:"launch-typegate",level:3},{value:"Make sure it's all working",id:"make-sure-its-all-working",level:3},{value:"Building our Models",id:"building-our-models",level:2},{value:"Exposing our application",id:"exposing-our-application",level:2},{value:"The Prisma Runtime",id:"the-prisma-runtime",level:3},{value:"Policies",id:"policies",level:2},{value:"More Customization for our app",id:"more-customization-for-our-app",level:2},{value:"Preventing Unauthorized Creation of Related Objects",id:"preventing-unauthorized-creation-of-related-objects",level:3},{value:"Restrict Update Operation on Selected Fields",id:"restrict-update-operation-on-selected-fields",level:3},{value:"Creating REST endpoints",id:"creating-rest-endpoints",level:3}];function h(e){const n={a:"a",admonition:"admonition",code:"code",h1:"h1",h2:"h2",h3:"h3",li:"li",p:"p",pre:"pre",strong:"strong",ul:"ul",...(0,i.R)(),...e.components};return(0,a.jsxs)(a.Fragment,{children:[(0,a.jsx)(n.h1,{id:"metatype-basics",children:"Metatype Basics"}),"\n",(0,a.jsx)(n.p,{children:(0,a.jsx)(n.strong,{children:"This page will walk you through a real world API with data storage and authorization."})}),"\n",(0,a.jsx)(n.admonition,{title:"You will learn",type:"note",children:(0,a.jsxs)(n.ul,{children:["\n",(0,a.jsx)(n.li,{children:"How to setup your development for metatype projects."}),"\n",(0,a.jsx)(n.li,{children:"How to run the typegate on the docker runtime."}),"\n",(0,a.jsx)(n.li,{children:"How to create/read/update/delete data."}),"\n",(0,a.jsx)(n.li,{children:"How to write custom business logic."}),"\n",(0,a.jsx)(n.li,{children:"How to authenticate requests."}),"\n",(0,a.jsx)(n.li,{children:"How to protect data with policies."}),"\n"]})}),"\n",(0,a.jsx)(n.h2,{id:"what-are-you-building",children:"What are you building?"}),"\n",(0,a.jsxs)(n.p,{children:["For this tutorial, we'll be implementing an API to power a simple feature roadmap/request hybrid as can be seen on ",(0,a.jsx)(n.a,{href:"https://productlane.com/roadmap",children:"Productlane"}),"."]}),"\n",(0,a.jsx)(n.p,{children:"Looking through the app we can see that the api should allow:"}),"\n",(0,a.jsxs)(n.ul,{children:["\n",(0,a.jsx)(n.li,{children:'Unauthenticated users to submit new "ideas" or vote on any of those already listed.'}),"\n",(0,a.jsx)(n.li,{children:'Specify or vote on the importance of an "idea" from "medium" to "critical" or even submit text with more description.'}),"\n",(0,a.jsx)(n.li,{children:'Admins will be able to move ideas across buckets like "Backlog", "Planned", "In Progress".'}),"\n"]}),"\n","\n",(0,a.jsx)(n.h2,{id:"setup",children:"Setup"}),"\n",(0,a.jsxs)(n.p,{children:["To setup your Metatype development environment, please follow the installation guide ",(0,a.jsx)(n.a,{href:"/docs/tutorials/quick-start#1-meta-cli",children:"here"})]}),"\n",(0,a.jsx)(n.h3,{id:"create-a-new-project",children:"Create a new project"}),"\n",(0,a.jsx)(n.p,{children:"Metatype projects are composed of modular bundles of types, logic and policies called typegraphs. We author typegraphs using modern programming languages & environments. Python and Typescript are currently available for use. The meta-cli allows us to create a new project based on pre-existing templates."}),"\n",(0,a.jsxs)(r.Ay,{children:[(0,a.jsxs)(o.A,{value:"typescript",children:[(0,a.jsxs)(n.p,{children:["Run one the following commands to create a new project under a new directory titled ",(0,a.jsx)(n.code,{children:"tg_roadmap"}),"."]}),(0,a.jsx)(n.pre,{children:(0,a.jsx)(n.code,{className:"language-bash",children:"# using Node/Bun runtimes\nmeta new --template node tg_roadmap\n# ^ project name\n# ^ Use `meta new --help` find out more available templates.\n"})}),(0,a.jsx)(n.pre,{children:(0,a.jsx)(n.code,{className:"language-bash",children:"# using Deno\nmeta new --template deno tg_roadmap\n"})}),(0,a.jsxs)(n.p,{children:["When using Typescript, the ",(0,a.jsx)(n.code,{children:"@typegraph/sdk"})," package exposes all the necessary functions and types we'll need to describe our typegraph. The templates already specify it as as a dependency so all we need to do now is run the following command to download it:"]}),(0,a.jsx)(n.pre,{children:(0,a.jsx)(n.code,{className:"language-bash",children:"# using Deno\ndeno cache api/example.ts # cache dependencies\n\n# using Bun\nbun install\n\n# using pnpm\npnpm install\n\n# using npm\nnpm install\n\n# using yarn\nyarn install\n"})})]}),(0,a.jsxs)(o.A,{value:"python",children:[(0,a.jsxs)(n.p,{children:["Run the following command to create a new project under a new directory titled ",(0,a.jsx)(n.code,{children:"tg_roadmap"}),"."]}),(0,a.jsx)(n.pre,{children:(0,a.jsx)(n.code,{className:"language-bash",children:"meta new --template python tg_roadmap\n# ^ project name\n# ^ Use `meta new --help` find out more available templates.\n"})}),(0,a.jsxs)(n.p,{children:["When using python, the ",(0,a.jsx)(n.code,{children:"typegraph"})," package exposes all the necessary functions and types we'll need to describe our typegraph. We'll need to run the following command to install it:"]}),(0,a.jsx)(n.pre,{children:(0,a.jsx)(n.code,{className:"language-bash",children:"# virtual env\npython3 -m venv .venv\n# other activate scripts should be available for non bash shells\nsource .venv/bin/activate\n\n# using pip\npip3 install typegraph\n\n# using poetry\n# the template has included `typegraph` in the poetry manifest\npoetry install\n"})})]})]}),"\n",(0,a.jsx)(n.h3,{id:"launch-typegate",children:"Launch typegate"}),"\n",(0,a.jsxs)(n.p,{children:["The typegate is a program that runs and orchestrates our typegraphs. We can run it locally for development purposes. Typegate currently requires the Redis database to function and to make it easy to run both, we'll make use of a linux container runtime for this. The Docker runtime to be specific which has installation guides located ",(0,a.jsx)(n.a,{href:"https://docs.docker.com/get-docker/",children:"here"}),"."]}),"\n",(0,a.jsxs)(n.p,{children:["We'll also need the Docker Compose orchestrator which usually comes by default with the ",(0,a.jsx)(n.code,{children:"docker"})," command. Use the following command to check if it is available:"]}),"\n",(0,a.jsx)(n.pre,{children:(0,a.jsx)(n.code,{className:"language-bash",children:"docker compose version\n# Docker Compose version 2.23.0\n"})}),"\n",(0,a.jsxs)(n.p,{children:["...and if not, the official installation guide can be found ",(0,a.jsx)(n.a,{href:"https://docs.docker.com/compose/install/",children:"here"}),"."]}),"\n",(0,a.jsxs)(n.p,{children:["If you have your docker runtime installed and running correctly, you will be able to launch the ",(0,a.jsx)(n.code,{children:"compose.yml"})," file that's bundled in every template.\nThe compose file also includes the ",(0,a.jsx)(n.code,{children:"postgres"})," databases that we'll be using."]}),"\n",(0,a.jsx)(n.p,{children:"To launch the services, navigate your shell to the project directory and run the following command:"}),"\n",(0,a.jsx)(n.pre,{children:(0,a.jsx)(n.code,{className:"language-bash",children:"docker compose up --detach\n# ^ detach means it'll run in the background.\n# Omit to get the all logs in the current terminal\n"})}),"\n",(0,a.jsx)(n.p,{children:"This should download and start typegate and its dependent services."}),"\n",(0,a.jsx)(n.p,{children:"We can observe their log of typegate or any of the other services with the following command. It has to be run from the same project directory."}),"\n",(0,a.jsx)(n.pre,{children:(0,a.jsx)(n.code,{className:"language-bash",children:"docker compose logs typegate --follow\n# ^ Omit service name to look at the combined logs of all services\n"})}),"\n",(0,a.jsx)(n.h3,{id:"make-sure-its-all-working",children:"Make sure it's all working"}),"\n",(0,a.jsx)(n.p,{children:"Run the following to make sure everything's up and running."}),"\n",(0,a.jsx)(n.pre,{children:(0,a.jsx)(n.code,{className:"language-bash",children:"meta doctor\n"})}),"\n",(0,a.jsxs)(n.p,{children:["After running the command, you should get a result similar to then one ",(0,a.jsx)(n.a,{href:"/docs/tutorials/quick-start#4-verify-your-installation",children:"here"}),"."]}),"\n",(0,a.jsx)(n.h2,{id:"building-our-models",children:"Building our Models"}),"\n",(0,a.jsxs)(n.p,{children:["We will be using the ",(0,a.jsx)(n.a,{href:"/docs/reference/types",children:"type system"}),' from the typegraph SDK to describe the shape of the data that flows through our application. In this case, we\'ll build our typegraph around types that represent "ideas", "votes" and "buckets".']}),"\n",(0,a.jsxs)(r.Ay,{children:[(0,a.jsxs)(o.A,{value:"typescript",children:[(0,a.jsxs)(n.p,{children:["Modify the file at ",(0,a.jsx)(n.code,{children:"api/example.ts"})," to look something like the following."]}),(0,a.jsx)(n.pre,{children:(0,a.jsx)(n.code,{className:"language-typescript",children:'// we\'ll need the following imports\nimport { t, typegraph } from "@typegraph/sdk.js";\n\ntypegraph("roadmap", (g) => {\n // ^ each typegraph has a name\n\n const bucket = t.struct({\n // asId and other config items describe the logical properties\n // of our types beyond just the shape\n id: t.integer({}, { asId: true }),\n name: t.string(),\n });\n const idea = t.struct({\n // uuid is just a shorthand alias for `t.string({format: "uuid"})`\n id: t.uuid({ asId: true }),\n name: t.string(),\n // another string shorthand\n authorEmail: t.email(),\n });\n const vote = t.struct({\n id: t.uuid(),\n authorEmail: t.email(),\n // `enum_` is also a shorthand over `t.string`\n importance: t.enum_(["medium", "important", "critical"]).optional(),\n // makes it optional\n desc: t.string().optional(),\n });\n});\n'})})]}),(0,a.jsxs)(o.A,{value:"python",children:[(0,a.jsxs)(n.p,{children:["Modify the file at ",(0,a.jsx)(n.code,{children:"api/example.py"})," to look something like the following."]}),(0,a.jsx)(n.pre,{children:(0,a.jsx)(n.code,{className:"language-python",children:'# we\'ll need the following imports\nfrom typegraph import typegraph, t, Graph\n\n# the typegraph will carry the name of the defining function by default\n@typegraph()\ndef roadmap(g: Graph):\n bucket = t.struct({\n # asId and other config items describe the logical properties\n # of our types beyond just the shape\n "id": t.integer(as_id=True),\n "name": t.string(),\n });\n idea = t.struct({\n # email is just a shorthand alias for `t.string({format: "uuid"})`\n "id": t.uuid(as_id=True),\n "name": t.string(),\n # another string shorthand\n "authorEmail": t.email(),\n });\n vote = t.struct({\n "id": t.uuid(),\n "authorEmail": t.email(),\n # `enum` is also a shorthand over `t.string`\n "importance": t.enum(["medium", "important", "critical"]).optional(),\n # makes it optional\n "desc": t.string().optional(),\n });\n\n'})})]})]}),"\n",(0,a.jsx)(n.p,{children:"The types here are very simple and we haven't yet added any thing that models their relationships but they should do for our purposes."}),"\n",(0,a.jsx)(n.h2,{id:"exposing-our-application",children:"Exposing our application"}),"\n",(0,a.jsx)(n.p,{children:"Typegraphs expose an API to the external world using Function objects. Functions describe the operation that transform some input type into an output type and we define them in scope of different Runtimes, where the actual logic runs. At this early stage, we can make use of the Random runtime which allows us to generate random test data for our types to get a feel of our API."}),"\n",(0,a.jsxs)(r.Ay,{children:[(0,a.jsx)(o.A,{value:"typescript",children:(0,a.jsx)(n.pre,{children:(0,a.jsx)(n.code,{className:"language-typescript",children:'// add need the following imports\nimport { Policy } from "@typegraph/sdk/index.js";\nimport { RandomRuntime } from "@typegraph/sdk/runtimes/random.js";\n\ntypegraph("roadmap", (g) => {\n // ...\n // every exposed function requires access control policies\n // for now, just use the public policy, anyone can access it\n const pub = Policy.public();\n const random = new RandomRuntime({});\n g.expose({\n // generates a random object in the shape of idea\n get_idea: random.gen(idea).withPolicy(pub),\n });\n});\n'})})}),(0,a.jsx)(o.A,{value:"python",children:(0,a.jsx)(n.pre,{children:(0,a.jsx)(n.code,{className:"language-python",children:"# add need the following imports\nfrom typegraph.runtimes.random import RandomRuntime\nfrom typegraph import Policy\n\n@typegraph() def roadmap(g: Graph): # every exposed function requires access control policies # for now, just use the public policy, anyone can access it pub = Policy.public() random = RandomRuntime() g.expose( # generates a random object in the shape of idea get_idea=random.gen(idea).with_policy(pub) )\n\n"})})})]}),"\n",(0,a.jsx)(n.p,{children:"At this point, we can push our typegraph to the locally running typegate node and access it. Run the following command in your project root:"}),"\n",(0,a.jsx)(n.pre,{children:(0,a.jsx)(n.code,{className:"language-bash",children:"# features auto-reload on any changes to your source files\nmeta dev\n"})}),"\n",(0,a.jsxs)(n.p,{children:["Typegate has first-class support for consuming the API through a GraphQl interface and it is enabled by default. It also bundles the GrahpiQl API explorer and you should be able to access it at ",(0,a.jsx)(n.a,{href:"http://localhost:7890/roadmap",children:"http://localhost:7890/roadmap"})," once meta-cli has successfully pushed your typegraph."]}),"\n",(0,a.jsxs)(n.p,{children:["You can go ahead and try out the following ",(0,a.jsx)(n.code,{children:"graphql"})," on the interface and get a feel for it."]}),"\n",(0,a.jsx)(n.pre,{children:(0,a.jsx)(n.code,{className:"language-graphql",children:"query {\n get_idea {\n id\n name\n authorEmail\n }\n}\n"})}),"\n",(0,a.jsx)(n.p,{children:"Or, you can mess around on the playground below."}),"\n",(0,a.jsx)(s.A,{typegraph:"first-typegraph",python:t(84986),typescript:t(24204),query:t(10374)}),"\n",(0,a.jsx)(n.h3,{id:"the-prisma-runtime",children:"The Prisma Runtime"}),"\n",(0,a.jsxs)(n.p,{children:["Now that we have created a simple endpoint that generates random values for our ",(0,a.jsx)(n.code,{children:"idea"})," model/type, let's add a CRUD support to our app. A runtime most apps will be depend on is the ",(0,a.jsx)(n.a,{href:"/docs/reference/runtimes/prisma",children:"Prisma Runtime"})," which allows us to connect to different databases and peform database operations."]}),"\n",(0,a.jsxs)(n.p,{children:["For this tutorial, we'll be making use of the ",(0,a.jsx)(n.code,{children:"PostgreSQL"})," database. If you made use of the ",(0,a.jsx)(n.code,{children:"compose.yml"})," to run typegate as outlined in this tutorial, there should be an instance of Postgres already up. You can check if postgres container is currently running by using the ",(0,a.jsx)(n.code,{children:"meta doctor"})," command."]}),"\n",(0,a.jsxs)(n.p,{children:["If a typegraph needs to access a database, it first needs to be made aware of its address. This is done through secrets. In the root of your project directory, you'll find a file titled ",(0,a.jsx)(n.code,{children:"metatype.yaml"}),". It contains metatype specific configuration for our project such as the top level ",(0,a.jsx)(n.code,{children:"typegates"})," object which we use to specify the location and credentials of the different typegate nodes we'll be using. Each typegate entry also takes an ",(0,a.jsx)(n.a,{href:"/docs/reference/meta-cli/configuration-file#named-secrets",children:(0,a.jsx)(n.code,{children:"secrets"})})," object where we can specify secret to be passed to our typegraphs."]}),"\n",(0,a.jsxs)(n.p,{children:["The keys in the ",(0,a.jsx)(n.code,{children:"secrets"})," object are the names of the typegraphs and the values are objects mapping secret names to their values/sources."]}),"\n",(0,a.jsxs)(n.p,{children:["The ",(0,a.jsx)(n.code,{children:"metatype.yaml"})," should already have a few sample environment variables. Add an entry like the following to give our typegraph access to the database's address:"]}),"\n",(0,a.jsx)(n.pre,{children:(0,a.jsx)(n.code,{className:"language-yaml",children:'typegates:\n dev:\n # ..\n secrets:\n TG_ROADMAP_POSTGRES: "postgresql://postgres:password@postgres:5432/db"\n'})}),"\n",(0,a.jsxs)(n.p,{children:["Meta-cli will auto-reload when it detects changes to ",(0,a.jsx)(n.code,{children:"metatype.yaml"}),". This is because Meta-cli was run in ",(0,a.jsx)(n.code,{children:"dev"})," mode(through the ",(0,a.jsx)(n.code,{children:"meta dev"})," command)."]}),"\n",(0,a.jsx)(n.p,{children:"We can add the Prisma runtime to our typegraph now."}),"\n",(0,a.jsxs)(r.Ay,{children:[(0,a.jsx)(o.A,{value:"typescript",children:(0,a.jsx)(n.pre,{children:(0,a.jsx)(n.code,{className:"language-typescript",children:'// new imports\nimport { PrismaRuntime } from "@typegraph/sdk/providers/prisma.js";\n\ntypegraph("roadmap", (g) => {\n // ...\n\n // the constructor takes the name of the env var directly\n const db = new PrismaRuntime("db", "POSTGRES");\n // ...\n});\n'})})}),(0,a.jsx)(o.A,{value:"python",children:(0,a.jsx)(n.pre,{children:(0,a.jsx)(n.code,{className:"language-python",children:'# new imports\nfrom typegraph.providers.prisma import PrismaRuntime\n\n@typegraph()\ndef roadmap(g: Graph):\n # ..\n\n # the constructor takes the name of the env var directly\n db = PrismaRuntime("db", "POSTGRES")\n # ..\n\n'})})})]}),"\n",(0,a.jsxs)(n.p,{children:["One of the features that the Prisma runtime allows us to implement is relationships. Here, we are creating a one to many relationship between bucket and ideas, also another one to many between ideas and vote. We will be specifiying relationships by using the ",(0,a.jsx)(n.code,{children:"t.list"})," List type and ",(0,a.jsx)(n.code,{children:"g.ref"}),"(method which accepts the name of the model/entity as a parameter) for creating the link. Check the example below for better understanding."]}),"\n",(0,a.jsxs)(r.Ay,{children:[(0,a.jsx)(o.A,{value:"typescript",children:(0,a.jsx)(n.pre,{children:(0,a.jsx)(n.code,{className:"language-typescript",children:'import { PrismaRuntime } from "@typegraph/sdk/providers/prisma.js";\n\ntypegraph("roadmap", (g) => {\n // ...\n\n const db = new PrismaRuntime("db", "POSTGRES");\n\n const bucket = t\n .struct({\n id: t.integer(\n {},\n {\n asId: true,\n // auto generate ids during creation\n config: { auto: true },\n },\n ),\n name: t.string(),\n // one-to many relationship\n ideas: t.list(g.ref("idea")),\n })\n // explicitly naming our types makes reference later easier\n .rename("bucket");\n\n const idea = t\n .struct({\n id: t.uuid({ asId: true, config: { auto: true } }),\n name: t.string(),\n authorEmail: t.email(),\n // we need to specify the relationships on both types\n bucket: g.ref("bucket"),\n votes: t.list(g.ref("vote")),\n })\n .rename("idea");\n\n const vote = t\n .struct({\n id: t.uuid({ asId: true, config: { auto: true } }),\n authorEmail: t.email(),\n importance: t.enum_(["medium", "important", "critical"]).optional(),\n desc: t.string().optional(),\n idea: g.ref("idea"),\n })\n .rename("vote");\n\n // ...\n});\n'})})}),(0,a.jsx)(o.A,{value:"python",children:(0,a.jsx)(n.pre,{children:(0,a.jsx)(n.code,{className:"language-python",children:'from typegraph.providers.prisma import PrismaRuntime\n\n@typegraph()\ndef roadmap(g: Graph):\n # ..\n db = PrismaRuntime("db", "POSTGRES")\n\n bucket = t.struct(\n {\n "id": t.integer(\n as_id=True,\n # auto generate ids during creation\n config={"auto": True}\n ),\n "name": t.string(),\n # one-to many relationship\n "ideas": t.list(g.ref("idea")),\n },\n # explicitly naming our types makes reference later easier\n name="bucket"\n )\n idea = t.struct(\n {\n "id": t.uuid(as_id=True, config={"auto": True}),\n "name": t.string(),\n "authorEmail": t.email(),\n "votes": t.list(g.ref("vote")),\n "bucket": g.ref("bucket"),\n },\n name="idea"\n )\n vote = t.struct(\n {\n "id": t.uuid(as_id=True, config={"auto": True}),\n "authorEmail": t.email(),\n "importance": t.enum(["medium", "important", "critical"]).optional(),\n "desc": t.string().optional(),\n "idea": g.ref("idea"),\n },\n name="vote"\n )\n # ..\n'})})})]}),"\n",(0,a.jsxs)(n.p,{children:[(0,a.jsx)(n.code,{children:"g.ref"})," declares logical relationships between our types which the Prisma runtime will be able to pick up. If you need more control on what the relationships will look like on the database, you can use the ",(0,a.jsx)(n.code,{children:"db.link"})," function. More information can be found on the Prisma runtime ",(0,a.jsx)(n.a,{href:"/docs/reference/runtimes/prisma",children:"reference"}),"."]}),"\n",(0,a.jsxs)(n.p,{children:["When we save our file at this point, the ",(0,a.jsx)(n.code,{children:"meta dev"})," watcher should automatically create and push the necessary migrations to our database to get it in its intended shape. You should see a new subdirectory in your project called ",(0,a.jsx)(n.code,{children:"prisma"}),". It's where the generated migrations are contained."]}),"\n",(0,a.jsx)(n.p,{children:"If you mess something up in the migrations and want a clean slate, you can reset everything by recreating the containers like so:"}),"\n",(0,a.jsx)(n.pre,{children:(0,a.jsx)(n.code,{className:"language-bash",children:"# remove all containers and their volumes\ndocker compose down -v\n# launch\ndocker compose up --detach\n# meta dev will auto apply any pending changes to databases\nmeta dev\n"})}),"\n",(0,a.jsx)(n.p,{children:"At this point, we're ready to add functions to expose database queries to create or read data. The Prisma runtime allows us to run raw queries directly on the database but it also provides handy functions we can use for basic CRUD operations. We'll make use of those."}),"\n",(0,a.jsxs)(r.Ay,{children:[(0,a.jsx)(o.A,{value:"typescript",children:(0,a.jsx)(n.pre,{children:(0,a.jsx)(n.code,{className:"language-typescript",children:'import { PrismaRuntime } from "@typegraph/sdk/providers/prisma.js";\n\ntypegraph("roadmap", (g) => {\n // ...\n const pub = Policy.public();\n const db = new PrismaRuntime("db", "POSTGRES");\n // ...\n g.expose(\n {\n get_buckets: db.findMany(bucket),\n create_bucket: db.create(bucket),\n get_idea: db.findFirst(idea),\n create_ideas: db.create(idea),\n },\n pub, // make all functions public by default\n );\n});\n'})})}),(0,a.jsx)(o.A,{value:"python",children:(0,a.jsx)(n.pre,{children:(0,a.jsx)(n.code,{className:"language-python",children:'from typegraph.providers.prisma import PrismaRuntime\n\n@typegraph()\ndef roadmap(g: Graph):\n # ..\n pub = Policy.public()\n db = PrismaRuntime("db", "POSTGRES")\n # ..\n g.expose(\n pub, # make all functions public by default\n get_buckets=db.find_many(bucket),\n create_bucket=db.create(bucket),\n get_idea=db.find_many(bucket),\n create_idea=db.create(bucket),\n get_vote=db.create(vote),\n )\n\n'})})})]}),"\n",(0,a.jsx)(n.p,{children:"We should be able to add a few buckets and ideas now."}),"\n",(0,a.jsx)(s.A,{typegraph:"roadmap-prisma",python:t(37745),typescript:t(72839),query:t(1532)}),"\n",(0,a.jsx)(n.h2,{id:"policies",children:"Policies"}),"\n",(0,a.jsx)(n.p,{children:"We now have the tools enough to allow coarse CRUD of our data. The next thing we usually add at this point is authorization. A way to control who can read or write what. The primary mechanism typegraphs use for this purpose are policies."}),"\n",(0,a.jsx)(n.p,{children:"Policies are small functions that get the context of a request as input and return a boolean signaling weather access should be granted."}),"\n",(0,a.jsx)(n.p,{children:"Metatype currently supports policies based on javascript functions that are run on the Deno runtime."}),"\n",(0,a.jsxs)(n.p,{children:['For this tutorial, we\'ll be making use of the basic auth extractor. It expects a string in the format "Basic token" to be set in the ',(0,a.jsx)(n.code,{children:"Authorization"})," http header. The token is expected to be a base64 encoded string in the format ",(0,a.jsx)(n.code,{children:"username:secret"}),"."]}),"\n",(0,a.jsxs)(r.Ay,{children:[(0,a.jsx)(o.A,{value:"typescript",children:(0,a.jsx)(n.pre,{children:(0,a.jsx)(n.code,{className:"language-typescript",children:'import { DenoRuntime } from "@typegraph/sdk/runtimes/deno.js";\nimport { Auth } from "@typegraph/sdk/params.js";\n\ntypegraph("roadmap", (g) => {\n // ...\n\n const deno = new DenoRuntime();\n\n // The basic extractor only populates the context when\n // it recognizes the username and the secret matches\n g.auth(Auth.basic(["andim" /*more users*/]));\n\n // the `username` value is only availaible if the basic\n // extractor was successful\n const admins = deno.policy(\n "admins",\n `\n (_args, { context }) => !!context.username\n`,\n );\n\n g.expose(\n {\n // ..\n // only admins are allowed to create new buckets\n create_bucket: db.create(bucket).withPolicy(admins),\n // ..\n },\n pub,\n );\n\n // ...\n});\n'})})}),(0,a.jsx)(o.A,{value:"python",children:(0,a.jsx)(n.pre,{children:(0,a.jsx)(n.code,{className:"language-python",children:'from typegraph.providers.prisma import PrismaRuntime\nfrom typegraph.graph.params import Auth\n\n@typegraph()\ndef roadmap(g: Graph):\n # ..\n # The basic extractor only populates the context when\n # it recognizes the username and the secret matches\n g.auth(Auth.basic(["andim"]))\n\n deno = DenoRuntime()\n\n # the username value is only available if the basic\n # extractor was successful\n admins = deno.policy("admins", """\n (_args, { context }) => !!context.username\n""")\n\n g.expose(\n pub,\n # ..\n # only admins are allowed to create new buckets\n create_bucket=db.create(bucket).with_policy(admins),\n # ..\n )\n\n'})})})]}),"\n",(0,a.jsxs)(n.p,{children:["The basic extractors expects the secrets in environment variables named in a specific format. Add the following entries to the ",(0,a.jsx)(n.code,{children:"metatype.yaml"})," file:"]}),"\n",(0,a.jsx)(n.pre,{children:(0,a.jsx)(n.code,{className:"language-yaml",children:"typegates:\n dev:\n # ..\n secrets:\n roadmap: # your typegraph name\n # ..\n # the basic extractor secret format\n # BASIC_[username]\n BASIC_ADMIN: hunter2\n"})}),"\n",(0,a.jsxs)(n.p,{children:["When you save the files, meta-cli will reload the new additions to your typegraph. ",(0,a.jsx)(n.code,{children:"create_bucket"})," is now only accessible to requests bearing the right tokens (For the provided example, ",(0,a.jsx)(n.code,{children:"Basic YW5kaW06aHVudGVyMg=="}),' should work). If you are using the GraphiQl interface from earlier, there should be a panel in the bottom left called "Headers" for setting http headers']}),"\n",(0,a.jsx)(s.A,{typegraph:"roadmap-policies",python:t(41764),typescript:t(2386),query:t(38798)}),"\n",(0,a.jsx)(n.h2,{id:"more-customization-for-our-app",children:"More Customization for our app"}),"\n",(0,a.jsx)(n.h3,{id:"preventing-unauthorized-creation-of-related-objects",children:"Preventing Unauthorized Creation of Related Objects"}),"\n",(0,a.jsxs)(n.p,{children:[(0,a.jsx)(n.strong,{children:"Reference"}),": ",(0,a.jsx)(n.a,{href:"/docs/reference/types/parameter-transformations",children:"Parameter transformations"})]}),"\n",(0,a.jsxs)(n.p,{children:["By default, Prisma generates types that supports the whole suite of usecases one might have on a CRUD operation such as allowing creation of objects of related types in a single operation. We don't always want this and in our case, we want to prevent users from being able to create buckets, which are protected, through the ",(0,a.jsx)(n.code,{children:"create_idea"})," function which's public. We can use the ",(0,a.jsx)(n.code,{children:"reduce"})," method to modify the input types of functions."]}),"\n",(0,a.jsx)(n.pre,{children:(0,a.jsx)(n.code,{className:"language-graphql",children:'mutation CIdea {\n create_idea(\n data: {\n # we want to prevent bucket creation through `create_idea`\n bucket: { create: { name: "Backlog" } }\n authorEmail: "asdf@as.df"\n name: "Add support for WASM GC"\n }\n ) {\n id\n name\n }\n}\n'})}),"\n",(0,a.jsxs)(n.p,{children:["Even though the ",(0,a.jsx)(n.code,{children:"reduce"})," method doesn't allow us to change the shape of the type, we can change the types of members and importantly here, hide the ones we don't need."]}),"\n",(0,a.jsxs)(r.Ay,{children:[(0,a.jsx)(o.A,{value:"typescript",children:(0,a.jsx)(n.pre,{children:(0,a.jsx)(n.code,{className:"language-typescript",children:'typegraph("roadmap", (g) => {\n // ...\n g.expose(\n {\n // ..\n create_idea: db.create(idea).reduce({\n data: {\n // `g.inherit` specifies that we keep the member\n // type of the original\n name: g.inherit(),\n authorEmail: g.inherit(),\n votes: g.inherit(),\n bucket: {\n connect: g.inherit(),\n // by omitting the `create` member, we hide it\n },\n },\n }),\n // ..\n },\n pub,\n );\n});\n'})})}),(0,a.jsx)(o.A,{value:"python",children:(0,a.jsx)(n.pre,{children:(0,a.jsx)(n.code,{className:"language-python",children:'@typegraph()\ndef roadmap(g: Graph):\n # ..\n g.expose(\n pub,\n # ..\n create_idea=db.create(idea).reduce({\n "data": {\n # `g.inherit` specifies that we keep the member\n # type of the original\n "name": g.inherit(),\n "authorEmail": g.inherit(),\n "votes": g.inherit(),\n "bucket": {\n "connect": g.inherit(),\n # by omitting the `create` member, we hide it\n }\n }\n }),\n # ..\n )\n\n'})})})]}),"\n",(0,a.jsxs)(n.p,{children:["Requests are now only able to ",(0,a.jsx)(n.code,{children:"connect"})," new ideas with pre-existing buckets and won't be able to create them. If you try to ",(0,a.jsx)(n.code,{children:"create"})," new bucket through ",(0,a.jsx)(n.code,{children:"create_idea"}),", the typgate will return this response."]}),"\n",(0,a.jsx)(n.pre,{children:(0,a.jsx)(n.code,{className:"language-json",children:'{\n "errors": [\n {\n "message": "Unexpected property \'create\' for argument \'data.bucket\' of type \'object\' (\'object_288\') at create_idea; valid properties are: connect",\n "locations": [],\n "path": [],\n "extensions": {\n "timestamp": "2024-04-21T09:46:33.177Z"\n }\n }\n ]\n}\n'})}),"\n",(0,a.jsxs)(n.p,{children:["As you will be linking existing buckets when creating ideas, you need to create at least one bucket in your database. To do that you need to execute the following graphql query with admin privileges. You should add ",(0,a.jsx)(n.code,{children:'Authorization: "Basic YW5kaW06cGFzc3dvcmQ="'})," in your headers when sending the request."]}),"\n",(0,a.jsx)(n.pre,{children:(0,a.jsx)(n.code,{className:"language-graphql",children:'mutation CBucket {\n create_bucket(data: { name: "Backlog" }) {\n id\n name\n }\n}\n'})}),"\n",(0,a.jsx)(n.p,{children:"Now, If you try using this mutation, it will work as expected. You can only specify buckets that are already created."}),"\n",(0,a.jsx)(n.pre,{children:(0,a.jsx)(n.code,{className:"language-graphql",children:'mutation {\n create_idea(\n data: {\n # we want to prevent bucket creation through `create_idea`\n bucket: { connect: { id: 1 } }\n authorEmail: "asdf@as.df"\n name: "Add support for WASM GC"\n }\n ) {\n id\n name\n bucket {\n id\n name\n }\n }\n}\n'})}),"\n",(0,a.jsx)(s.A,{typegraph:"roadmap-reduce",python:t(39047),typescript:t(55385),query:t(11642),headers:{Authorization:"Basic YW5kaW06cGFzc3dvcmQ="},tab:"headers"}),"\n",(0,a.jsx)(n.h3,{id:"restrict-update-operation-on-selected-fields",children:"Restrict Update Operation on Selected Fields"}),"\n",(0,a.jsxs)(n.p,{children:["You'll notice that we had set the ",(0,a.jsx)(n.code,{children:"importance"})," field on votes as optional. This is to allow users to just up-vote an idea from the main list without opening a form. If they want to add importance or a description to their vote at a later point, we want to update their already existing vote. It should be easy to expose a function for this using Prisma's ",(0,a.jsx)(n.code,{children:"db.update"})," helper and ",(0,a.jsx)(n.code,{children:"reduce"})," to restrict changes to only those field. But we'll take this opportunity to explore the feature of the Prisma runtime to execute raw queries."]}),"\n",(0,a.jsxs)(r.Ay,{children:[(0,a.jsx)(o.A,{value:"typescript",children:(0,a.jsx)(n.pre,{children:(0,a.jsx)(n.code,{className:"language-typescript",children:'import * as effects from "@typegraph/sdk/effects.js";\n\ntypegraph("roadmap", (g) => {\n // ...\n g.expose(\n {\n // ..\n set_vote_importance: db.execute(\n // query parameters are matched by name from the input type\n \'UPDATE "vote" SET importance = ${importance} WHERE id = ${vote_id}::uuid\',\n // our input type\n t.struct({\n vote_id: t.uuid(),\n importance: t.enum_(["medium", "important", "critical"]),\n }),\n // we use effects to signal what kind of operation we\'re doing\n // updates and creates will be exposed as mutations in GraphQl\n // the boolean signals that the query is idempotent\n effects.update(true),\n ),\n // ..\n },\n pub,\n );\n});\n'})})}),(0,a.jsx)(o.A,{value:"python",children:(0,a.jsx)(n.pre,{children:(0,a.jsx)(n.code,{className:"language-python",children:'from typegraph.gen.exports.runtimes import EffectUpdate\n\n@typegraph()\ndef roadmap(g: Graph):\n # ..\n g.expose(\n pub,\n # ..\n set_vote_importance=db.execute(\n # query parameters are matched by name from the input typ\n \'UPDATE "vote" SET importance = ${importance} WHERE id = ${vote_id}::uuid\',\n # our input type\n t.struct({\n "vote_id": t.uuid(),\n "importance": t.enum(["medium", "important", "critical"]),\n }),\n # we use effects to signal what kind of operation we\'re doing\n # updates and creates will be exposed as mutations in GraphQl\n # the boolean signals that the query is idempotent\n EffectUpdate(True),\n ),\n # ..\n )\n\n'})})})]}),"\n",(0,a.jsx)(n.p,{children:"Our query is exposed like any other function in the GraphQl api."}),"\n",(0,a.jsx)(s.A,{typegraph:"roadmap-execute",python:t(49198),typescript:t(25544),query:t(85779)}),"\n",(0,a.jsx)(n.h3,{id:"creating-rest-endpoints",children:"Creating REST endpoints"}),"\n",(0,a.jsxs)(n.p,{children:["We can easily expose an HTTP API for our typegraph using the ",(0,a.jsx)(n.code,{children:"g.rest"})," method. It takes a string describe a graphql query to be executed when the http path is requested."]}),"\n",(0,a.jsxs)(r.Ay,{children:[(0,a.jsx)(o.A,{value:"typescript",children:(0,a.jsx)(n.pre,{children:(0,a.jsx)(n.code,{className:"language-typescript",children:'typegraph("roadmap", (g) => {\n // ...\n\n g.rest(\n `\n query get_buckets {\n get_buckets {\n id\n name\n ideas {\n id\n name\n authorEmail\n }\n }\n }\n `,\n );\n g.rest(\n // query parameters present\n // expects a request of the type `roadmap/rest/get_bucket?id=uuidstr`\n `\n query get_bucket($id: Integer) {\n get_bucket(where:{\n id: $id\n }) {\n id\n name\n ideas {\n id\n name\n authorEmail\n }\n }\n }\n `,\n );\n});\n'})})}),(0,a.jsx)(o.A,{value:"python",children:(0,a.jsx)(n.pre,{children:(0,a.jsx)(n.code,{className:"language-python",children:'@typegraph()\ndef roadmap(g: Graph):\n # ..\n g.rest(\n """\n query get_buckets {\n get_buckets {\n id\n name\n ideas {\n id\n name\n authorEmail\n }\n }\n }\n """\n )\n g.rest(\n # query parameters present\n # expects a request of the type `roadmap/rest/get_bucket?id=uuidstr`\n """\n query get_bucket($id: Integer) {\n get_bucket(where:{\n id: $id\n }) {\n id\n name\n ideas {\n id\n name\n authorEmail\n }\n }\n }\n """\n )\n\n'})})})]}),"\n",(0,a.jsxs)(n.p,{children:["The exposed query is served at the path ",(0,a.jsx)(n.code,{children:"{typegate_url}/{typegraph_name}/rest/{query_name}"}),". Any parameters that the query takes are processed from the search params of the request. You can check this ",(0,a.jsx)(n.a,{href:"http://localhost:7890/roadmap/rest/get_buckets",children:"link"})," on your local machine and check the results. "]}),"\n",(0,a.jsx)(n.p,{children:"This is it for this tutorial and thanks for following till the end! This was a long one but we hope it gave you an overview to the vast capabilties of Metatype. We ecourage you to keep exploring!"})]})}function m(e={}){const{wrapper:n}={...(0,i.R)(),...e.components};return n?(0,a.jsx)(n,{...e,children:(0,a.jsx)(h,{...e})}):h(e)}},65480:(e,n,t)=>{"use strict";t.d(n,{Ay:()=>o,gc:()=>s});t(30758);var a=t(3733),i=t(56315),r=t(86070);function o(e){let{children:n}=e;const[t,o]=(0,a.e)();return(0,r.jsx)(i.mS,{choices:{typescript:"Typescript SDK",python:"Python SDK"},choice:t,onChange:o,children:n})}function s(e){let{children:n}=e;const[t]=(0,a.e)();return(0,r.jsx)(i.q9,{choices:{typescript:"Typescript SDK",python:"Python SDK"},choice:t,children:n})}},65671:(e,n,t)=>{"use strict";t.d(n,{A:()=>r});var a=t(98302),i=(t(30758),t(86070));function r(e){let{python:n,typescript:t,rust:r,...o}=e;const s=[n&&{content:n.content,codeLanguage:"python",codeFileUrl:n.path},t&&{content:t.content,codeLanguage:"typescript",codeFileUrl:t.path},r&&{content:r.content,codeLanguage:"rust",codeFileUrl:r.path}].filter((e=>!!e));return(0,i.jsx)(a.A,{code:0==s.length?void 0:s,...o})}},85779:e=>{var n={kind:"Document",definitions:[{kind:"OperationDefinition",operation:"mutation",name:{kind:"Name",value:"UVote"},variableDefinitions:[],directives:[],selectionSet:{kind:"SelectionSet",selections:[{kind:"Field",name:{kind:"Name",value:"set_vote_importance"},arguments:[{kind:"Argument",name:{kind:"Name",value:"vote_id"},value:{kind:"StringValue",value:"2f3207e0-6cb6-4aaf-a759-037cdfe48f0c",block:!1}},{kind:"Argument",name:{kind:"Name",value:"importance"},value:{kind:"StringValue",value:"medium",block:!1}}],directives:[]}]}}],loc:{start:0,end:123}};n.loc.source={body:'mutation UVote {\n set_vote_importance(\n vote_id: "2f3207e0-6cb6-4aaf-a759-037cdfe48f0c"\n importance: "medium"\n )\n}\n',name:"GraphQL request",locationOffset:{line:1,column:1}};function t(e,n){if("FragmentSpread"===e.kind)n.add(e.name.value);else if("VariableDefinition"===e.kind){var 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n={kind:"Document",definitions:[{kind:"OperationDefinition",operation:"mutation",name:{kind:"Name",value:"CBucket"},variableDefinitions:[],directives:[],selectionSet:{kind:"SelectionSet",selections:[{kind:"Field",name:{kind:"Name",value:"create_bucket"},arguments:[{kind:"Argument",name:{kind:"Name",value:"data"},value:{kind:"ObjectValue",fields:[{kind:"ObjectField",name:{kind:"Name",value:"name"},value:{kind:"StringValue",value:"Backlog",block:!1}}]}}],directives:[],selectionSet:{kind:"SelectionSet",selections:[{kind:"Field",name:{kind:"Name",value:"id"},arguments:[],directives:[]},{kind:"Field",name:{kind:"Name",value:"name"},arguments:[],directives:[]}]}}]}}],loc:{start:0,end:86}};n.loc.source={body:'mutation CBucket {\n create_bucket(data: { name: "Backlog" }) {\n id\n name\n }\n}\n',name:"GraphQL request",locationOffset:{line:1,column:1}};function t(e,n){if("FragmentSpread"===e.kind)n.add(e.name.value);else if("VariableDefinition"===e.kind){var 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n={kind:"Document",definitions:[{kind:"OperationDefinition",operation:"mutation",name:{kind:"Name",value:"CBucket"},variableDefinitions:[],directives:[],selectionSet:{kind:"SelectionSet",selections:[{kind:"Field",name:{kind:"Name",value:"create_bucket"},arguments:[{kind:"Argument",name:{kind:"Name",value:"data"},value:{kind:"ObjectValue",fields:[{kind:"ObjectField",name:{kind:"Name",value:"name"},value:{kind:"StringValue",value:"Backlog",block:!1}}]}}],directives:[],selectionSet:{kind:"SelectionSet",selections:[{kind:"Field",name:{kind:"Name",value:"id"},arguments:[],directives:[]},{kind:"Field",name:{kind:"Name",value:"name"},arguments:[],directives:[]}]}}]}},{kind:"OperationDefinition",operation:"mutation",name:{kind:"Name",value:"CIdea"},variableDefinitions:[],directives:[],selectionSet:{kind:"SelectionSet",selections:[{kind:"Field",name:{kind:"Name",value:"create_idea"},arguments:[{kind:"Argument",name:{kind:"Name",value:"data"},value:{kind:"ObjectValue",fields:[{kind:"ObjectField",name:{kind:"Name",value:"bucket"},value:{kind:"ObjectValue",fields:[{kind:"ObjectField",name:{kind:"Name",value:"connect"},value:{kind:"ObjectValue",fields:[{kind:"ObjectField",name:{kind:"Name",value:"id"},value:{kind:"IntValue",value:"1"}}]}}]}},{kind:"ObjectField",name:{kind:"Name",value:"authorEmail"},value:{kind:"StringValue",value:"deng@xi.ng",block:!1}},{kind:"ObjectField",name:{kind:"Name",value:"name"},value:{kind:"StringValue",value:"Add support for WASM Gc",block:!1}}]}}],directives:[],selectionSet:{kind:"SelectionSet",selections:[{kind:"Field",name:{kind:"Name",value:"id"},arguments:[],directives:[]},{kind:"Field",name:{kind:"Name",value:"name"},arguments:[],directives:[]}]}}]}}],loc:{start:0,end:272}};n.loc.source={body:'mutation CBucket {\n create_bucket(data: { name: "Backlog" }) {\n id\n name\n }\n}\n\nmutation CIdea {\n create_idea(\n data: {\n bucket: { connect: { id: 1 } }\n authorEmail: "deng@xi.ng"\n name: "Add support for WASM Gc"\n }\n ) {\n id\n name\n }\n}\n',name:"GraphQL request",locationOffset:{line:1,column:1}};function t(e,n){if("FragmentSpread"===e.kind)n.add(e.name.value);else if("VariableDefinition"===e.kind){var a=e.type;"NamedType"===a.kind&&n.add(a.name.value)}e.selectionSet&&e.selectionSet.selections.forEach((function(e){t(e,n)})),e.variableDefinitions&&e.variableDefinitions.forEach((function(e){t(e,n)})),e.definitions&&e.definitions.forEach((function(e){t(e,n)}))}var a={};function i(e,n){for(var t=0;t0;){var d=s;s=new Set,d.forEach((function(e){o.has(e)||(o.add(e),(a[e]||new Set).forEach((function(e){s.add(e)})))}))}return o.forEach((function(n){var a=i(e,n);a&&t.definitions.push(a)})),t}n.definitions.forEach((function(e){if(e.name){var n=new Set;t(e,n),a[e.name.value]=n}})),e.exports=n,e.exports.CBucket=r(n,"CBucket"),e.exports.CIdea=r(n,"CIdea")},10374:e=>{var n={kind:"Document",definitions:[{kind:"OperationDefinition",operation:"query",variableDefinitions:[],directives:[],selectionSet:{kind:"SelectionSet",selections:[{kind:"Field",name:{kind:"Name",value:"get_message"},arguments:[],directives:[],selectionSet:{kind:"SelectionSet",selections:[{kind:"Field",name:{kind:"Name",value:"id"},arguments:[],directives:[]},{kind:"Field",name:{kind:"Name",value:"title"},arguments:[],directives:[]}]}},{kind:"Field",alias:{kind:"Name",value:"second_one"},name:{kind:"Name",value:"get_message"},arguments:[],directives:[],selectionSet:{kind:"SelectionSet",selections:[{kind:"Field",name:{kind:"Name",value:"user_id"},arguments:[],directives:[]}]}}]}}],loc:{start:0,end:106}};n.loc.source={body:"query {\n get_message {\n id\n title\n # user_id\n }\n\n second_one: get_message {\n user_id\n }\n}\n",name:"GraphQL request",locationOffset:{line:1,column:1}};function t(e,n){if("FragmentSpread"===e.kind)n.add(e.name.value);else if("VariableDefinition"===e.kind){var a=e.type;"NamedType"===a.kind&&n.add(a.name.value)}e.selectionSet&&e.selectionSet.selections.forEach((function(e){t(e,n)})),e.variableDefinitions&&e.variableDefinitions.forEach((function(e){t(e,n)})),e.definitions&&e.definitions.forEach((function(e){t(e,n)}))}var a={};n.definitions.forEach((function(e){if(e.name){var n=new Set;t(e,n),a[e.name.value]=n}})),e.exports=n},11642:e=>{var n={kind:"Document",definitions:[{kind:"OperationDefinition",operation:"mutation",name:{kind:"Name",value:"CBucket"},variableDefinitions:[],directives:[],selectionSet:{kind:"SelectionSet",selections:[{kind:"Field",name:{kind:"Name",value:"create_bucket"},arguments:[{kind:"Argument",name:{kind:"Name",value:"data"},value:{kind:"ObjectValue",fields:[{kind:"ObjectField",name:{kind:"Name",value:"name"},value:{kind:"StringValue",value:"Backlog",block:!1}}]}}],directives:[],selectionSet:{kind:"SelectionSet",selections:[{kind:"Field",name:{kind:"Name",value:"id"},arguments:[],directives:[]},{kind:"Field",name:{kind:"Name",value:"name"},arguments:[],directives:[]}]}}]}},{kind:"OperationDefinition",operation:"mutation",name:{kind:"Name",value:"CIdea"},variableDefinitions:[],directives:[],selectionSet:{kind:"SelectionSet",selections:[{kind:"Field",name:{kind:"Name",value:"create_idea"},arguments:[{kind:"Argument",name:{kind:"Name",value:"data"},value:{kind:"ObjectValue",fields:[{kind:"ObjectField",name:{kind:"Name",value:"bucket"},value:{kind:"ObjectValue",fields:[{kind:"ObjectField",name:{kind:"Name",value:"connect"},value:{kind:"ObjectValue",fields:[{kind:"ObjectField",name:{kind:"Name",value:"id"},value:{kind:"IntValue",value:"1"}}]}}]}},{kind:"ObjectField",name:{kind:"Name",value:"authorEmail"},value:{kind:"StringValue",value:"deng@xi.ng",block:!1}},{kind:"ObjectField",name:{kind:"Name",value:"name"},value:{kind:"StringValue",value:"Add support for WASM Gc",block:!1}}]}}],directives:[],selectionSet:{kind:"SelectionSet",selections:[{kind:"Field",name:{kind:"Name",value:"id"},arguments:[],directives:[]},{kind:"Field",name:{kind:"Name",value:"name"},arguments:[],directives:[]}]}}]}}],loc:{start:0,end:272}};n.loc.source={body:'mutation CBucket {\n create_bucket(data: { name: "Backlog" }) {\n id\n name\n }\n}\n\nmutation CIdea {\n create_idea(\n data: {\n bucket: { connect: { id: 1 } }\n authorEmail: "deng@xi.ng"\n name: "Add support for WASM Gc"\n }\n ) {\n id\n name\n }\n}\n',name:"GraphQL request",locationOffset:{line:1,column:1}};function t(e,n){if("FragmentSpread"===e.kind)n.add(e.name.value);else if("VariableDefinition"===e.kind){var a=e.type;"NamedType"===a.kind&&n.add(a.name.value)}e.selectionSet&&e.selectionSet.selections.forEach((function(e){t(e,n)})),e.variableDefinitions&&e.variableDefinitions.forEach((function(e){t(e,n)})),e.definitions&&e.definitions.forEach((function(e){t(e,n)}))}var a={};function i(e,n){for(var t=0;t0;){var d=s;s=new Set,d.forEach((function(e){o.has(e)||(o.add(e),(a[e]||new Set).forEach((function(e){s.add(e)})))}))}return o.forEach((function(n){var a=i(e,n);a&&t.definitions.push(a)})),t}n.definitions.forEach((function(e){if(e.name){var n=new Set;t(e,n),a[e.name.value]=n}})),e.exports=n,e.exports.CBucket=r(n,"CBucket"),e.exports.CIdea=r(n,"CIdea")},49198:e=>{e.exports={content:'from typegraph import typegraph, Policy, t, Graph\nfrom typegraph.runtimes.deno import DenoRuntime\nfrom typegraph.graph.params import Auth\nfrom typegraph.providers.prisma import PrismaRuntime\nfrom typegraph.gen.exports.runtimes import EffectUpdate\nfrom typegraph.graph.params import Cors\n\n\n@typegraph(\n)\ndef roadmap(g: Graph):\n pub = Policy.public()\n db = PrismaRuntime("db", "POSTGRES")\n deno = DenoRuntime()\n\n bucket = t.struct(\n {\n "id": t.integer(as_id=True, config={"auto": True}),\n "name": t.string(),\n "ideas": t.list(g.ref("idea")),\n },\n name="bucket",\n )\n\n idea = t.struct(\n {\n "id": t.uuid(as_id=True, config={"auto": True}),\n "name": t.string(),\n "authorEmail": t.email(),\n "votes": t.list(g.ref("vote")),\n "bucket": g.ref("bucket"),\n },\n name="idea",\n )\n\n vote = t.struct(\n {\n "id": t.uuid(as_id=True, config={"auto": True}),\n "authorEmail": t.email(),\n "importance": t.enum(["medium", "important", "critical"]).optional(),\n "desc": t.string().optional(),\n "idea": g.ref("idea"),\n },\n name="vote",\n )\n\n g.auth(Auth.basic(["andim"]))\n\n admins = deno.policy(\n "admins",\n """\n (_args, { context }) => !!context.username\n""",\n )\n\n g.expose(\n pub,\n create_bucket=db.create(bucket).with_policy(admins),\n get_buckets=db.find_many(bucket),\n get_bucket=db.find_first(bucket),\n get_idea=db.find_many(idea),\n create_idea=db.create(idea).reduce(\n {\n "data": {\n "name": g.inherit(),\n "authorEmail": g.inherit(),\n "votes": g.inherit(),\n "bucket": {"connect": g.inherit()},\n }\n }\n ),\n create_vote=db.create(vote),\n set_vote_importance=db.execute(\n \'UPDATE "vote" SET importance = ${importance} WHERE id = ${vote_id}::uuid\',\n t.struct(\n {\n "vote_id": t.uuid(),\n "importance": t.enum(["medium", "important", "critical"]),\n }\n ),\n EffectUpdate(True),\n ),\n get_context=deno.identity(t.struct({"username": t.string().optional()})).apply(\n {\n "username": g.from_context("username"),\n }\n ),\n )',path:"../examples/typegraphs/execute.py"}},25544:e=>{e.exports={content:'import { Policy, t, typegraph } from "@typegraph/sdk/index.ts";\nimport { DenoRuntime } from "@typegraph/sdk/runtimes/deno.ts";\nimport { PrismaRuntime } from "@typegraph/sdk/providers/prisma.ts";\nimport { Auth } from "@typegraph/sdk/params.ts";\nimport * as effects from "@typegraph/sdk/effects.ts";\n\nawait typegraph(\n {\n },\n (g) => {\n const pub = Policy.public();\n const db = new PrismaRuntime("db", "POSTGRES");\n const deno = new DenoRuntime();\n\n const bucket = t.struct(\n {\n id: t.integer({}, { asId: true, config: { auto: true } }),\n name: t.string(),\n ideas: t.list(g.ref("idea")),\n },\n { name: "bucket" },\n );\n\n const idea = t.struct(\n {\n id: t.uuid({ asId: true, config: { auto: true } }),\n name: t.string(),\n authorEmail: t.email(),\n votes: t.list(g.ref("vote")),\n bucket: g.ref("bucket"),\n },\n { name: "idea" },\n );\n\n const vote = t.struct(\n {\n id: t.uuid({ asId: true, config: { auto: true } }),\n authorEmail: t.email(),\n importance: t.enum_(["medium", "important", "critical"]).optional(),\n desc: t.string().optional(),\n idea: g.ref("idea"),\n },\n { name: "vote" },\n );\n\n g.auth(Auth.basic(["andim"]));\n\n const admins = deno.policy(\n "admins",\n `\n (_args, { context }) => !!context.username\n `,\n );\n\n g.expose(\n {\n create_bucket: db.create(bucket).withPolicy(admins),\n get_buckets: db.findMany(bucket),\n get_bucket: db.findFirst(bucket),\n get_idea: db.findMany(idea),\n create_idea: db.create(idea).reduce({\n data: {\n name: g.inherit(),\n authorEmail: g.inherit(),\n votes: g.inherit(),\n bucket: { connect: g.inherit() },\n },\n }),\n create_vote: db.create(vote),\n set_vote_importance: db.execute(\n \'UPDATE "vote" SET importance = ${importance} WHERE id = ${vote_id}::uuid\',\n t.struct({\n vote_id: t.uuid(),\n importance: t.enum_(["medium", "important", "critical"]),\n }),\n effects.update(true),\n ),\n get_context: deno\n .identity(t.struct({ username: t.string().optional() }))\n .apply({\n username: g.fromContext("username"),\n }),\n },\n pub,\n );\n },\n);',path:"../examples/typegraphs/execute.ts"}},84986:e=>{e.exports={content:'from typegraph import typegraph, Policy, t, Graph\nfrom typegraph.graph.params import Cors\nfrom typegraph.runtimes import RandomRuntime\n\n\n@typegraph(\n)\ndef first_typegraph(g: Graph):\n # declare runtimes and policies\n random = RandomRuntime(reset=None)\n public = Policy.public()\n\n # declare types\n message = t.struct(\n {\n "id": t.integer(),\n "title": t.string(),\n "user_id": t.integer(),\n }\n )\n\n # expose them with policies\n g.expose(\n public,\n # input \u2192 output via runtime function\n get_message=random.gen(message),\n )',path:"../examples/typegraphs/first-typegraph.py"}},24204:e=>{e.exports={content:'import { Policy, t, typegraph } from "@typegraph/sdk/index.ts";\nimport { RandomRuntime } from "@typegraph/sdk/runtimes/random.ts";\n\nawait typegraph(\n {\n name: "first-typegraph",\n },\n (g) => {\n // declare runtimes and policies\n const random = new RandomRuntime({});\n const pub = Policy.public();\n\n // declare types\n const message = t.struct({\n id: t.integer(),\n title: t.string(),\n user_id: t.integer(),\n });\n\n // expose them with policies\n g.expose(\n {\n // input \u2192 output via runtime function\n get_message: random.gen(message),\n },\n pub\n );\n }\n);',path:"../examples/typegraphs/first-typegraph.ts"}},37745:e=>{e.exports={content:'from typegraph import typegraph, Policy, t, Graph\nfrom typegraph.providers.prisma import PrismaRuntime\nfrom typegraph.graph.params import Cors\n\n\n@typegraph(\n)\ndef roadmap_py(g: Graph):\n pub = Policy.public()\n db = PrismaRuntime("db", "POSTGRES")\n\n bucket = t.struct(\n {\n "id": t.integer(config={"auto": True}).id(),\n "name": t.string(),\n "ideas": t.list(g.ref("idea")),\n },\n name="bucket",\n )\n idea = t.struct(\n {\n "id": t.uuid(config={"auto": True}).id(),\n "name": t.string(),\n "authorEmail": t.email(),\n "votes": t.list(g.ref("vote")),\n "bucket": g.ref("bucket"),\n },\n name="idea",\n )\n vote = t.struct(\n {\n "id": t.uuid(config={"auto": True}).id(),\n "authorEmail": t.email(),\n "importance": t.enum(["medium", "important", "critical"]).optional(),\n "desc": t.string().optional(),\n "idea": g.ref("idea"),\n },\n name="vote",\n )\n\n g.expose(\n pub,\n get_buckets=db.find_many(bucket),\n create_bucket=db.create(bucket),\n get_idea=db.find_many(idea),\n create_idea=db.create(idea),\n get_vote=db.create(vote),\n )',path:"../examples/typegraphs/prisma.py"}},72839:e=>{e.exports={content:'import { Policy, t, typegraph } from "@typegraph/sdk/index.ts";\nimport { PrismaRuntime } from "@typegraph/sdk/providers/prisma.ts";\n\ntypegraph(\n {\n name: "roadmap-prisma",\n },\n (g) => {\n const pub = Policy.public();\n const db = new PrismaRuntime("db", "POSTGRES");\n\n const bucket = t.struct(\n {\n id: t.integer({}, { config: { auto: true } }).id(),\n name: t.string(),\n ideas: t.list(g.ref("idea")),\n },\n { name: "bucket" },\n );\n const idea = t.struct(\n {\n id: t.uuid({ config: { auto: true } }).id(),\n name: t.string(),\n authorEmail: t.email(),\n votes: t.list(g.ref("vote")),\n bucket: g.ref("bucket"),\n },\n { name: "idea" },\n );\n const vote = t.struct(\n {\n id: t.uuid({ config: { auto: true } }).id(),\n authorEmail: t.email(),\n importance: t.enum_(["medium", "important", "critical"]).optional(),\n desc: t.string().optional(),\n idea: g.ref("idea"),\n },\n { name: "vote" },\n );\n\n g.expose(\n {\n get_buckets: db.findMany(bucket),\n create_bucket: db.create(bucket),\n get_idea: db.findMany(idea),\n create_idea: db.create(idea),\n get_vote: db.create(vote),\n },\n pub,\n );\n },\n);',path:"../examples/typegraphs/prisma.ts"}},39047:e=>{e.exports={content:'from typegraph import typegraph, Policy, t, Graph\nfrom typegraph.runtimes.deno import DenoRuntime\nfrom typegraph.graph.params import Auth\nfrom typegraph.providers.prisma import PrismaRuntime\nfrom typegraph.graph.params import Cors\n\n\n@typegraph(\n)\ndef roadmap(g: Graph):\n pub = Policy.public()\n db = PrismaRuntime("db", "POSTGRES")\n deno = DenoRuntime()\n\n bucket = t.struct(\n {\n "id": t.integer(as_id=True, config={"auto": True}),\n "name": t.string(),\n "ideas": t.list(g.ref("idea")),\n },\n name="bucket",\n )\n\n idea = t.struct(\n {\n "id": t.uuid(as_id=True, config={"auto": True}),\n "name": t.string(),\n "authorEmail": t.email(),\n "votes": t.list(g.ref("vote")),\n "bucket": g.ref("bucket"),\n },\n name="idea",\n )\n\n vote = t.struct(\n {\n "id": t.uuid(as_id=True, config={"auto": True}),\n "authorEmail": t.email(),\n "importance": t.enum(["medium", "important", "critical"]).optional(),\n "desc": t.string().optional(),\n "idea": g.ref("idea"),\n },\n name="vote",\n )\n\n g.auth(Auth.basic(["andim"]))\n\n admins = deno.policy(\n "admins",\n "(_args, { context }) => !!context.username",\n )\n\n g.expose(\n pub,\n create_bucket=db.create(bucket).with_policy(admins),\n get_buckets=db.find_many(bucket),\n get_bucket=db.find_first(bucket),\n get_idea=db.find_many(idea),\n create_idea=db.create(idea).reduce(\n {\n "data": {\n "name": g.inherit(),\n "authorEmail": g.inherit(),\n "votes": g.inherit(),\n "bucket": {"connect": g.inherit()},\n }\n }\n ),\n create_vote=db.create(vote),\n )',path:"../examples/typegraphs/reduce.py"}},55385:e=>{e.exports={content:'import { Policy, t, typegraph } from "@typegraph/sdk/index.ts";\nimport { Auth } from "@typegraph/sdk/params.ts";\nimport { PrismaRuntime } from "@typegraph/sdk/providers/prisma.ts";\nimport { DenoRuntime } from "@typegraph/sdk/runtimes/deno.ts";\n\ntypegraph(\n {\n name: "roadmap-reduce",\n },\n (g) => {\n const pub = Policy.public();\n const db = new PrismaRuntime("db", "POSTGRES");\n const deno = new DenoRuntime();\n\n const bucket = t.struct(\n {\n id: t.integer({}, { asId: true, config: { auto: true } }),\n name: t.string(),\n ideas: t.list(g.ref("idea")),\n },\n { name: "bucket" }\n );\n\n const idea = t.struct(\n {\n id: t.uuid({ asId: true, config: { auto: true } }),\n name: t.string(),\n authorEmail: t.email(),\n votes: t.list(g.ref("vote")),\n bucket: g.ref("bucket"),\n },\n { name: "idea" }\n );\n\n const vote = t.struct(\n {\n id: t.uuid({ asId: true, config: { auto: true } }),\n authorEmail: t.email(),\n importance: t.enum_(["medium", "important", "critical"]).optional(),\n desc: t.string().optional(),\n idea: g.ref("idea"),\n },\n { name: "vote" }\n );\n\n g.auth(Auth.basic(["andim"]));\n\n const admins = deno.policy(\n "admins",\n "(_args, { context }) => !!context.username"\n );\n\n g.expose(\n {\n create_bucket: db.create(bucket).withPolicy(admins),\n get_buckets: db.findMany(bucket),\n get_bucket: db.findFirst(bucket),\n get_idea: db.findMany(idea),\n create_idea: db.create(idea).reduce({\n data: {\n name: g.inherit(),\n authorEmail: g.inherit(),\n votes: g.inherit(),\n bucket: { connect: g.inherit() },\n },\n }),\n create_vote: db.create(vote),\n },\n pub\n );\n }\n);',path:"../examples/typegraphs/reduce.ts"}},41764:e=>{e.exports={content:'from typegraph import typegraph, Policy, t, Graph\nfrom typegraph.runtimes.deno import DenoRuntime\nfrom typegraph.graph.params import Auth\nfrom typegraph.providers.prisma import PrismaRuntime\nfrom typegraph.graph.params import Cors\n\n\n@typegraph(\n)\ndef roadmap(g: Graph):\n pub = Policy.public()\n db = PrismaRuntime("db", "POSTGRES")\n deno = DenoRuntime()\n\n\n # highlight-next-line\n g.auth(Auth.basic(["andim"]))\n\n # highlight-start\n admins = deno.policy(\n "admins",\n "(_args, { context }) => !!context.username",\n )\n # highlight-end\n\n g.expose(\n pub,\n # highlight-next-line\n create_bucket=db.create(bucket).with_policy(admins),\n get_buckets=db.find_many(bucket),\n get_idea=db.find_many(idea),\n create_idea=db.create(idea),\n create_vote=db.create(vote),\n )',path:"../examples/typegraphs/roadmap-policies.py"}},2386:e=>{e.exports={content:'import { Policy, t, typegraph } from "@typegraph/sdk/index.ts";\nimport { Auth } from "@typegraph/sdk/params.ts";\nimport { DenoRuntime } from "@typegraph/sdk/runtimes/deno.ts";\nimport { PrismaRuntime } from "@typegraph/sdk/providers/prisma.ts";\n\ntypegraph(\n {\n name: "roadmap-policies",\n },\n (g) => {\n const pub = Policy.public();\n const db = new PrismaRuntime("db", "POSTGRES");\n const deno = new DenoRuntime();\n\n const bucket = t.struct(\n {\n // auto generate ids during creation\n id: t.integer({}, { asId: true, config: { auto: true } }),\n name: t.string(),\n ideas: t.list(g.ref("idea")),\n },\n { name: "bucket" }\n );\n\n const idea = t.struct(\n {\n id: t.uuid({ asId: true, config: { auto: true } }),\n name: t.string(),\n authorEmail: t.email(),\n votes: t.list(g.ref("vote")),\n bucket: g.ref("bucket"),\n },\n { name: "idea" }\n );\n\n const vote = t.struct(\n {\n id: t.uuid({ asId: true, config: { auto: true } }),\n authorEmail: t.email(),\n importance: t.enum_(["medium", "important", "critical"]).optional(),\n desc: t.string().optional(),\n idea: g.ref("idea"),\n },\n { name: "vote" }\n );\n\n g.auth(Auth.basic(["andim"]));\n\n const admins = deno.policy(\n "admins",\n "(_args, { context }) => !!context.username"\n );\n\n g.expose(\n {\n create_bucket: db.create(bucket).withPolicy(admins),\n get_buckets: db.findMany(bucket),\n get_idea: db.findMany(idea),\n create_idea: db.create(idea),\n create_vote: db.create(vote),\n },\n pub\n );\n }\n);',path:"../examples/typegraphs/roadmap-policies.ts"}}}]); \ No newline at end of file diff --git a/assets/js/ad5e0346.f7dec28d.js b/assets/js/ad5e0346.f7dec28d.js deleted file mode 100644 index 641aa55bb7..0000000000 --- a/assets/js/ad5e0346.f7dec28d.js +++ /dev/null @@ -1 +0,0 @@ -(self.webpackChunkwebsite=self.webpackChunkwebsite||[]).push([[11],{14344:(e,n,t)=>{"use strict";t.d(n,{Ay:()=>s,RM:()=>r});var a=t(86070),i=t(25710);const r=[];function o(e){const n={a:"a",admonition:"admonition",code:"code",li:"li",p:"p",pre:"pre",ul:"ul",...(0,i.R)(),...e.components};return(0,a.jsxs)(a.Fragment,{children:[(0,a.jsx)(n.admonition,{type:"info",children:(0,a.jsxs)(n.p,{children:["Metatype is only supported on macOS and Linux. Windows users should use ",(0,a.jsx)(n.a,{href:"https://learn.microsoft.com/windows/wsl/install",children:"Linux on Windows with WSL"}),"."]})}),"\n",(0,a.jsxs)(n.p,{children:["You can download the binary from the\n",(0,a.jsx)(n.a,{href:"https://github.com/metatypedev/metatype/releases/",children:"releases page"}),", make it\nexecutable and add it to your ",(0,a.jsx)(n.code,{children:"PATH"})," or use the automated method below."]}),"\n",(0,a.jsxs)(n.ul,{children:["\n",(0,a.jsxs)(n.li,{children:["\n",(0,a.jsx)(n.p,{children:"An installer script is also provided for the CLI in our repository. Curl and install in it with the following one-liner. The installer may ask for your password."}),"\n",(0,a.jsx)(n.pre,{children:(0,a.jsx)(n.code,{className:"language-bash",children:"curl -fsSL https://raw.githubusercontent.com/metatypedev/metatype/main/installer.sh | bash\n"})}),"\n"]}),"\n"]}),"\n",(0,a.jsx)(n.admonition,{type:"info",children:(0,a.jsxs)(n.ul,{children:["\n",(0,a.jsxs)(n.li,{children:["\n",(0,a.jsxs)(n.p,{children:["For later use, you can run the following command to upgrade ",(0,a.jsx)(n.code,{children:"Meta CLI"})," to a newer version. If your Meta CLI is up to date, you will get an ",(0,a.jsx)(n.code,{children:"Already up to date!"})," response."]}),"\n",(0,a.jsx)(n.pre,{children:(0,a.jsx)(n.code,{className:"language-bash",children:"meta upgrade\n"})}),"\n"]}),"\n"]})}),"\n",(0,a.jsxs)(n.p,{children:["That's it! You are done installing ",(0,a.jsx)(n.code,{children:"Meta CLI"}),"."]})]})}function s(e={}){const{wrapper:n}={...(0,i.R)(),...e.components};return n?(0,a.jsx)(n,{...e,children:(0,a.jsx)(o,{...e})}):o(e)}},95459:(e,n,t)=>{"use strict";t.r(n),t.d(n,{assets:()=>u,contentTitle:()=>c,default:()=>m,frontMatter:()=>d,metadata:()=>l,toc:()=>p});var a=t(86070),i=t(25710),r=t(65480),o=t(27676),s=t(65671);t(14344),t(7871);const d={sidebar_position:3},c="Metatype Basics",l={id:"tutorials/metatype-basics/index",title:"Metatype Basics",description:"This page will walk you through a real world API with data storage and authorization.",source:"@site/docs/tutorials/metatype-basics/index.mdx",sourceDirName:"tutorials/metatype-basics",slug:"/tutorials/metatype-basics/",permalink:"/docs/tutorials/metatype-basics/",draft:!1,unlisted:!1,editUrl:"https://github.com/metatypedev/metatype/tree/main/docs/metatype.dev/docs/tutorials/metatype-basics/index.mdx",tags:[],version:"current",sidebarPosition:3,frontMatter:{sidebar_position:3},sidebar:"docs",previous:{title:"Quick-start",permalink:"/docs/tutorials/quick-start/"},next:{title:"Custom functions",permalink:"/docs/guides/external-functions/"}},u={},p=[{value:"What are you building?",id:"what-are-you-building",level:2},{value:"Setup",id:"setup",level:2},{value:"Create a new project",id:"create-a-new-project",level:3},{value:"Launch typegate",id:"launch-typegate",level:3},{value:"Make sure it's all working",id:"make-sure-its-all-working",level:3},{value:"Building our Models",id:"building-our-models",level:2},{value:"Exposing our application",id:"exposing-our-application",level:2},{value:"The Prisma Runtime",id:"the-prisma-runtime",level:3},{value:"Policies",id:"policies",level:2},{value:"More Customization for our app",id:"more-customization-for-our-app",level:2},{value:"Preventing Unauthorized Creation of Related Objects",id:"preventing-unauthorized-creation-of-related-objects",level:3},{value:"Restrict Update Operation on Selected Fields",id:"restrict-update-operation-on-selected-fields",level:3},{value:"Creating REST endpoints",id:"creating-rest-endpoints",level:3}];function h(e){const n={a:"a",admonition:"admonition",code:"code",h1:"h1",h2:"h2",h3:"h3",li:"li",p:"p",pre:"pre",strong:"strong",ul:"ul",...(0,i.R)(),...e.components};return(0,a.jsxs)(a.Fragment,{children:[(0,a.jsx)(n.h1,{id:"metatype-basics",children:"Metatype Basics"}),"\n",(0,a.jsx)(n.p,{children:(0,a.jsx)(n.strong,{children:"This page will walk you through a real world API with data storage and authorization."})}),"\n",(0,a.jsx)(n.admonition,{title:"You will learn",type:"note",children:(0,a.jsxs)(n.ul,{children:["\n",(0,a.jsx)(n.li,{children:"How to setup your development for metatype projects."}),"\n",(0,a.jsx)(n.li,{children:"How to run the typegate on the docker runtime."}),"\n",(0,a.jsx)(n.li,{children:"How to create/read/update/delete data."}),"\n",(0,a.jsx)(n.li,{children:"How to write custom business logic."}),"\n",(0,a.jsx)(n.li,{children:"How to authenticate requests."}),"\n",(0,a.jsx)(n.li,{children:"How to protect data with policies."}),"\n"]})}),"\n",(0,a.jsx)(n.h2,{id:"what-are-you-building",children:"What are you building?"}),"\n",(0,a.jsxs)(n.p,{children:["For this tutorial, we'll be implementing an API to power a simple feature roadmap/request hybrid as can be seen on ",(0,a.jsx)(n.a,{href:"https://productlane.com/roadmap",children:"Productlane"}),"."]}),"\n",(0,a.jsx)(n.p,{children:"Looking through the app we can see that the api should allow:"}),"\n",(0,a.jsxs)(n.ul,{children:["\n",(0,a.jsx)(n.li,{children:'Unauthenticated users to submit new "ideas" or vote on any of those already listed.'}),"\n",(0,a.jsx)(n.li,{children:'Specify or vote on the importance of an "idea" from "medium" to "critical" or even submit text with more description.'}),"\n",(0,a.jsx)(n.li,{children:'Admins will be able to move ideas across buckets like "Backlog", "Planned", "In Progress".'}),"\n"]}),"\n","\n",(0,a.jsx)(n.h2,{id:"setup",children:"Setup"}),"\n",(0,a.jsxs)(n.p,{children:["To setup your Metatype development environment, please follow the installation guide ",(0,a.jsx)(n.a,{href:"/docs/tutorials/quick-start#1-meta-cli",children:"here"})]}),"\n",(0,a.jsx)(n.h3,{id:"create-a-new-project",children:"Create a new project"}),"\n",(0,a.jsx)(n.p,{children:"Metatype projects are composed of modular bundles of types, logic and policies called typegraphs. We author typegraphs using modern programming languages & environments. Python and Typescript are currently available for use. The meta-cli allows us to create a new project based on pre-existing templates."}),"\n",(0,a.jsxs)(r.Ay,{children:[(0,a.jsxs)(o.A,{value:"typescript",children:[(0,a.jsxs)(n.p,{children:["Run one the following commands to create a new project under a new directory titled ",(0,a.jsx)(n.code,{children:"tg_roadmap"}),"."]}),(0,a.jsx)(n.pre,{children:(0,a.jsx)(n.code,{className:"language-bash",children:"# using Node/Bun runtimes\nmeta new --template node tg_roadmap\n# ^ project name\n# ^ Use `meta new --help` find out more available templates.\n"})}),(0,a.jsx)(n.pre,{children:(0,a.jsx)(n.code,{className:"language-bash",children:"# using Deno\nmeta new --template deno tg_roadmap\n"})}),(0,a.jsxs)(n.p,{children:["When using Typescript, the ",(0,a.jsx)(n.code,{children:"@typegraph/sdk"})," package exposes all the necessary functions and types we'll need to describe our typegraph. The templates already specify it as as a dependency so all we need to do now is run the following command to download it:"]}),(0,a.jsx)(n.pre,{children:(0,a.jsx)(n.code,{className:"language-bash",children:"# using Deno\ndeno cache api/example.ts # cache dependencies\n\n# using Bun\nbun install\n\n# using pnpm\npnpm install\n\n# using npm\nnpm install\n\n# using yarn\nyarn install\n"})})]}),(0,a.jsxs)(o.A,{value:"python",children:[(0,a.jsxs)(n.p,{children:["Run the following command to create a new project under a new directory titled ",(0,a.jsx)(n.code,{children:"tg_roadmap"}),"."]}),(0,a.jsx)(n.pre,{children:(0,a.jsx)(n.code,{className:"language-bash",children:"meta new --template python tg_roadmap\n# ^ project name\n# ^ Use `meta new --help` find out more available templates.\n"})}),(0,a.jsxs)(n.p,{children:["When using python, the ",(0,a.jsx)(n.code,{children:"typegraph"})," package exposes all the necessary functions and types we'll need to describe our typegraph. We'll need to run the following command to install it:"]}),(0,a.jsx)(n.pre,{children:(0,a.jsx)(n.code,{className:"language-bash",children:"# virtual env\npython3 -m venv .venv\n# other activate scripts should be available for non bash shells\nsource .venv/bin/activate\n\n# using pip\npip3 install typegraph\n\n# using poetry\n# the template has included `typegraph` in the poetry manifest\npoetry install\n"})})]})]}),"\n",(0,a.jsx)(n.h3,{id:"launch-typegate",children:"Launch typegate"}),"\n",(0,a.jsxs)(n.p,{children:["The typegate is a program that runs and orchestrates our typegraphs. We can run it locally for development purposes. Typegate currently requires the Redis database to function and to make it easy to run both, we'll make use of a linux container runtime for this. The Docker runtime to be specific which has installation guides located ",(0,a.jsx)(n.a,{href:"https://docs.docker.com/get-docker/",children:"here"}),"."]}),"\n",(0,a.jsxs)(n.p,{children:["We'll also need the Docker Compose orchestrator which usually comes by default with the ",(0,a.jsx)(n.code,{children:"docker"})," command. Use the following command to check if it is available:"]}),"\n",(0,a.jsx)(n.pre,{children:(0,a.jsx)(n.code,{className:"language-bash",children:"docker compose version\n# Docker Compose version 2.23.0\n"})}),"\n",(0,a.jsxs)(n.p,{children:["...and if not, the official installation guide can be found ",(0,a.jsx)(n.a,{href:"https://docs.docker.com/compose/install/",children:"here"}),"."]}),"\n",(0,a.jsxs)(n.p,{children:["If you have your docker runtime installed and running correctly, you will be able to launch the ",(0,a.jsx)(n.code,{children:"compose.yml"})," file that's bundled in every template. The compose file by default includes the ",(0,a.jsx)(n.code,{children:"postgres"})," and ",(0,a.jsx)(n.code,{children:"mongo"})," databases. You can disable the latter by commenting it out or removing it as we'll not be needing it for this tutorial."]}),"\n",(0,a.jsx)(n.p,{children:"To launch the services, navigate your shell to the project directory and run the following command:"}),"\n",(0,a.jsx)(n.pre,{children:(0,a.jsx)(n.code,{className:"language-bash",children:"docker compose up --detach\n# ^ detach means it'll run in the background.\n# Omit to get the all logs in the current terminal\n"})}),"\n",(0,a.jsx)(n.p,{children:"This should download and start typegate and its dependent services."}),"\n",(0,a.jsx)(n.p,{children:"We can observe their log of typegate or any of the other services with the following command. It has to be run from the same project directory."}),"\n",(0,a.jsx)(n.pre,{children:(0,a.jsx)(n.code,{className:"language-bash",children:"docker compose logs typegate --follow\n# ^ Omit service name to look at the combined logs of all services\n"})}),"\n",(0,a.jsx)(n.h3,{id:"make-sure-its-all-working",children:"Make sure it's all working"}),"\n",(0,a.jsx)(n.p,{children:"Run the following to make sure everything's up and running."}),"\n",(0,a.jsx)(n.pre,{children:(0,a.jsx)(n.code,{className:"language-bash",children:"meta doctor\n"})}),"\n",(0,a.jsxs)(n.p,{children:["After running the command, you should get a result similar to then one ",(0,a.jsx)(n.a,{href:"/docs/tutorials/quick-start#4-verify-your-installation",children:"here"}),"."]}),"\n",(0,a.jsx)(n.h2,{id:"building-our-models",children:"Building our Models"}),"\n",(0,a.jsxs)(n.p,{children:["We will be using the ",(0,a.jsx)(n.a,{href:"/docs/reference/types",children:"type system"}),' from the typegraph SDK to describe the shape of the data that flows through our application. In this case, we\'ll build our typegraph around types that represent "ideas", "votes" and "buckets".']}),"\n",(0,a.jsxs)(r.Ay,{children:[(0,a.jsxs)(o.A,{value:"typescript",children:[(0,a.jsxs)(n.p,{children:["Modify the file at ",(0,a.jsx)(n.code,{children:"api/example.ts"})," to look something like the following."]}),(0,a.jsx)(n.pre,{children:(0,a.jsx)(n.code,{className:"language-typescript",children:'// we\'ll need the following imports\nimport { t, typegraph } from "@typegraph/sdk.js";\n\ntypegraph("roadmap", (g) => {\n // ^ each typegraph has a name\n\n const bucket = t.struct({\n // asId and other config items describe the logical properties\n // of our types beyond just the shape\n id: t.integer({}, { asId: true }),\n name: t.string(),\n });\n const idea = t.struct({\n // uuid is just a shorthand alias for `t.string({format: "uuid"})`\n id: t.uuid({ asId: true }),\n name: t.string(),\n // another string shorthand\n authorEmail: t.email(),\n });\n const vote = t.struct({\n id: t.uuid(),\n authorEmail: t.email(),\n // `enum_` is also a shorthand over `t.string`\n importance: t.enum_(["medium", "important", "critical"]).optional(),\n // makes it optional\n desc: t.string().optional(),\n });\n});\n'})})]}),(0,a.jsxs)(o.A,{value:"python",children:[(0,a.jsxs)(n.p,{children:["Modify the file at ",(0,a.jsx)(n.code,{children:"api/example.py"})," to look something like the following."]}),(0,a.jsx)(n.pre,{children:(0,a.jsx)(n.code,{className:"language-python",children:'# we\'ll need the following imports\nfrom typegraph import typegraph, t, Graph\n\n# the typegraph will carry the name of the defining function by default\n@typegraph()\ndef roadmap(g: Graph):\n bucket = t.struct({\n # asId and other config items describe the logical properties\n # of our types beyond just the shape\n "id": t.integer(as_id=True),\n "name": t.string(),\n });\n idea = t.struct({\n # email is just a shorthand alias for `t.string({format: "uuid"})`\n "id": t.uuid(as_id=True),\n "name": t.string(),\n # another string shorthand\n "authorEmail": t.email(),\n });\n vote = t.struct({\n "id": t.uuid(),\n "authorEmail": t.email(),\n # `enum` is also a shorthand over `t.string`\n "importance": t.enum(["medium", "important", "critical"]).optional(),\n # makes it optional\n "desc": t.string().optional(),\n });\n\n'})})]})]}),"\n",(0,a.jsx)(n.p,{children:"The types here are very simple and we haven't yet added any thing that models their relationships but they should do for our purposes."}),"\n",(0,a.jsx)(n.h2,{id:"exposing-our-application",children:"Exposing our application"}),"\n",(0,a.jsx)(n.p,{children:"Typegraphs expose an API to the external world using Function objects. Functions describe the operation that transform some input type into an output type and we define them in scope of different Runtimes, where the actual logic runs. At this early stage, we can make use of the Random runtime which allows us to generate random test data for our types to get a feel of our API."}),"\n",(0,a.jsxs)(r.Ay,{children:[(0,a.jsx)(o.A,{value:"typescript",children:(0,a.jsx)(n.pre,{children:(0,a.jsx)(n.code,{className:"language-typescript",children:'// add need the following imports\nimport { Policy } from "@typegraph/sdk/index.js";\nimport { RandomRuntime } from "@typegraph/sdk/runtimes/random.js";\n\ntypegraph("roadmap", (g) => {\n // ...\n // every exposed function requires access control policies\n // for now, just use the public policy, anyone can access it\n const pub = Policy.public();\n const random = new RandomRuntime({});\n g.expose({\n // generates a random object in the shape of idea\n get_idea: random.gen(idea).withPolicy(pub),\n });\n});\n'})})}),(0,a.jsx)(o.A,{value:"python",children:(0,a.jsx)(n.pre,{children:(0,a.jsx)(n.code,{className:"language-python",children:"# add need the following imports\nfrom typegraph.runtimes.random import RandomRuntime\nfrom typegraph import Policy\n\n@typegraph() def roadmap(g: Graph): # every exposed function requires access control policies # for now, just use the public policy, anyone can access it pub = Policy.public() random = RandomRuntime() g.expose( # generates a random object in the shape of idea get_idea=random.gen(idea).with_policy(pub) )\n\n"})})})]}),"\n",(0,a.jsx)(n.p,{children:"At this point, we can push our typegraph to the locally running typegate node and access it. Run the following command in your project root:"}),"\n",(0,a.jsx)(n.pre,{children:(0,a.jsx)(n.code,{className:"language-bash",children:"# features auto-reload on any changes to your source files\nmeta dev\n"})}),"\n",(0,a.jsxs)(n.p,{children:["Typegate has first-class support for consuming the API through a GraphQl interface and it is enabled by default. It also bundles the GrahpiQl API explorer and you should be able to access it at ",(0,a.jsx)(n.a,{href:"http://localhost:7890/roadmap",children:"http://localhost:7890/roadmap"})," once meta-cli has successfully pushed your typegraph."]}),"\n",(0,a.jsxs)(n.p,{children:["You can go ahead and try out the following ",(0,a.jsx)(n.code,{children:"graphql"})," on the interface and get a feel for it."]}),"\n",(0,a.jsx)(n.pre,{children:(0,a.jsx)(n.code,{className:"language-graphql",children:"query {\n get_idea {\n id\n name\n authorEmail\n }\n}\n"})}),"\n",(0,a.jsx)(n.p,{children:"Or, you can mess around on the playground below."}),"\n",(0,a.jsx)(s.A,{typegraph:"first-typegraph",python:t(84986),typescript:t(24204),query:t(10374)}),"\n",(0,a.jsx)(n.h3,{id:"the-prisma-runtime",children:"The Prisma Runtime"}),"\n",(0,a.jsxs)(n.p,{children:["Now that we have created a simple endpoint that generates random values for our ",(0,a.jsx)(n.code,{children:"idea"})," model/type, let's add a CRUD support to our app. A runtime most apps will be depend on is the ",(0,a.jsx)(n.a,{href:"/docs/reference/runtimes/prisma",children:"Prisma Runtime"})," which allows us to connect to different databases and peform database operations."]}),"\n",(0,a.jsxs)(n.p,{children:["For this tutorial, we'll be making use of the ",(0,a.jsx)(n.code,{children:"PostgreSQL"})," database. If you made use of the ",(0,a.jsx)(n.code,{children:"compose.yml"})," to run typegate as outlined in this tutorial, there should be an instance of Postgres already up. You can check if postgres container is currently running by using the ",(0,a.jsx)(n.code,{children:"meta doctor"})," command."]}),"\n",(0,a.jsxs)(n.p,{children:["If a typegraph needs to access a database, it first needs to be made aware of its address. This is done through secrets. In the root of your project directory, you'll find a file titled ",(0,a.jsx)(n.code,{children:"metatype.yaml"}),". It contains metatype specific configuration for our project such as the top level ",(0,a.jsx)(n.code,{children:"typegates"})," object which we use to specify the location and credentials of the different typegate nodes we'll be using. Each typegate entry also takes an ",(0,a.jsx)(n.a,{href:"/docs/reference/meta-cli/configuration-file#named-secrets",children:(0,a.jsx)(n.code,{children:"secrets"})})," object where we can specify secret to be passed to our typegraphs."]}),"\n",(0,a.jsxs)(n.p,{children:["The keys in the ",(0,a.jsx)(n.code,{children:"secrets"})," object are the names of the typegraphs and the values are objects mapping secret names to their values/sources."]}),"\n",(0,a.jsxs)(n.p,{children:["The ",(0,a.jsx)(n.code,{children:"metatype.yaml"})," should already have a few sample environment variables. Add an entry like the following to give our typegraph access to the database's address:"]}),"\n",(0,a.jsx)(n.pre,{children:(0,a.jsx)(n.code,{className:"language-yaml",children:'typegates:\n dev:\n # ..\n secrets:\n TG_ROADMAP_POSTGRES: "postgresql://postgres:password@postgres:5432/db"\n'})}),"\n",(0,a.jsxs)(n.p,{children:["Meta-cli will auto-reload when it detects changes to ",(0,a.jsx)(n.code,{children:"metatype.yaml"}),". This is because Meta-cli was run in ",(0,a.jsx)(n.code,{children:"dev"})," mode(through the ",(0,a.jsx)(n.code,{children:"meta dev"})," command)."]}),"\n",(0,a.jsx)(n.p,{children:"We can add the Prisma runtime to our typegraph now."}),"\n",(0,a.jsxs)(r.Ay,{children:[(0,a.jsx)(o.A,{value:"typescript",children:(0,a.jsx)(n.pre,{children:(0,a.jsx)(n.code,{className:"language-typescript",children:'// new imports\nimport { PrismaRuntime } from "@typegraph/sdk/providers/prisma.js";\n\ntypegraph("roadmap", (g) => {\n // ...\n\n // the constructor takes the name of the env var directly\n const db = new PrismaRuntime("db", "POSTGRES");\n // ...\n});\n'})})}),(0,a.jsx)(o.A,{value:"python",children:(0,a.jsx)(n.pre,{children:(0,a.jsx)(n.code,{className:"language-python",children:'# new imports\nfrom typegraph.providers.prisma import PrismaRuntime\n\n@typegraph()\ndef roadmap(g: Graph):\n # ..\n\n # the constructor takes the name of the env var directly\n db = PrismaRuntime("db", "POSTGRES")\n # ..\n\n'})})})]}),"\n",(0,a.jsxs)(n.p,{children:["One of the features that the Prisma runtime allows us to implement is relationships. Here, we are creating a one to many relationship between bucket and ideas, also another one to many between ideas and vote. We will be specifiying relationships by using the ",(0,a.jsx)(n.code,{children:"t.list"})," List type and ",(0,a.jsx)(n.code,{children:"g.ref"}),"(method which accepts the name of the model/entity as a parameter) for creating the link. Check the example below for better understanding."]}),"\n",(0,a.jsxs)(r.Ay,{children:[(0,a.jsx)(o.A,{value:"typescript",children:(0,a.jsx)(n.pre,{children:(0,a.jsx)(n.code,{className:"language-typescript",children:'import { PrismaRuntime } from "@typegraph/sdk/providers/prisma.js";\n\ntypegraph("roadmap", (g) => {\n // ...\n\n const db = new PrismaRuntime("db", "POSTGRES");\n\n const bucket = t\n .struct({\n id: t.integer(\n {},\n {\n asId: true,\n // auto generate ids during creation\n config: { auto: true },\n },\n ),\n name: t.string(),\n // one-to many relationship\n ideas: t.list(g.ref("idea")),\n })\n // explicitly naming our types makes reference later easier\n .rename("bucket");\n\n const idea = t\n .struct({\n id: t.uuid({ asId: true, config: { auto: true } }),\n name: t.string(),\n authorEmail: t.email(),\n // we need to specify the relationships on both types\n bucket: g.ref("bucket"),\n votes: t.list(g.ref("vote")),\n })\n .rename("idea");\n\n const vote = t\n .struct({\n id: t.uuid({ asId: true, config: { auto: true } }),\n authorEmail: t.email(),\n importance: t.enum_(["medium", "important", "critical"]).optional(),\n desc: t.string().optional(),\n idea: g.ref("idea"),\n })\n .rename("vote");\n\n // ...\n});\n'})})}),(0,a.jsx)(o.A,{value:"python",children:(0,a.jsx)(n.pre,{children:(0,a.jsx)(n.code,{className:"language-python",children:'from typegraph.providers.prisma import PrismaRuntime\n\n@typegraph()\ndef roadmap(g: Graph):\n # ..\n db = PrismaRuntime("db", "POSTGRES")\n\n bucket = t.struct(\n {\n "id": t.integer(\n as_id=True,\n # auto generate ids during creation\n config={"auto": True}\n ),\n "name": t.string(),\n # one-to many relationship\n "ideas": t.list(g.ref("idea")),\n },\n # explicitly naming our types makes reference later easier\n name="bucket"\n )\n idea = t.struct(\n {\n "id": t.uuid(as_id=True, config={"auto": True}),\n "name": t.string(),\n "authorEmail": t.email(),\n "votes": t.list(g.ref("vote")),\n "bucket": g.ref("bucket"),\n },\n name="idea"\n )\n vote = t.struct(\n {\n "id": t.uuid(as_id=True, config={"auto": True}),\n "authorEmail": t.email(),\n "importance": t.enum(["medium", "important", "critical"]).optional(),\n "desc": t.string().optional(),\n "idea": g.ref("idea"),\n },\n name="vote"\n )\n # ..\n'})})})]}),"\n",(0,a.jsxs)(n.p,{children:[(0,a.jsx)(n.code,{children:"g.ref"})," declares logical relationships between our types which the Prisma runtime will be able to pick up. If you need more control on what the relationships will look like on the database, you can use the ",(0,a.jsx)(n.code,{children:"db.link"})," function. More information can be found on the Prisma runtime ",(0,a.jsx)(n.a,{href:"/docs/reference/runtimes/prisma",children:"reference"}),"."]}),"\n",(0,a.jsxs)(n.p,{children:["When we save our file at this point, the ",(0,a.jsx)(n.code,{children:"meta dev"})," watcher should automatically create and push the necessary migrations to our database to get it in its intended shape. You should see a new subdirectory in your project called ",(0,a.jsx)(n.code,{children:"prisma"}),". It's where the generated migrations are contained."]}),"\n",(0,a.jsx)(n.p,{children:"If you mess something up in the migrations and want a clean slate, you can reset everything by recreating the containers like so:"}),"\n",(0,a.jsx)(n.pre,{children:(0,a.jsx)(n.code,{className:"language-bash",children:"# remove all containers and their volumes\ndocker compose down -v\n# launch\ndocker compose up --detach\n# meta dev will auto apply any pending changes to databases\nmeta dev\n"})}),"\n",(0,a.jsx)(n.p,{children:"At this point, we're ready to add functions to expose database queries to create or read data. The Prisma runtime allows us to run raw queries directly on the database but it also provides handy functions we can use for basic CRUD operations. We'll make use of those."}),"\n",(0,a.jsxs)(r.Ay,{children:[(0,a.jsx)(o.A,{value:"typescript",children:(0,a.jsx)(n.pre,{children:(0,a.jsx)(n.code,{className:"language-typescript",children:'import { PrismaRuntime } from "@typegraph/sdk/providers/prisma.js";\n\ntypegraph("roadmap", (g) => {\n // ...\n const pub = Policy.public();\n const db = new PrismaRuntime("db", "POSTGRES");\n // ...\n g.expose(\n {\n get_buckets: db.findMany(bucket),\n create_bucket: db.create(bucket),\n get_idea: db.findFirst(idea),\n create_ideas: db.create(idea),\n },\n pub, // make all functions public by default\n );\n});\n'})})}),(0,a.jsx)(o.A,{value:"python",children:(0,a.jsx)(n.pre,{children:(0,a.jsx)(n.code,{className:"language-python",children:'from typegraph.providers.prisma import PrismaRuntime\n\n@typegraph()\ndef roadmap(g: Graph):\n # ..\n pub = Policy.public()\n db = PrismaRuntime("db", "POSTGRES")\n # ..\n g.expose(\n pub, # make all functions public by default\n get_buckets=db.find_many(bucket),\n create_bucket=db.create(bucket),\n get_idea=db.find_many(bucket),\n create_idea=db.create(bucket),\n get_vote=db.create(vote),\n )\n\n'})})})]}),"\n",(0,a.jsx)(n.p,{children:"We should be able to add a few buckets and ideas now."}),"\n",(0,a.jsx)(s.A,{typegraph:"roadmap-prisma",python:t(37745),typescript:t(72839),query:t(1532)}),"\n",(0,a.jsx)(n.h2,{id:"policies",children:"Policies"}),"\n",(0,a.jsx)(n.p,{children:"We now have the tools enough to allow coarse CRUD of our data. The next thing we usually add at this point is authorization. A way to control who can read or write what. The primary mechanism typegraphs use for this purpose are policies."}),"\n",(0,a.jsx)(n.p,{children:"Policies are small functions that get the context of a request as input and return a boolean signaling weather access should be granted."}),"\n",(0,a.jsx)(n.p,{children:"Metatype currently supports policies based on javascript functions that are run on the Deno runtime."}),"\n",(0,a.jsxs)(n.p,{children:['For this tutorial, we\'ll be making use of the basic auth extractor. It expects a string in the format "Basic token" to be set in the ',(0,a.jsx)(n.code,{children:"Authorization"})," http header. The token is expected to be a base64 encoded string in the format ",(0,a.jsx)(n.code,{children:"username:secret"}),"."]}),"\n",(0,a.jsxs)(r.Ay,{children:[(0,a.jsx)(o.A,{value:"typescript",children:(0,a.jsx)(n.pre,{children:(0,a.jsx)(n.code,{className:"language-typescript",children:'import { DenoRuntime } from "@typegraph/sdk/runtimes/deno.js";\nimport { Auth } from "@typegraph/sdk/params.js";\n\ntypegraph("roadmap", (g) => {\n // ...\n\n const deno = new DenoRuntime();\n\n // The basic extractor only populates the context when\n // it recognizes the username and the secret matches\n g.auth(Auth.basic(["andim" /*more users*/]));\n\n // the `username` value is only availaible if the basic\n // extractor was successful\n const admins = deno.policy(\n "admins",\n `\n (_args, { context }) => !!context.username\n`,\n );\n\n g.expose(\n {\n // ..\n // only admins are allowed to create new buckets\n create_bucket: db.create(bucket).withPolicy(admins),\n // ..\n },\n pub,\n );\n\n // ...\n});\n'})})}),(0,a.jsx)(o.A,{value:"python",children:(0,a.jsx)(n.pre,{children:(0,a.jsx)(n.code,{className:"language-python",children:'from typegraph.providers.prisma import PrismaRuntime\nfrom typegraph.graph.params import Auth\n\n@typegraph()\ndef roadmap(g: Graph):\n # ..\n # The basic extractor only populates the context when\n # it recognizes the username and the secret matches\n g.auth(Auth.basic(["andim"]))\n\n deno = DenoRuntime()\n\n # the username value is only available if the basic\n # extractor was successful\n admins = deno.policy("admins", """\n (_args, { context }) => !!context.username\n""")\n\n g.expose(\n pub,\n # ..\n # only admins are allowed to create new buckets\n create_bucket=db.create(bucket).with_policy(admins),\n # ..\n )\n\n'})})})]}),"\n",(0,a.jsxs)(n.p,{children:["The basic extractors expects the secrets in environment variables named in a specific format. Add the following entries to the ",(0,a.jsx)(n.code,{children:"metatype.yaml"})," file:"]}),"\n",(0,a.jsx)(n.pre,{children:(0,a.jsx)(n.code,{className:"language-yaml",children:"typegates:\n dev:\n # ..\n secrets:\n roadmap: # your typegraph name\n # ..\n # the basic extractor secret format\n # BASIC_[username]\n BASIC_ADMIN: hunter2\n"})}),"\n",(0,a.jsxs)(n.p,{children:["When you save the files, meta-cli will reload the new additions to your typegraph. ",(0,a.jsx)(n.code,{children:"create_bucket"})," is now only accessible to requests bearing the right tokens (For the provided example, ",(0,a.jsx)(n.code,{children:"Basic YW5kaW06aHVudGVyMg=="}),' should work). If you are using the GraphiQl interface from earlier, there should be a panel in the bottom left called "Headers" for setting http headers']}),"\n",(0,a.jsx)(s.A,{typegraph:"roadmap-policies",python:t(41764),typescript:t(2386),query:t(38798)}),"\n",(0,a.jsx)(n.h2,{id:"more-customization-for-our-app",children:"More Customization for our app"}),"\n",(0,a.jsx)(n.h3,{id:"preventing-unauthorized-creation-of-related-objects",children:"Preventing Unauthorized Creation of Related Objects"}),"\n",(0,a.jsxs)(n.p,{children:[(0,a.jsx)(n.strong,{children:"Reference"}),": ",(0,a.jsx)(n.a,{href:"/docs/reference/types/parameter-transformations",children:"Parameter transformations"})]}),"\n",(0,a.jsxs)(n.p,{children:["By default, Prisma generates types that supports the whole suite of usecases one might have on a CRUD operation such as allowing creation of objects of related types in a single operation. We don't always want this and in our case, we want to prevent users from being able to create buckets, which are protected, through the ",(0,a.jsx)(n.code,{children:"create_idea"})," function which's public. We can use the ",(0,a.jsx)(n.code,{children:"reduce"})," method to modify the input types of functions."]}),"\n",(0,a.jsx)(n.pre,{children:(0,a.jsx)(n.code,{className:"language-graphql",children:'mutation CIdea {\n create_idea(\n data: {\n # we want to prevent bucket creation through `create_idea`\n bucket: { create: { name: "Backlog" } }\n authorEmail: "asdf@as.df"\n name: "Add support for WASM GC"\n }\n ) {\n id\n name\n }\n}\n'})}),"\n",(0,a.jsxs)(n.p,{children:["Even though the ",(0,a.jsx)(n.code,{children:"reduce"})," method doesn't allow us to change the shape of the type, we can change the types of members and importantly here, hide the ones we don't need."]}),"\n",(0,a.jsxs)(r.Ay,{children:[(0,a.jsx)(o.A,{value:"typescript",children:(0,a.jsx)(n.pre,{children:(0,a.jsx)(n.code,{className:"language-typescript",children:'typegraph("roadmap", (g) => {\n // ...\n g.expose(\n {\n // ..\n create_idea: db.create(idea).reduce({\n data: {\n // `g.inherit` specifies that we keep the member\n // type of the original\n name: g.inherit(),\n authorEmail: g.inherit(),\n votes: g.inherit(),\n bucket: {\n connect: g.inherit(),\n // by omitting the `create` member, we hide it\n },\n },\n }),\n // ..\n },\n pub,\n );\n});\n'})})}),(0,a.jsx)(o.A,{value:"python",children:(0,a.jsx)(n.pre,{children:(0,a.jsx)(n.code,{className:"language-python",children:'@typegraph()\ndef roadmap(g: Graph):\n # ..\n g.expose(\n pub,\n # ..\n create_idea=db.create(idea).reduce({\n "data": {\n # `g.inherit` specifies that we keep the member\n # type of the original\n "name": g.inherit(),\n "authorEmail": g.inherit(),\n "votes": g.inherit(),\n "bucket": {\n "connect": g.inherit(),\n # by omitting the `create` member, we hide it\n }\n }\n }),\n # ..\n )\n\n'})})})]}),"\n",(0,a.jsxs)(n.p,{children:["Requests are now only able to ",(0,a.jsx)(n.code,{children:"connect"})," new ideas with pre-existing buckets and won't be able to create them. If you try to ",(0,a.jsx)(n.code,{children:"create"})," new bucket through ",(0,a.jsx)(n.code,{children:"create_idea"}),", the typgate will return this response."]}),"\n",(0,a.jsx)(n.pre,{children:(0,a.jsx)(n.code,{className:"language-json",children:'{\n "errors": [\n {\n "message": "Unexpected property \'create\' for argument \'data.bucket\' of type \'object\' (\'object_288\') at create_idea; valid properties are: connect",\n "locations": [],\n "path": [],\n "extensions": {\n "timestamp": "2024-04-21T09:46:33.177Z"\n }\n }\n ]\n}\n'})}),"\n",(0,a.jsxs)(n.p,{children:["As you will be linking existing buckets when creating ideas, you need to create at least one bucket in your database. To do that you need to execute the following graphql query with admin privileges. You should add ",(0,a.jsx)(n.code,{children:'Authorization: "Basic YW5kaW06cGFzc3dvcmQ="'})," in your headers when sending the request."]}),"\n",(0,a.jsx)(n.pre,{children:(0,a.jsx)(n.code,{className:"language-graphql",children:'mutation CBucket {\n create_bucket(data: { name: "Backlog" }) {\n id\n name\n }\n}\n'})}),"\n",(0,a.jsx)(n.p,{children:"Now, If you try using this mutation, it will work as expected. You can only specify buckets that are already created."}),"\n",(0,a.jsx)(n.pre,{children:(0,a.jsx)(n.code,{className:"language-graphql",children:'mutation {\n create_idea(\n data: {\n # we want to prevent bucket creation through `create_idea`\n bucket: { connect: { id: 1 } }\n authorEmail: "asdf@as.df"\n name: "Add support for WASM GC"\n }\n ) {\n id\n name\n bucket {\n id\n name\n }\n }\n}\n'})}),"\n",(0,a.jsx)(s.A,{typegraph:"roadmap-reduce",python:t(39047),typescript:t(55385),query:t(11642),headers:{Authorization:"Basic YW5kaW06cGFzc3dvcmQ="},tab:"headers"}),"\n",(0,a.jsx)(n.h3,{id:"restrict-update-operation-on-selected-fields",children:"Restrict Update Operation on Selected Fields"}),"\n",(0,a.jsxs)(n.p,{children:["You'll notice that we had set the ",(0,a.jsx)(n.code,{children:"importance"})," field on votes as optional. This is to allow users to just up-vote an idea from the main list without opening a form. If they want to add importance or a description to their vote at a later point, we want to update their already existing vote. It should be easy to expose a function for this using Prisma's ",(0,a.jsx)(n.code,{children:"db.update"})," helper and ",(0,a.jsx)(n.code,{children:"reduce"})," to restrict changes to only those field. But we'll take this opportunity to explore the feature of the Prisma runtime to execute raw queries."]}),"\n",(0,a.jsxs)(r.Ay,{children:[(0,a.jsx)(o.A,{value:"typescript",children:(0,a.jsx)(n.pre,{children:(0,a.jsx)(n.code,{className:"language-typescript",children:'import * as effects from "@typegraph/sdk/effects.js";\n\ntypegraph("roadmap", (g) => {\n // ...\n g.expose(\n {\n // ..\n set_vote_importance: db.execute(\n // query parameters are matched by name from the input type\n \'UPDATE "vote" SET importance = ${importance} WHERE id = ${vote_id}::uuid\',\n // our input type\n t.struct({\n vote_id: t.uuid(),\n importance: t.enum_(["medium", "important", "critical"]),\n }),\n // we use effects to signal what kind of operation we\'re doing\n // updates and creates will be exposed as mutations in GraphQl\n // the boolean signals that the query is idempotent\n effects.update(true),\n ),\n // ..\n },\n pub,\n );\n});\n'})})}),(0,a.jsx)(o.A,{value:"python",children:(0,a.jsx)(n.pre,{children:(0,a.jsx)(n.code,{className:"language-python",children:'from typegraph.gen.exports.runtimes import EffectUpdate\n\n@typegraph()\ndef roadmap(g: Graph):\n # ..\n g.expose(\n pub,\n # ..\n set_vote_importance=db.execute(\n # query parameters are matched by name from the input typ\n \'UPDATE "vote" SET importance = ${importance} WHERE id = ${vote_id}::uuid\',\n # our input type\n t.struct({\n "vote_id": t.uuid(),\n "importance": t.enum(["medium", "important", "critical"]),\n }),\n # we use effects to signal what kind of operation we\'re doing\n # updates and creates will be exposed as mutations in GraphQl\n # the boolean signals that the query is idempotent\n EffectUpdate(True),\n ),\n # ..\n )\n\n'})})})]}),"\n",(0,a.jsx)(n.p,{children:"Our query is exposed like any other function in the GraphQl api."}),"\n",(0,a.jsx)(s.A,{typegraph:"roadmap-execute",python:t(49198),typescript:t(25544),query:t(85779)}),"\n",(0,a.jsx)(n.h3,{id:"creating-rest-endpoints",children:"Creating REST endpoints"}),"\n",(0,a.jsxs)(n.p,{children:["We can easily expose an HTTP API for our typegraph using the ",(0,a.jsx)(n.code,{children:"g.rest"})," method. It takes a string describe a graphql query to be executed when the http path is requested."]}),"\n",(0,a.jsxs)(r.Ay,{children:[(0,a.jsx)(o.A,{value:"typescript",children:(0,a.jsx)(n.pre,{children:(0,a.jsx)(n.code,{className:"language-typescript",children:'typegraph("roadmap", (g) => {\n // ...\n\n g.rest(\n `\n query get_buckets {\n get_buckets {\n id\n name\n ideas {\n id\n name\n authorEmail\n }\n }\n }\n `,\n );\n g.rest(\n // query parameters present\n // expects a request of the type `roadmap/rest/get_bucket?id=uuidstr`\n `\n query get_bucket($id: Integer) {\n get_bucket(where:{\n id: $id\n }) {\n id\n name\n ideas {\n id\n name\n authorEmail\n }\n }\n }\n `,\n );\n});\n'})})}),(0,a.jsx)(o.A,{value:"python",children:(0,a.jsx)(n.pre,{children:(0,a.jsx)(n.code,{className:"language-python",children:'@typegraph()\ndef roadmap(g: Graph):\n # ..\n g.rest(\n """\n query get_buckets {\n get_buckets {\n id\n name\n ideas {\n id\n name\n authorEmail\n }\n }\n }\n """\n )\n g.rest(\n # query parameters present\n # expects a request of the type `roadmap/rest/get_bucket?id=uuidstr`\n """\n query get_bucket($id: Integer) {\n get_bucket(where:{\n id: $id\n }) {\n id\n name\n ideas {\n id\n name\n authorEmail\n }\n }\n }\n """\n )\n\n'})})})]}),"\n",(0,a.jsxs)(n.p,{children:["The exposed query is served at the path ",(0,a.jsx)(n.code,{children:"{typegate_url}/{typegraph_name}/rest/{query_name}"}),". Any parameters that the query takes are processed from the search params of the request. You can check this ",(0,a.jsx)(n.a,{href:"http://localhost:7890/roadmap/rest/get_buckets",children:"link"})," on your local machine and check the results. "]}),"\n",(0,a.jsx)(n.p,{children:"This is it for this tutorial and thanks for following till the end! This was a long one but we hope it gave you an overview to the vast capabilties of Metatype. We ecourage you to keep exploring!"})]})}function m(e={}){const{wrapper:n}={...(0,i.R)(),...e.components};return n?(0,a.jsx)(n,{...e,children:(0,a.jsx)(h,{...e})}):h(e)}},65480:(e,n,t)=>{"use strict";t.d(n,{Ay:()=>o,gc:()=>s});t(30758);var a=t(3733),i=t(56315),r=t(86070);function o(e){let{children:n}=e;const[t,o]=(0,a.e)();return(0,r.jsx)(i.mS,{choices:{typescript:"Typescript SDK",python:"Python SDK"},choice:t,onChange:o,children:n})}function s(e){let{children:n}=e;const[t]=(0,a.e)();return(0,r.jsx)(i.q9,{choices:{typescript:"Typescript SDK",python:"Python SDK"},choice:t,children:n})}},65671:(e,n,t)=>{"use strict";t.d(n,{A:()=>r});var a=t(98302),i=(t(30758),t(86070));function r(e){let{python:n,typescript:t,rust:r,...o}=e;const s=[n&&{content:n.content,codeLanguage:"python",codeFileUrl:n.path},t&&{content:t.content,codeLanguage:"typescript",codeFileUrl:t.path},r&&{content:r.content,codeLanguage:"rust",codeFileUrl:r.path}].filter((e=>!!e));return(0,i.jsx)(a.A,{code:0==s.length?void 0:s,...o})}},85779:e=>{var n={kind:"Document",definitions:[{kind:"OperationDefinition",operation:"mutation",name:{kind:"Name",value:"UVote"},variableDefinitions:[],directives:[],selectionSet:{kind:"SelectionSet",selections:[{kind:"Field",name:{kind:"Name",value:"set_vote_importance"},arguments:[{kind:"Argument",name:{kind:"Name",value:"vote_id"},value:{kind:"StringValue",value:"2f3207e0-6cb6-4aaf-a759-037cdfe48f0c",block:!1}},{kind:"Argument",name:{kind:"Name",value:"importance"},value:{kind:"StringValue",value:"medium",block:!1}}],directives:[]}]}}],loc:{start:0,end:123}};n.loc.source={body:'mutation UVote {\n set_vote_importance(\n vote_id: "2f3207e0-6cb6-4aaf-a759-037cdfe48f0c"\n importance: "medium"\n )\n}\n',name:"GraphQL request",locationOffset:{line:1,column:1}};function t(e,n){if("FragmentSpread"===e.kind)n.add(e.name.value);else if("VariableDefinition"===e.kind){var 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n={kind:"Document",definitions:[{kind:"OperationDefinition",operation:"mutation",name:{kind:"Name",value:"CBucket"},variableDefinitions:[],directives:[],selectionSet:{kind:"SelectionSet",selections:[{kind:"Field",name:{kind:"Name",value:"create_bucket"},arguments:[{kind:"Argument",name:{kind:"Name",value:"data"},value:{kind:"ObjectValue",fields:[{kind:"ObjectField",name:{kind:"Name",value:"name"},value:{kind:"StringValue",value:"Backlog",block:!1}}]}}],directives:[],selectionSet:{kind:"SelectionSet",selections:[{kind:"Field",name:{kind:"Name",value:"id"},arguments:[],directives:[]},{kind:"Field",name:{kind:"Name",value:"name"},arguments:[],directives:[]}]}}]}}],loc:{start:0,end:86}};n.loc.source={body:'mutation CBucket {\n create_bucket(data: { name: "Backlog" }) {\n id\n name\n }\n}\n',name:"GraphQL request",locationOffset:{line:1,column:1}};function t(e,n){if("FragmentSpread"===e.kind)n.add(e.name.value);else if("VariableDefinition"===e.kind){var 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n={kind:"Document",definitions:[{kind:"OperationDefinition",operation:"mutation",name:{kind:"Name",value:"CBucket"},variableDefinitions:[],directives:[],selectionSet:{kind:"SelectionSet",selections:[{kind:"Field",name:{kind:"Name",value:"create_bucket"},arguments:[{kind:"Argument",name:{kind:"Name",value:"data"},value:{kind:"ObjectValue",fields:[{kind:"ObjectField",name:{kind:"Name",value:"name"},value:{kind:"StringValue",value:"Backlog",block:!1}}]}}],directives:[],selectionSet:{kind:"SelectionSet",selections:[{kind:"Field",name:{kind:"Name",value:"id"},arguments:[],directives:[]},{kind:"Field",name:{kind:"Name",value:"name"},arguments:[],directives:[]}]}}]}},{kind:"OperationDefinition",operation:"mutation",name:{kind:"Name",value:"CIdea"},variableDefinitions:[],directives:[],selectionSet:{kind:"SelectionSet",selections:[{kind:"Field",name:{kind:"Name",value:"create_idea"},arguments:[{kind:"Argument",name:{kind:"Name",value:"data"},value:{kind:"ObjectValue",fields:[{kind:"ObjectField",name:{kind:"Name",value:"bucket"},value:{kind:"ObjectValue",fields:[{kind:"ObjectField",name:{kind:"Name",value:"connect"},value:{kind:"ObjectValue",fields:[{kind:"ObjectField",name:{kind:"Name",value:"id"},value:{kind:"IntValue",value:"1"}}]}}]}},{kind:"ObjectField",name:{kind:"Name",value:"authorEmail"},value:{kind:"StringValue",value:"deng@xi.ng",block:!1}},{kind:"ObjectField",name:{kind:"Name",value:"name"},value:{kind:"StringValue",value:"Add support for WASM Gc",block:!1}}]}}],directives:[],selectionSet:{kind:"SelectionSet",selections:[{kind:"Field",name:{kind:"Name",value:"id"},arguments:[],directives:[]},{kind:"Field",name:{kind:"Name",value:"name"},arguments:[],directives:[]}]}}]}}],loc:{start:0,end:272}};n.loc.source={body:'mutation CBucket {\n create_bucket(data: { name: "Backlog" }) {\n id\n name\n }\n}\n\nmutation CIdea {\n create_idea(\n data: {\n bucket: { connect: { id: 1 } }\n authorEmail: "deng@xi.ng"\n name: "Add support for WASM Gc"\n }\n ) {\n id\n name\n }\n}\n',name:"GraphQL request",locationOffset:{line:1,column:1}};function t(e,n){if("FragmentSpread"===e.kind)n.add(e.name.value);else if("VariableDefinition"===e.kind){var a=e.type;"NamedType"===a.kind&&n.add(a.name.value)}e.selectionSet&&e.selectionSet.selections.forEach((function(e){t(e,n)})),e.variableDefinitions&&e.variableDefinitions.forEach((function(e){t(e,n)})),e.definitions&&e.definitions.forEach((function(e){t(e,n)}))}var a={};function i(e,n){for(var t=0;t0;){var d=s;s=new Set,d.forEach((function(e){o.has(e)||(o.add(e),(a[e]||new Set).forEach((function(e){s.add(e)})))}))}return o.forEach((function(n){var a=i(e,n);a&&t.definitions.push(a)})),t}n.definitions.forEach((function(e){if(e.name){var n=new Set;t(e,n),a[e.name.value]=n}})),e.exports=n,e.exports.CBucket=r(n,"CBucket"),e.exports.CIdea=r(n,"CIdea")},10374:e=>{var n={kind:"Document",definitions:[{kind:"OperationDefinition",operation:"query",variableDefinitions:[],directives:[],selectionSet:{kind:"SelectionSet",selections:[{kind:"Field",name:{kind:"Name",value:"get_message"},arguments:[],directives:[],selectionSet:{kind:"SelectionSet",selections:[{kind:"Field",name:{kind:"Name",value:"id"},arguments:[],directives:[]},{kind:"Field",name:{kind:"Name",value:"title"},arguments:[],directives:[]}]}},{kind:"Field",alias:{kind:"Name",value:"second_one"},name:{kind:"Name",value:"get_message"},arguments:[],directives:[],selectionSet:{kind:"SelectionSet",selections:[{kind:"Field",name:{kind:"Name",value:"user_id"},arguments:[],directives:[]}]}}]}}],loc:{start:0,end:106}};n.loc.source={body:"query {\n get_message {\n id\n title\n # user_id\n }\n\n second_one: get_message {\n user_id\n }\n}\n",name:"GraphQL request",locationOffset:{line:1,column:1}};function t(e,n){if("FragmentSpread"===e.kind)n.add(e.name.value);else if("VariableDefinition"===e.kind){var a=e.type;"NamedType"===a.kind&&n.add(a.name.value)}e.selectionSet&&e.selectionSet.selections.forEach((function(e){t(e,n)})),e.variableDefinitions&&e.variableDefinitions.forEach((function(e){t(e,n)})),e.definitions&&e.definitions.forEach((function(e){t(e,n)}))}var a={};n.definitions.forEach((function(e){if(e.name){var n=new Set;t(e,n),a[e.name.value]=n}})),e.exports=n},11642:e=>{var n={kind:"Document",definitions:[{kind:"OperationDefinition",operation:"mutation",name:{kind:"Name",value:"CBucket"},variableDefinitions:[],directives:[],selectionSet:{kind:"SelectionSet",selections:[{kind:"Field",name:{kind:"Name",value:"create_bucket"},arguments:[{kind:"Argument",name:{kind:"Name",value:"data"},value:{kind:"ObjectValue",fields:[{kind:"ObjectField",name:{kind:"Name",value:"name"},value:{kind:"StringValue",value:"Backlog",block:!1}}]}}],directives:[],selectionSet:{kind:"SelectionSet",selections:[{kind:"Field",name:{kind:"Name",value:"id"},arguments:[],directives:[]},{kind:"Field",name:{kind:"Name",value:"name"},arguments:[],directives:[]}]}}]}},{kind:"OperationDefinition",operation:"mutation",name:{kind:"Name",value:"CIdea"},variableDefinitions:[],directives:[],selectionSet:{kind:"SelectionSet",selections:[{kind:"Field",name:{kind:"Name",value:"create_idea"},arguments:[{kind:"Argument",name:{kind:"Name",value:"data"},value:{kind:"ObjectValue",fields:[{kind:"ObjectField",name:{kind:"Name",value:"bucket"},value:{kind:"ObjectValue",fields:[{kind:"ObjectField",name:{kind:"Name",value:"connect"},value:{kind:"ObjectValue",fields:[{kind:"ObjectField",name:{kind:"Name",value:"id"},value:{kind:"IntValue",value:"1"}}]}}]}},{kind:"ObjectField",name:{kind:"Name",value:"authorEmail"},value:{kind:"StringValue",value:"deng@xi.ng",block:!1}},{kind:"ObjectField",name:{kind:"Name",value:"name"},value:{kind:"StringValue",value:"Add support for WASM Gc",block:!1}}]}}],directives:[],selectionSet:{kind:"SelectionSet",selections:[{kind:"Field",name:{kind:"Name",value:"id"},arguments:[],directives:[]},{kind:"Field",name:{kind:"Name",value:"name"},arguments:[],directives:[]}]}}]}}],loc:{start:0,end:272}};n.loc.source={body:'mutation CBucket {\n create_bucket(data: { name: "Backlog" }) {\n id\n name\n }\n}\n\nmutation CIdea {\n create_idea(\n data: {\n bucket: { connect: { id: 1 } }\n authorEmail: "deng@xi.ng"\n name: "Add support for WASM Gc"\n }\n ) {\n id\n name\n }\n}\n',name:"GraphQL request",locationOffset:{line:1,column:1}};function t(e,n){if("FragmentSpread"===e.kind)n.add(e.name.value);else if("VariableDefinition"===e.kind){var a=e.type;"NamedType"===a.kind&&n.add(a.name.value)}e.selectionSet&&e.selectionSet.selections.forEach((function(e){t(e,n)})),e.variableDefinitions&&e.variableDefinitions.forEach((function(e){t(e,n)})),e.definitions&&e.definitions.forEach((function(e){t(e,n)}))}var a={};function i(e,n){for(var t=0;t0;){var d=s;s=new Set,d.forEach((function(e){o.has(e)||(o.add(e),(a[e]||new Set).forEach((function(e){s.add(e)})))}))}return o.forEach((function(n){var a=i(e,n);a&&t.definitions.push(a)})),t}n.definitions.forEach((function(e){if(e.name){var n=new Set;t(e,n),a[e.name.value]=n}})),e.exports=n,e.exports.CBucket=r(n,"CBucket"),e.exports.CIdea=r(n,"CIdea")},49198:e=>{e.exports={content:'from typegraph import typegraph, Policy, t, Graph\nfrom typegraph.runtimes.deno import DenoRuntime\nfrom typegraph.graph.params import Auth\nfrom typegraph.providers.prisma import PrismaRuntime\nfrom typegraph.gen.exports.runtimes import EffectUpdate\nfrom typegraph.graph.params import Cors\n\n\n@typegraph(\n)\ndef roadmap(g: Graph):\n pub = Policy.public()\n db = PrismaRuntime("db", "POSTGRES")\n deno = DenoRuntime()\n\n bucket = t.struct(\n {\n "id": t.integer(as_id=True, config={"auto": True}),\n "name": t.string(),\n "ideas": t.list(g.ref("idea")),\n },\n name="bucket",\n )\n\n idea = t.struct(\n {\n "id": t.uuid(as_id=True, config={"auto": True}),\n "name": t.string(),\n "authorEmail": t.email(),\n "votes": t.list(g.ref("vote")),\n "bucket": g.ref("bucket"),\n },\n name="idea",\n )\n\n vote = t.struct(\n {\n "id": t.uuid(as_id=True, config={"auto": True}),\n "authorEmail": t.email(),\n "importance": t.enum(["medium", "important", "critical"]).optional(),\n "desc": t.string().optional(),\n "idea": g.ref("idea"),\n },\n name="vote",\n )\n\n g.auth(Auth.basic(["andim"]))\n\n admins = deno.policy(\n "admins",\n """\n (_args, { context }) => !!context.username\n""",\n )\n\n g.expose(\n pub,\n create_bucket=db.create(bucket).with_policy(admins),\n get_buckets=db.find_many(bucket),\n get_bucket=db.find_first(bucket),\n get_idea=db.find_many(idea),\n create_idea=db.create(idea).reduce(\n {\n "data": {\n "name": g.inherit(),\n "authorEmail": g.inherit(),\n "votes": g.inherit(),\n "bucket": {"connect": g.inherit()},\n }\n }\n ),\n create_vote=db.create(vote),\n set_vote_importance=db.execute(\n \'UPDATE "vote" SET importance = ${importance} WHERE id = ${vote_id}::uuid\',\n t.struct(\n {\n "vote_id": t.uuid(),\n "importance": t.enum(["medium", "important", "critical"]),\n }\n ),\n EffectUpdate(True),\n ),\n get_context=deno.identity(t.struct({"username": t.string().optional()})).apply(\n {\n "username": g.from_context("username"),\n }\n ),\n )',path:"../examples/typegraphs/execute.py"}},25544:e=>{e.exports={content:'import { Policy, t, typegraph } from "@typegraph/sdk/index.ts";\nimport { DenoRuntime } from "@typegraph/sdk/runtimes/deno.ts";\nimport { PrismaRuntime } from "@typegraph/sdk/providers/prisma.ts";\nimport { Auth } from "@typegraph/sdk/params.ts";\nimport * as effects from "@typegraph/sdk/effects.ts";\n\nawait typegraph(\n {\n },\n (g) => {\n const pub = Policy.public();\n const db = new PrismaRuntime("db", "POSTGRES");\n const deno = new DenoRuntime();\n\n const bucket = t.struct(\n {\n id: t.integer({}, { asId: true, config: { auto: true } }),\n name: t.string(),\n ideas: t.list(g.ref("idea")),\n },\n { name: "bucket" },\n );\n\n const idea = t.struct(\n {\n id: t.uuid({ asId: true, config: { auto: true } }),\n name: t.string(),\n authorEmail: t.email(),\n votes: t.list(g.ref("vote")),\n bucket: g.ref("bucket"),\n },\n { name: "idea" },\n );\n\n const vote = t.struct(\n {\n id: t.uuid({ asId: true, config: { auto: true } }),\n authorEmail: t.email(),\n importance: t.enum_(["medium", "important", "critical"]).optional(),\n desc: t.string().optional(),\n idea: g.ref("idea"),\n },\n { name: "vote" },\n );\n\n g.auth(Auth.basic(["andim"]));\n\n const admins = deno.policy(\n "admins",\n `\n (_args, { context }) => !!context.username\n `,\n );\n\n g.expose(\n {\n create_bucket: db.create(bucket).withPolicy(admins),\n get_buckets: db.findMany(bucket),\n get_bucket: db.findFirst(bucket),\n get_idea: db.findMany(idea),\n create_idea: db.create(idea).reduce({\n data: {\n name: g.inherit(),\n authorEmail: g.inherit(),\n votes: g.inherit(),\n bucket: { connect: g.inherit() },\n },\n }),\n create_vote: db.create(vote),\n set_vote_importance: db.execute(\n \'UPDATE "vote" SET importance = ${importance} WHERE id = ${vote_id}::uuid\',\n t.struct({\n vote_id: t.uuid(),\n importance: t.enum_(["medium", "important", "critical"]),\n }),\n effects.update(true),\n ),\n get_context: deno\n .identity(t.struct({ username: t.string().optional() }))\n .apply({\n username: g.fromContext("username"),\n }),\n },\n pub,\n );\n },\n);',path:"../examples/typegraphs/execute.ts"}},84986:e=>{e.exports={content:'from typegraph import typegraph, Policy, t, Graph\nfrom typegraph.graph.params import Cors\nfrom typegraph.runtimes import RandomRuntime\n\n\n@typegraph(\n)\ndef first_typegraph(g: Graph):\n # declare runtimes and policies\n random = RandomRuntime(reset=None)\n public = Policy.public()\n\n # declare types\n message = t.struct(\n {\n "id": t.integer(),\n "title": t.string(),\n "user_id": t.integer(),\n }\n )\n\n # expose them with policies\n g.expose(\n public,\n # input \u2192 output via runtime function\n get_message=random.gen(message),\n )',path:"../examples/typegraphs/first-typegraph.py"}},24204:e=>{e.exports={content:'import { Policy, t, typegraph } from "@typegraph/sdk/index.ts";\nimport { RandomRuntime } from "@typegraph/sdk/runtimes/random.ts";\n\nawait typegraph(\n {\n name: "first-typegraph",\n },\n (g) => {\n // declare runtimes and policies\n const random = new RandomRuntime({});\n const pub = Policy.public();\n\n // declare types\n const message = t.struct({\n id: t.integer(),\n title: t.string(),\n user_id: t.integer(),\n });\n\n // expose them with policies\n g.expose(\n {\n // input \u2192 output via runtime function\n get_message: random.gen(message),\n },\n pub\n );\n }\n);',path:"../examples/typegraphs/first-typegraph.ts"}},37745:e=>{e.exports={content:'from typegraph import typegraph, Policy, t, Graph\nfrom typegraph.providers.prisma import PrismaRuntime\nfrom typegraph.graph.params import Cors\n\n\n@typegraph(\n)\ndef roadmap_py(g: Graph):\n pub = Policy.public()\n db = PrismaRuntime("db", "POSTGRES")\n\n bucket = t.struct(\n {\n "id": t.integer(config={"auto": True}).id(),\n "name": t.string(),\n "ideas": t.list(g.ref("idea")),\n },\n name="bucket",\n )\n idea = t.struct(\n {\n "id": t.uuid(config={"auto": True}).id(),\n "name": t.string(),\n "authorEmail": t.email(),\n "votes": t.list(g.ref("vote")),\n "bucket": g.ref("bucket"),\n },\n name="idea",\n )\n vote = t.struct(\n {\n "id": t.uuid(config={"auto": True}).id(),\n "authorEmail": t.email(),\n "importance": t.enum(["medium", "important", "critical"]).optional(),\n "desc": t.string().optional(),\n "idea": g.ref("idea"),\n },\n name="vote",\n )\n\n g.expose(\n pub,\n get_buckets=db.find_many(bucket),\n create_bucket=db.create(bucket),\n get_idea=db.find_many(idea),\n create_idea=db.create(idea),\n get_vote=db.create(vote),\n )',path:"../examples/typegraphs/prisma.py"}},72839:e=>{e.exports={content:'import { Policy, t, typegraph } from "@typegraph/sdk/index.ts";\nimport { PrismaRuntime } from "@typegraph/sdk/providers/prisma.ts";\n\ntypegraph(\n {\n name: "roadmap-prisma",\n },\n (g) => {\n const pub = Policy.public();\n const db = new PrismaRuntime("db", "POSTGRES");\n\n const bucket = t.struct(\n {\n id: t.integer({}, { config: { auto: true } }).id(),\n name: t.string(),\n ideas: t.list(g.ref("idea")),\n },\n { name: "bucket" },\n );\n const idea = t.struct(\n {\n id: t.uuid({ config: { auto: true } }).id(),\n name: t.string(),\n authorEmail: t.email(),\n votes: t.list(g.ref("vote")),\n bucket: g.ref("bucket"),\n },\n { name: "idea" },\n );\n const vote = t.struct(\n {\n id: t.uuid({ config: { auto: true } }).id(),\n authorEmail: t.email(),\n importance: t.enum_(["medium", "important", "critical"]).optional(),\n desc: t.string().optional(),\n idea: g.ref("idea"),\n },\n { name: "vote" },\n );\n\n g.expose(\n {\n get_buckets: db.findMany(bucket),\n create_bucket: db.create(bucket),\n get_idea: db.findMany(idea),\n create_idea: db.create(idea),\n get_vote: db.create(vote),\n },\n pub,\n );\n },\n);',path:"../examples/typegraphs/prisma.ts"}},39047:e=>{e.exports={content:'from typegraph import typegraph, Policy, t, Graph\nfrom typegraph.runtimes.deno import DenoRuntime\nfrom typegraph.graph.params import Auth\nfrom typegraph.providers.prisma import PrismaRuntime\nfrom typegraph.graph.params import Cors\n\n\n@typegraph(\n)\ndef roadmap(g: Graph):\n pub = Policy.public()\n db = PrismaRuntime("db", "POSTGRES")\n deno = DenoRuntime()\n\n bucket = t.struct(\n {\n "id": t.integer(as_id=True, config={"auto": True}),\n "name": t.string(),\n "ideas": t.list(g.ref("idea")),\n },\n name="bucket",\n )\n\n idea = t.struct(\n {\n "id": t.uuid(as_id=True, config={"auto": True}),\n "name": t.string(),\n "authorEmail": t.email(),\n "votes": t.list(g.ref("vote")),\n "bucket": g.ref("bucket"),\n },\n name="idea",\n )\n\n vote = t.struct(\n {\n "id": t.uuid(as_id=True, config={"auto": True}),\n "authorEmail": t.email(),\n "importance": t.enum(["medium", "important", "critical"]).optional(),\n "desc": t.string().optional(),\n "idea": g.ref("idea"),\n },\n name="vote",\n )\n\n g.auth(Auth.basic(["andim"]))\n\n admins = deno.policy(\n "admins",\n "(_args, { context }) => !!context.username",\n )\n\n g.expose(\n pub,\n create_bucket=db.create(bucket).with_policy(admins),\n get_buckets=db.find_many(bucket),\n get_bucket=db.find_first(bucket),\n get_idea=db.find_many(idea),\n create_idea=db.create(idea).reduce(\n {\n "data": {\n "name": g.inherit(),\n "authorEmail": g.inherit(),\n "votes": g.inherit(),\n "bucket": {"connect": g.inherit()},\n }\n }\n ),\n create_vote=db.create(vote),\n )',path:"../examples/typegraphs/reduce.py"}},55385:e=>{e.exports={content:'import { Policy, t, typegraph } from "@typegraph/sdk/index.ts";\nimport { Auth } from "@typegraph/sdk/params.ts";\nimport { PrismaRuntime } from "@typegraph/sdk/providers/prisma.ts";\nimport { DenoRuntime } from "@typegraph/sdk/runtimes/deno.ts";\n\ntypegraph(\n {\n name: "roadmap-reduce",\n },\n (g) => {\n const pub = Policy.public();\n const db = new PrismaRuntime("db", "POSTGRES");\n const deno = new DenoRuntime();\n\n const bucket = t.struct(\n {\n id: t.integer({}, { asId: true, config: { auto: true } }),\n name: t.string(),\n ideas: t.list(g.ref("idea")),\n },\n { name: "bucket" }\n );\n\n const idea = t.struct(\n {\n id: t.uuid({ asId: true, config: { auto: true } }),\n name: t.string(),\n authorEmail: t.email(),\n votes: t.list(g.ref("vote")),\n bucket: g.ref("bucket"),\n },\n { name: "idea" }\n );\n\n const vote = t.struct(\n {\n id: t.uuid({ asId: true, config: { auto: true } }),\n authorEmail: t.email(),\n importance: t.enum_(["medium", "important", "critical"]).optional(),\n desc: t.string().optional(),\n idea: g.ref("idea"),\n },\n { name: "vote" }\n );\n\n g.auth(Auth.basic(["andim"]));\n\n const admins = deno.policy(\n "admins",\n "(_args, { context }) => !!context.username"\n );\n\n g.expose(\n {\n create_bucket: db.create(bucket).withPolicy(admins),\n get_buckets: db.findMany(bucket),\n get_bucket: db.findFirst(bucket),\n get_idea: db.findMany(idea),\n create_idea: db.create(idea).reduce({\n data: {\n name: g.inherit(),\n authorEmail: g.inherit(),\n votes: g.inherit(),\n bucket: { connect: g.inherit() },\n },\n }),\n create_vote: db.create(vote),\n },\n pub\n );\n }\n);',path:"../examples/typegraphs/reduce.ts"}},41764:e=>{e.exports={content:'from typegraph import typegraph, Policy, t, Graph\nfrom typegraph.runtimes.deno import DenoRuntime\nfrom typegraph.graph.params import Auth\nfrom typegraph.providers.prisma import PrismaRuntime\nfrom typegraph.graph.params import Cors\n\n\n@typegraph(\n)\ndef roadmap(g: Graph):\n pub = Policy.public()\n db = PrismaRuntime("db", "POSTGRES")\n deno = DenoRuntime()\n\n\n # highlight-next-line\n g.auth(Auth.basic(["andim"]))\n\n # highlight-start\n admins = deno.policy(\n "admins",\n "(_args, { context }) => !!context.username",\n )\n # highlight-end\n\n g.expose(\n pub,\n # highlight-next-line\n create_bucket=db.create(bucket).with_policy(admins),\n get_buckets=db.find_many(bucket),\n get_idea=db.find_many(idea),\n create_idea=db.create(idea),\n create_vote=db.create(vote),\n )',path:"../examples/typegraphs/roadmap-policies.py"}},2386:e=>{e.exports={content:'import { Policy, t, typegraph } from "@typegraph/sdk/index.ts";\nimport { Auth } from "@typegraph/sdk/params.ts";\nimport { DenoRuntime } from "@typegraph/sdk/runtimes/deno.ts";\nimport { PrismaRuntime } from "@typegraph/sdk/providers/prisma.ts";\n\ntypegraph(\n {\n name: "roadmap-policies",\n },\n (g) => {\n const pub = Policy.public();\n const db = new PrismaRuntime("db", "POSTGRES");\n const deno = new DenoRuntime();\n\n const bucket = t.struct(\n {\n // auto generate ids during creation\n id: t.integer({}, { asId: true, config: { auto: true } }),\n name: t.string(),\n ideas: t.list(g.ref("idea")),\n },\n { name: "bucket" }\n );\n\n const idea = t.struct(\n {\n id: t.uuid({ asId: true, config: { auto: true } }),\n name: t.string(),\n authorEmail: t.email(),\n votes: t.list(g.ref("vote")),\n bucket: g.ref("bucket"),\n },\n { name: "idea" }\n );\n\n const vote = t.struct(\n {\n id: t.uuid({ asId: true, config: { auto: true } }),\n authorEmail: t.email(),\n importance: t.enum_(["medium", "important", "critical"]).optional(),\n desc: t.string().optional(),\n idea: g.ref("idea"),\n },\n { name: "vote" }\n );\n\n g.auth(Auth.basic(["andim"]));\n\n const admins = deno.policy(\n "admins",\n "(_args, { context }) => !!context.username"\n );\n\n g.expose(\n {\n create_bucket: db.create(bucket).withPolicy(admins),\n get_buckets: db.findMany(bucket),\n get_idea: db.findMany(idea),\n create_idea: db.create(idea),\n create_vote: db.create(vote),\n },\n pub\n );\n }\n);',path:"../examples/typegraphs/roadmap-policies.ts"}}}]); \ No newline at end of file diff --git a/assets/js/b3219b4c.29471a66.js b/assets/js/b3219b4c.29471a66.js new file mode 100644 index 0000000000..0e78cd06d0 --- /dev/null +++ b/assets/js/b3219b4c.29471a66.js @@ -0,0 +1 @@ +"use strict";(self.webpackChunkwebsite=self.webpackChunkwebsite||[]).push([[3099],{83890:e=>{e.exports=JSON.parse('{"archive":{"blogPosts":[{"id":"/2024/08/27/distributed-execution-flow-paradigms","metadata":{"permalink":"/blog/2024/08/27/distributed-execution-flow-paradigms","editUrl":"https://github.com/metatypedev/metatype/tree/main/docs/metatype.dev/blog/2024-08-27-distributed-execution-flow-paradigms/index.mdx","source":"@site/blog/2024-08-27-distributed-execution-flow-paradigms/index.mdx","title":"Distributed execution flow paradigms","description":"In this age of cloud development and microservices architecture, problems start to arise with the increased workloads that run in the system. Imagine an e-commerce platform where a customer places an order for a product during a high-demand sale event. The order triggers a series of interconnected processes: payment processing, inventory checks, packaging, shipping, and final delivery. Each of these processes might be handled by different microservices, potentially running on different servers or even in different data centers. What happens if the payment service goes down right after the payment is authorized but before the inventory is updated? Or if the packaging service fails just after the inventory is deducted but before the item is packed? Without a robust mechanism to ensure that each step in the workflow completes successfully and that failures are properly handled, you could end up with unhappy customers, lost orders, and inventory discrepancies.","date":"2024-08-27T00:00:00.000Z","tags":[],"readingTime":10.92,"hasTruncateMarker":false,"authors":[],"frontMatter":{},"unlisted":false,"nextItem":{"title":"Python on WebAssembly: How?","permalink":"/blog/2024/08/26/python-on-webassembly"}},"content":"import TabItem from \\"@theme/TabItem\\";\\nimport SDKTabs from \\"@site/src/components/SDKTabs\\";\\n\\n\\nIn this age of cloud development and microservices architecture, problems start to arise with the increased workloads that run in the system. Imagine an e-commerce platform where a customer places an order for a product during a high-demand sale event. The order triggers a series of interconnected processes: payment processing, inventory checks, packaging, shipping, and final delivery. Each of these processes might be handled by different microservices, potentially running on different servers or even in different data centers. What happens if the payment service goes down right after the payment is authorized but before the inventory is updated? Or if the packaging service fails just after the inventory is deducted but before the item is packed? Without a robust mechanism to ensure that each step in the workflow completes successfully and that failures are properly handled, you could end up with unhappy customers, lost orders, and inventory discrepancies.\\n\\nHaving multiple components in your system introduces more failure points, which is a common phenomenon in complex systems. But one important behavior any application must ensure is that the execution flow reaches its completion. As systems grow in features and complexity, the likelihood of long-running processes increases. To ensure these processes complete as intended, several solutions have been introduced over the last few decades.\\nLet\'s explore some of the solutions that have been proposed to achieve workflow completeness.\\n\\n### 1. Event-Driven Architecture with Message Queues\\n\\nThis architecture relies heavily on services communicating by publishing and subscribing to events using message queues. Message queues are persistent storages that ensure data is not lost during failures or service unavailability. Components in a distributed system synchronize by using events/messages through these independent services. While this approach offers service decomposability and fault tolerance, it has some shortcomings. For example, using message queues comes with the overhead of managing messages (e.g., deduplication and message ordering). It also isn\u2019t ideal for systems requiring immediate consistency across components. Some technologies and patterns that utilize this architecture include:\\n\\n- [RabbitMQ](https://www.rabbitmq.com/)\\n- [Amazon SQS](https://aws.amazon.com/sqs/)\\n\\n![](eda.drawio.svg)\\n\\n
\\n Fig. Event Driven Architecture with Message Queues - RabbitMQ\\n
\\n\\n#### Advantages\\n\\n- Improved Scalability\\n- Enhanced Responsiveness\\n- Enhanced Fault Tolerance\\n- Simplified Complex Workflows\\n- Real-Time Data Processing\\n\\n#### Challenges\\n\\n- Event Ordering\\n- Data Consistency\\n- Monitoring and Debugging\\n- Event Deduplication\\n\\nYou can mitigate or reduce these challenges by following best practices like Event Sourcing, Idempotent Processing, CQRS (Command Query Responsibility Segregation), and Event Versioning.\\n\\n### 2. The [Saga Pattern](https://microservices.io/patterns/data/saga.html)\\n\\nThis design pattern aims to achieve consistency across different services in a distributed system by breaking complex transactions spanning multiple components into a series of local transactions. Each of these transactions triggers an event or message that starts the next transaction in the sequence. If any local transaction fails to complete, a series of compensating actions roll back the effects of preceding transactions. While the orchestration of local transactions can vary, the pattern aims to achieve consistency in a microservices-based system. Events are designed to be stored in durable storage systems or logs, providing a trail to reconstruct the system to a state after a failure. While the saga pattern is an effective way to ensure consistency, it can be challenging to implement timer/timeout-based workflows and to design and implement the compensating actions for local transactions.\\n\\n**Note**: In the Saga pattern, a compensating transaction must be idempotent and retryable. These principles ensure that transactions can be managed without manual intervention.\\n\\n![](saga.drawio.svg)\\n\\n
\\n Fig. The Saga Pattern for Order delivery system\\n
\\n\\n#### Advantages\\n\\n- Ensures data consistency in a distributed system without tight coupling.\\n- Provides Roll back if one of the operations in the sequence fails.\\n\\n#### Drawbacks\\n\\n- Might be challenging to implement initially.\\n- Hard to debug.\\n- Compensating transactions don\u2019t always work.\\n\\n### 3. [Stateful Orchestrators](https://docs.oracle.com/en/applications/jd-edwards/cross-product/9.2/eotos/creating-a-stateful-orchestration-release-9-2-8-3.html#u30249073)\\n\\nStateful orchestrators provide a solution for long-running workflows by maintaining the state of each step in a workflow. Each step in a workflow represents a task, and these tasks are represented as states inside workflows. Workflows are defined as state machines or directed acyclic graphs (DAGs). In this approach, an orchestrator handles task execution order, transitioning, handling retries, and maintaining state. In the event of a failure, the system can recover from the persisted state. Stateful orchestrators offer significant value in fault tolerance, consistency, and observability. It\u2019s one of the solutions proven effective in modern distributed computing. Some well-known services that provide this solution include:\\n\\n- [Apache Airflow](https://airflow.apache.org/docs/apache-airflow/stable/core-concepts/overview.html)\\n- [Azure Logic Apps](https://azure.microsoft.com/en-us/products/logic-apps)\\n\\n#### Advantages\\n\\n- **High Resiliency**: Stateful orchestrators provide high resiliency in case of outages, ensuring that workflows can continue from where they left off.\\n- **Data Persistence**: They allow you to keep, review, or reference data from previous events, which is useful for long-running processes.\\n- **Extended Runtime**: Stateful workflows can continue running for much longer than stateless workflows, making them suitable for complex and long-running tasks.\\n\\n#### Challenges\\n\\n- **Additional Complexity**: They introduce additional complexity, requiring you to manage issues such as load balancing, CPU and memory usage, and networking.\\n- **Cost**: With stateful workflows, you pay for the VMs that are running in the cluster, whereas with stateless workflows, you pay only for the actual compute resources consumed.\\n\\n### 4. Durable Execution\\n\\nDurable execution refers to the ability of a system to preserve the state of an application and persist execution despite failures or interruptions. Durable execution ensures that for every task, its inputs, outputs, call stack, and local variables are persisted. These constraints, or rather features, allow a system to automatically retry or continue running in the face of infrastructure or system failures, ultimately ensuring completion.\\n\\nDurable execution isn\u2019t a completely distinct solution from the ones listed above but rather incorporates some of their strengths while presenting a more comprehensive approach to achieving consistency, fault tolerance, data integrity, resilience for long-running processes, and observability.\\n\\n\\n
Fig. Durable workflow engine
\\n\\n#### Advantages\\n\\n- **Reduced Manual Intervention**: Minimizes the need for human intervention by handling retries and failures programmatically.\\n- **Improved Observability**: Provides a clear audit trail and visibility into the state of workflows, which aids in debugging and monitoring.\\n- **Scalability**: Scales efficiently across distributed systems while maintaining workflow integrity.\\n\\n#### Challenges\\n\\n- **Resource Intensive**: Persistent state storage and management can consume significant resources, especially in large-scale systems.\\n- **Latency**: The need to persist state and handle retries can introduce latency in the execution flow.\\n\\nAs durable execution grows to be a fundamental driver of distributed computing, some of the solutions which use this architecture are\\n\\n- [Temporal](https://temporal.io/)\\n- [Uber Cadence](https://cadenceworkflow.io/)\\n\\nAmong these, [Temporal](https://temporal.io/) has grown in influence, used by companies like SnapChat, HashiCorp, Stripe, DoorDash, and DataDog. Its success is driven by its practical application in real-world scenarios and the expertise of its founders.\\n\\nAt Metatype, we recognize the value of durable execution and are committed to making it accessible. Our [Temporal Runtime](/docs/reference/runtimes/temporal) integrates seamlessly into our declarative API development platform, enabling users to harness the power of Temporal directly within Metatype. For those interested in exploring further, our documentation provides a detailed guide on getting started with [Temporal Runtime](/docs/reference/runtimes/temporal).\\n\\nBelow is an example of how you can build a simple API to interact with an order delivery temporal workflow within Metatype.\\n\\n:::note\\nIf you are new to Metatype or haven\u2019t set it up yet in your development environment. You can follow this [guideline](/docs/tutorials/quick-start).\\n:::\\n\\nFor this example, the order delivery system will have few components/services such as Payment, Inventory and Delivery.\\n\\nYour temporal workflow definition should look similar to the one below.\\n\\n\\n\\n \\n\\n
\\n\\nActivities definition inside `src/activities.ts`:`\\n\\n```typescript\\nasync function sleep(time: number) {\\n return new Promise((resolve) => {\\n setTimeout(resolve, time);\\n });\\n}\\n\\nexport async function processPayment(orderId: string): Promise {\\n console.log(`Processing payment for order ${orderId}`);\\n // Simulate payment processing logic\\n await sleep(2);\\n return \\"Payment processed\\";\\n}\\n\\nexport async function checkInventory(orderId: string): Promise {\\n console.log(`Checking inventory for order ${orderId}`);\\n // Simulate inventory check logic\\n await sleep(2);\\n return \\"Inventory available\\";\\n}\\n\\nexport async function deliverOrder(orderId: string): Promise {\\n console.log(`Delivering order ${orderId}`);\\n // Simulate delivery logic\\n await sleep(5);\\n return \\"Order delivered\\";\\n}\\n```\\n\\n
\\n\\n
\\n\\nWorkflow definition inside `src/workflows.ts`:\\n```typescript import {proxyActivities} from \\"@temporalio/workflow\\";\\n\\nexport const { processPayment, checkInventory, deliverOrder } =\\n proxyActivities<{\\n processPayment(orderId: string): Promise;\\n checkInventory(orderId: string): Promise;\\n deliverOrder(orderId: string): Promise;\\n }>({\\n startToCloseTimeout: \\"10 seconds\\",\\n });\\n\\nexport async function OrderWorkflow(orderId: string): Promise {\\n const paymentResult = await processPayment(orderId);\\n const inventoryResult = await checkInventory(orderId);\\n const deliveryResult = await deliverOrder(orderId);\\n return `Order ${orderId} completed with results: ${paymentResult}, ${inventoryResult}, ${deliveryResult}`;\\n}\\n```\\n
\\n\\n
\\nWorker definintion inside `src/worker.ts`:\\n\\n```typescript\\nimport { NativeConnection, Worker } from \\"@temporalio/worker\\";\\nimport * as activities from \\"./activities\\";\\nimport { TASK_QUEUE_NAME } from \\"./shared\\";\\n\\nasync function run() {\\n const connection = await NativeConnection.connect({\\n address: \\"localhost:7233\\",\\n });\\n\\n const worker = await Worker.create({\\n connection,\\n namespace: \\"default\\",\\n taskQueue: TASK_QUEUE_NAME,\\n workflowsPath: require.resolve(\\"./workflows\\"),\\n activities,\\n });\\n\\n await worker.run();\\n}\\n\\nrun().catch((err) => {\\n console.error(err);\\n process.exit(1);\\n});\\n```\\n\\n
\\n\\nAfter you have setup the above components, now you need a client to start of any `OrderWorkflow`. Here is where metatype comes in, through the simple APIs [Temporal Runtime](/docs/reference/runtimes/temporal) exposes, you can communicate with your temporal cluster.\\nDown below is the workflow communication bridge for this system expressed within a [typegraph](/docs/reference/typegraph) which includes endpoints to start a new workflow and describe an existing one.\\n\\n```typescript\\nimport { Policy, t, typegraph } from \\"@typegraph/sdk/index.ts\\";\\nimport { TemporalRuntime } from \\"@typegraph/sdk/providers/temporal.ts\\";\\n\\ntypegraph(\\n {\\n name: \\"order_delivery\\",\\n },\\n (g: any) => {\\n const pub = Policy.public();\\n\\n const temporal = new TemporalRuntime({\\n name: \\"order_delivery\\",\\n hostSecret: \\"HOST\\",\\n namespaceSecret: \\"NAMESPACE\\",\\n });\\n\\n const workflow_id = \\"order-delivery-1\\";\\n\\n const order_id = t.string();\\n\\n g.expose(\\n {\\n start: temporal.startWorkflow(\\"OrderWorkflow\\", order_id),\\n describe: workflow_id\\n ? temporal.describeWorkflow().reduce({ workflow_id })\\n : temporal.describeWorkflow(),\\n },\\n pub,\\n );\\n },\\n);\\n```\\n\\n \\n\\n {/* break */}\\n \\n\\n
\\nActivities definition inside `activities.py`.\\n\\n```python\\nfrom temporalio import activity\\nimport time\\n\\n@activity.defn\\nasync def process_payment(order_id: str) -> str:\\n print(f\\"Processing payment for order {order_id}\\")\\n # Simulate payment processing logic\\n time.sleep(5)\\n return \\"Payment processed\\"\\n\\n@activity.defn\\nasync def check_inventory(order_id: str) -> str:\\n print(f\\"Checking inventory for order {order_id}\\")\\n # Simulate inventory check logic\\n time.sleep(4)\\n return \\"Inventory available\\"\\n\\n@activity.defn\\nasync def deliver_order(order_id: str) -> str:\\n print(f\\"Delivering order {order_id}\\")\\n time.sleep(8)\\n # Simulate delivery logic\\n return \\"Order delivered\\"\\n```\\n\\n
\\n\\n
\\nWorker defintion inside `run_worker.py`.\\n\\n```python\\nimport asyncio\\n\\nfrom temporalio.client import Client\\nfrom temporalio.worker import Worker\\n\\nfrom activities import process_payment, deliver_order, check_inventory\\nfrom shared import ORDER_DELIVERY_QUEUE\\nfrom workflows import OrderWorkflow\\n\\n\\nasync def main() -> None:\\n client: Client = await Client.connect(\\"localhost:7233\\", namespace=\\"default\\")\\n worker: Worker = Worker(\\n client,\\n task_queue=ORDER_DELIVERY_QUEUE,\\n workflows=[OrderWorkflow],\\n activities=[process_payment, check_inventory, deliver_order],\\n )\\n await worker.run()\\n\\n\\nif __name__ == \\"__main__\\":\\n asyncio.run(main())\\n```\\n\\n
\\n\\nAfter you have setup the above components, now you need a client to start of any `OrderWorkflow`. Here is where metatype comes in, through the simple APIs [Temporal Runtime](/docs/reference/runtimes/temporal) exposes, you can communicate with your temporal cluster.\\nDown below is the workflow communication bridge for this system expressed within a [typegraph](/docs/reference/typegraph) which includes endpoints to start a new workflow and describe an existing one.\\n\\n```python\\nfrom typegraph import t, typegraph, Policy, Graph\\nfrom typegraph.providers.temporal import TemporalRuntime\\n\\n\\n@typegraph()\\ndef example(g: Graph):\\n public = Policy.public()\\n\\n temporal = TemporalRuntime(\\n \\"example\\", \\"HOST\\", namespace_secret=\\"NAMESPACE\\"\\n )\\n\\n workflow_id = \\"order-delivery-1\\"\\n\\n order_id = t.string()\\n\\n g.expose(\\n public,\\n start=temporal.start_workflow(\\"OrderWorkflow\\", order_id),\\n describe=temporal.describe_workflow().reduce({\\"workflow_id\\": workflow_id})\\n if workflow_id\\n else temporal.describe_workflow(),\\n )\\n```\\n\\n \\n\\n\\n\\nYou need to add the secrets `HOST` and `NAMESPACE` under your typegraph name inside the `metatype.yaml` file. These secrets are important to connect with your temporal cluster and can be safely stored in the config file as shown below.\\n\\n
\\nmetatype.yaml\\n\\n```yaml\\ntypegate:\\n dev:\\n url: \\"http://localhost:7890\\"\\n username: admin\\n password: password\\n secrets:\\n example:\\n POSTGRES: \\"postgresql://postgres:password@postgres:5432/db\\"\\n HOST: \\"http://localhost:7233\\"\\n NAMESPACE: \\"default\\"\\n```\\n\\n
\\n\\nYou need to add only the last two lines as the others are auto-generated. Note that secrets are defined under the `example` parent, which is the name of your typegraph. If the name doesn\'t match, you will face secret not found issues when deploying your typegraph.\\n\\nBefore deploying the above typegraph, you need to start the temporal server and the worker. You need to have [temporal](https://learn.temporal.io/getting_started/typescript/dev_environment/#set-up-a-local-temporal-service-for-development-with-temporal-cli) installed on your machine.\\n\\n
\\nBoot up temporal\\n\\nStart the temporal server.\\n\\n```bash\\ntemporal server start-dev\\n```\\n\\nStart the worker.\\n\\n\\n\\n\\n ```typescript npx ts-node src/worker.ts ```\\n\\n\\n```python python run_worker.py ```\\n\\n\\n
\\n\\nAfter booting the temporal server, run the command down below to get a locally spinning [typegate](/docs/reference/typegate) instance with your typegraph deployed.\\n\\n```bash\\nmeta dev\\n```\\n\\nAfter completing the above steps, you can access the web GraphQL client of the typegate at [`http://localhost:7890/example`](http://localhost:7890/example). Run this query inside the client to start your workflow.\\n\\n```graphql\\nmutation {\\n start(\\n workflow_id: \\"order-delivery-3\\"\\n task_queue: \\"order-delivery-queue\\"\\n args: [\\"order12\\"]\\n )\\n}\\n```\\n\\nAfter a successful run, you will get the following result which includes the `run_id` of the workflow which has just been started.\\n\\n\\n\\nYou can also check the temporal web UI to monitor your workflows and you should see a result similar to this one.\\n\\n\\n\\nYou can explore the [Temporal Runtime](/docs/reference/runtimes/temporal) for more info.\\n\\nThis wraps up the blog, thanks for reading until the end :)"},{"id":"/2024/08/26/python-on-webassembly","metadata":{"permalink":"/blog/2024/08/26/python-on-webassembly","editUrl":"https://github.com/metatypedev/metatype/tree/main/docs/metatype.dev/blog/2024-08-26-python-on-webassembly/index.mdx","source":"@site/blog/2024-08-26-python-on-webassembly/index.mdx","title":"Python on WebAssembly: How?","description":"Metatype\'s different language runtimes are nice, but integrating one is an entire story. Let\'s discover how we managed to implement one for Python.","date":"2024-08-26T00:00:00.000Z","tags":[],"readingTime":11.125,"hasTruncateMarker":false,"authors":[],"frontMatter":{},"unlisted":false,"prevItem":{"title":"Distributed execution flow paradigms","permalink":"/blog/2024/08/27/distributed-execution-flow-paradigms"},"nextItem":{"title":"Programmatic deployment (v0.4.x)","permalink":"/blog/2024/05/09/programmatic-deployment"}},"content":"Metatype\'s different language runtimes are nice, but integrating one is an entire story. Let\'s discover how we managed to implement one for Python.\\n\\n## Why?\\n\\nYou have probably heard of \\"Function as a Service\\" or FaaS. \\nIn simple terms, FaaS are platforms that allow users to run code in response to events without the hassle of managing the underlying infrastructure. \\nUsers submit their programs and the platform takes care of the rest including, usually, scaling, availability, and configuration.\\nAWS Lambda is one such example and FaaS as a whole are a popular implementation of the serverless model.\\n\\nMetatype has this model at heart with applications composed of small functions that respond to events like http requests and authorization checks. \\nThis is achieved through runtimes like the [`DenoRuntime`](/docs/reference/runtimes/deno) which implements a way to execute functions authored in Typescript using Web Workers as implemented by [Deno](https://docs.deno.com/runtime/manual/runtime/workers/) (not based on Deno Deploy). \\n\\n:::note\\nMetatype supports running multiple apps or typegraphs on a single deployed cluster but we\'re still in the kitchen on a hosted cloud solution. \\nSubscribe to the [blog](https://metatype.dev/blog/rss.xml) or the [Github](https://github.com/metatypedev/metatype) repository for updates.\\n:::\\n\\nImplementing the `DenoRuntime` was a very straightforward affair as the Typegate (the engine at the heart of Metatype) is primarily written in Typescript and runs on a slightly modified version of the Deno runtime.\\nWhat\'s more, JavaScript has single threaded and asynchronous semantics and the v8 engine that it commonly runs on is of very high-quality by all regards. \\nThese qualities lend themselves very well to the requirements of running a serverless platform like security (good sandboxing) and performance (low start-up latencies).\\nThis fact is reflected in the dominance of JavaScript in the serverless market though it doesn\'t hurt that it\'s also the most popular language in use today.\\n\\nAnother very popular language is Python; and its standard library can be quite resourceful for this type of use case.\\nHowever, as we shall see, integrating the Python runtime isn\'t as simple as integrating Deno.\\n\\n## What are the requirements?\\n\\nThere are a number of Python runtimes available but a set of extra factors limit what we can achieve.\\n\\n1. **Security**: functions should have limited access to the execution environment. Python doesn\'t have built-in features for sandboxing out of the box unlike Deno.\\n2. **Speed**: functions should run fast and with low latency. We\'re interested in metrics like cold-start latency and overhead of any cross process/system communication.\\n3. **User-friendliness**: functionalities provided in any of the languages supported by Metatype should, within reason, mirror each other and maintain a degree of uniformity. We support inline code snippets and external file references for `DenoRuntime` and this should be the case for Python as well.\\n4. **Interoperability**: functions running in Python will need to have access to other parts of the app running on the Typegate like being able to invoke other functions.\\n\\nThe Typegate is a TypeScript program with a bit of Rust sprinkled in. \\nIt runs as a traditional POSIX process. \\nThink Linux containers. \\nThis fact renders multi-processing, one of the readily apparent approaches, undesirable as it would require investing is robust worker process management and distribution schemes.\\nIt\'d be great if we could keep everything inside the Typegate process.\\n\\nOne solution that presents itself here is the [PyO3](https://pyo3.rs/) project which provide Rust bindings to different Python runtimes like CPython and PyPy.\\nIt\'d not only allow us to run Python code in-process but it also provide an easy way to expose the functions written in Rust to Python and vice-versa. \\nA good solution for the bidirectional communication needed for our interoperability requirements.\\n\\nUnfortunately, PyO3 doesn\'t have any provisions for sandboxing which is critical for our use case.\\nThis is where WebAssembly enters into the picture. \\nWebAssembly or Wasm for short is a executable bytecode format that originates from the web world and is designed for applications that run inside web-browsers. \\nThis use case shares most of our requirements and the Wasm world promises excellent sandboxing properties that should be perfect for our use case.\\nWe just have to find a way to run Python inside of it.\\n\\n## An aside on WASI \\n\\nWebAssembly System Interface (WASI) is an additional spec for the bytecode format that formalizes how Wasm programs access their host environment.\\nA lot like POSIX, this generally means OS capabilities such as file system access and networking but also, in it\'s latest iteration extends to any custom host defined functionality.\\n\\nWasm + WASI fits very well to our use case. As opposed to mutli-processing, we can instantiate, manage, and expose resources programmatically with ease.\\nAnd as luck would have it, some [community work](https://github.com/vmware-labs/webassembly-language-runtimes) has already been done at the time that led to wasm builds of CPython being available.\\n\\nUnfortunately, the WASI spec itself is a work in progress.\\nWhen we started out, only the limited \\"[preview1](https://github.com/WebAssembly/WASI/blob/main/legacy/preview1/docs.md)\\" implementation was supported by most runtimes.\\n`preview1` only focused on a standard set of host functionalities much like a `libc` implementation.\\nWell enough but any custom functionality meant having to rely on simple C ABI alike functions for _intra_-process communication.\\nIn order to make this work easier, we elected to bring PyO3 back into the picture so that all the IPC stuff is written in Rust, the language with the most support in the Wasm ecosystem today.\\n\\nAll in all, this would mean the python interpreter wrapped in a PyO3 based native API.\\nAn assembly that accepts user code as strings and then invokes them in response to events.\\nAll of this would be running inside a Wasm runtime, [WasmEdge](https://wasmedge.org/) in this case, which ticks of all of the sandboxing and security requirements.\\nThis approach is well described as the [Reactor pattern](https://wasmcloud.com/blog/webassembly-patterns-command-reactor-library#the-reactor-pattern), a common pattern used in Wasm land.\\n\\n\\"FIRST\\n\\n### File system access\\n\\nSince the PyO3 project doesn\'t support [statically linking](https://github.com/PyO3/pyo3/issues/416) the Python runtime, we\'ll need to find a way dynamically link `libpython`.\\nThankfully, Wasm does support [dynamic linking](https://github.com/WebAssembly/design/blob/main/DynamicLinking.md) and wasm builds of [`libpython`](https://github.com/vmware-labs/webassembly-language-runtimes/tree/main/python) are available curtsy of the WebAssembly Language Runtimes project. \\nBringing all of this together isn\'t as simple though as PyO3\'s tries to load `libpython` from certain _paths_, a concept that isn\'t exactly clearly defined in Wasm\'s post POSIX webtopia.\\n\\nOur first solution was to use [wasi-vfs](https://github.com/kateinoigakukun/wasi-vfs), a tool which allows you to embed a virtual file system, accessible through preview1 APIs, directly into your wasm binaries.\\nThis way, we could prepare a single wasm artifact that contains both the `libpython` build and the custom glue code.\\n\\nThis approach turned out to be quite hacky though and after encountering several issues, we ultimately decided to go with **preopens**.\\nPreopens are another virtual file-system solution where you map an actual file-system directory to a virtual directory visible to a running Wasm instance.\\nThis means we\'ll need to prepare the `libpython` Wasm file on disk before running the instance but it was an acceptable solution.\\nWe also use preopens to provide some of the user submitted code to our custom python runtime.\\n\\nThe following rust snippet demonstrates the preopens looked like in use:\\n\\n```rust\\nfn init_Python_vm() -> Result {\\n let preopens = vec![\\n // User script will be uploaded at ./src/Python which is virtually seen as /app\\n // Each script has access only to /app\\n \\"/app:./src/Python:readonly\\".to_owned()\\n ];\\n\\n // This follow the same idea as above, but for clarity\'s sake we decided to separate it\\n let pylib = PathBuf::from(\\"./vendor/libpython/usr/local/lib\\");\\n\\n // This is our wasm module reponsible for running Python scripts at runtime\\n // It assumes /app and libpython to be available in its world\\n let wasi_mod = PathBuf::from(\\"./build/Python-wasi-reactor.wasm\\");\\n\\n // Now we can instantiate the WASI module with all the configurations above\\n let rt = instantiate_custom_python_runtime(preopens, pylib, wasi_mod)?;\\n rt.run_func(None, \\"init_Python\\", params!())?;\\n\\n // ..\\n\\n Ok(rt)\\n}\\n```\\n\\n### WASI 0.2\\n\\nThe solution described above worked well to an extent but the limitations of preview1 and all the wrangling with PyO3 resulted in complexity that we were always ready to get rid of.\\nThis was exactly what we did after the Bytecode Alliance finalized [WASI 0.2](https://bytecodealliance.org/articles/WASI-0.2) back in January 2024 and with it, a slew of new opportunuties.\\n\\nWASI 0.2 introduces a whole new concept of components, wasm modules that come with pre-specifed interfaces using the [Wit](https://github.com/WebAssembly/component-model/blob/main/design/mvp/WIT.md) format and based on a whole new [ABI](https://github.com/WebAssembly/component-model/blob/main/design/mvp/CanonicalABI.md) to boot.\\nThese new capabilities suggest that it should possible to replace our PyO3 based glue code with the WASI based layer. \\nLet\'s see how.\\n\\nWe first used the new found WASI powers to implement support for Wasm based functions through the [`WasmRuntime`](/docs/reference/runtimes/wasm).\\nThis lead us to implement the [`wit_wire`](https://github.com/metatypedev/metatype/blob/2e692b9ae9e48b6e1a863130fc1bfbdd004cb631/src/wit/wit-wire.wit) protocol, a simple JSON based WIT interface that\'d be used by any wasm component that intenteds to run on the `WasmRuntime`.\\nSimple enough that it\'s reproduced down below in it\'s entirety.\\n\\n```wit\\npackage metatype:wit-wire;\\n\\n// what the host provides\\ninterface typegate-wire {\\n hostcall: func(op-name: string, json: string) -> result;\\n}\\n\\n// what\'s expected from the guest\\ninterface mat-wire {\\n\\n // init function called when we first make the component\\n init: func(args: init-args) -> result;\\n // general purpose event handler\\n handle: func(req: handle-req) -> result;\\n\\n type json-str = string;\\n\\n record init-args {\\n // the list of operations the application is expecting\\n // from this component\\n expected-ops: list\\n metatype-version: string,\\n }\\n\\n record mat-info {\\n op-name: string,\\n mat-title: string,\\n mat-data-json: string,\\n }\\n\\n record init-response {\\n ok: bool\\n }\\n\\n variant init-error {\\n version-mismatch(string),\\n unexpected-mat(mat-info),\\n other(string)\\n }\\n\\n record handle-req {\\n op-name: string,\\n in-json: json-str,\\n }\\n\\n variant handle-err {\\n no-handler,\\n in-json-err(string),\\n handler-err(string),\\n }\\n}\\n\\n// a world defines what interfaces get imported\\n// and exported\\nworld wit-wire {\\n import typegate-wire;\\n\\n export mat-wire;\\n}\\n\\n```\\n\\nSquint your eyes tight enough and the `wit_wire` protocol as implemented wasn\'t far off from what the PyO3 based glue code was doing in the previous implementation.\\nSpecifically, register a list of operations that the Typegate is expecting from the module and execute them for incoming event.\\nWe just need to add support for the operation metadata to contain extra items.\\nIn the case of the [`PythonRuntime`](/docs/reference/runtimes/python), this would be the Python code itself.\\n\\nNow that we have the `wit_wire` implementation taking care of bidirectional communication, we have little reason to keep the PyO3 based glue code around.\\nThis glue was doing a bit more than acting as a boundary though.\\nIt was also responsible for setting up the operating environment for the Python code.\\nFor example, we\'d need some kind of initialization to execute the user\'s Python snippets which are in free standing `lambda` form. \\nHow does one create components out of Python anyways?\\n\\n[componentize-py](https://github.com/bytecodealliance/componentize-py) is a tool authored by the Bytecode Alliance that allows you to produce WASI components that are authored in Python.\\nIt has code generation suite that emits guest bindings in Python for any WIT specification you feed it.\\nIt then takes your Python code written against these bindings and embeds them in a Wasm build of the Python interpreter to produce a component that supports the specified Wit.\\n\\nUnsurprisingly, componentize-py relies on PyO3 and preopens itself in addition to [component-init](https://github.com/dicej/component-init), a solution to pre-intialize components up to a certain point for improved startup latencies.\\nThis pre-intialization means we won\'t need to provide the actual preopens for the resulting component, baking the `libpython` object code directly into it as PyO3 will have dynamically loaded the object code by that point.\\nUltimately, this allows us to write all of our glue code in Python itself.\\n\\nWe still need a bit of Rust to support the `wit_wire` interface on the Typegate but this implementation is general across both the `PythonRuntime` and `WasmRuntime`.\\nWe\'d also moved to the [Wasmtime](https://wasmtime.dev/), also by Bytecode Alliance, for our wasm workloads at this point and their Rust bindings are a pleasure to use.\\nIt\'s all smooth sailing from here.\\n\\n## Cloudy skies?\\n\\nA final stumbling block for this approach was the many seconds Wasmtime spends cooking all your CPU cores when it compiles the fat wasm module that contains the Python interpreter, Pyo3 bindings and more.\\nThis happens because Wasmtime does\'t ([yet](https://github.com/bytecodealliance/rfcs/blob/main/accepted/wasmtime-baseline-compilation.md)) implement any schemes for tiered compilation, all code being greeted by their optimizing compiler, Cranelift.\\nAnd optimizations take time.\\nSure, you only pay this cost the first time you load the Python runtime module as Wasmtime has great support for caching including on-disk caching.\\nBut, 10+ second cold-starts, as measured on one developer\'s machine, are unacceptable in a system that primarily serves HTTP requests.\\nWhat to do?\\n\\nWasmtime has just the feature for this problem, [pre-compilation](https://docs.wasmtime.dev/cli-options.html#compile).\\nAhead-of-time compilation of wasm bytecode into a native instruction set.\\nSuch files are commonly given the `.cwasm` extesion, _c_ for compiled, and they are not a standalone executable but inteded to be run within Wasmtime\'s sandbox.\\nThis eliminates the compliation cost but the semantics of the source wasm bytecode and the runtime safe-guards means that this should be just as safe as JITting it (just-in-time compilation).\\nWe then statically embed this pre-compiled wasm artifact, after compressing it, in the Typegate binary removing the need for sidecar files while ensuring minimal cold-starts for our python workloads.\\nTo be concrete, this means _roughly_ around 200 ms of overhead for a cold function and 5 ms for a warm one.\\nGood enough.\\n\\nThis post describes the technical journey we took to arrive to the current implementation of the `PythonRuntime`. Hopefully, all details were clear enough and please direct any feedback, questions, and thoughts to the comments down below and our Github issues/discussion board."},{"id":"/2024/05/09/programmatic-deployment","metadata":{"permalink":"/blog/2024/05/09/programmatic-deployment","editUrl":"https://github.com/metatypedev/metatype/tree/main/docs/metatype.dev/blog/2024-05-09-programmatic-deployment/index.mdx","source":"@site/blog/2024-05-09-programmatic-deployment/index.mdx","title":"Programmatic deployment (v0.4.x)","description":"A new approach to deploying typegraphs has been introduced starting with version 0.4.0. This aims to facilitate the development of automation tools around the APIs you build within the Metatype ecosystem.","date":"2024-05-09T00:00:00.000Z","tags":[],"readingTime":3.405,"hasTruncateMarker":false,"authors":[],"frontMatter":{},"unlisted":false,"prevItem":{"title":"Python on WebAssembly: How?","permalink":"/blog/2024/08/26/python-on-webassembly"},"nextItem":{"title":"The Node/Deno SDK is now available","permalink":"/blog/2023/11/27/node-compatibility"}},"content":"import SDKTabs from \\"@site/src/components/SDKTabs\\";\\nimport TabItem from \\"@theme/TabItem\\";\\nimport UpgradePythonSDK from \\"../../shared/upgrade/python-sdk.mdx\\";\\nimport UpgradeTsSDK from \\"../../shared/upgrade/typescript-sdk.mdx\\";\\n\\n\\nA new approach to deploying typegraphs has been introduced starting with version 0.4.0. This aims to facilitate the development of automation tools around the APIs you build within the Metatype ecosystem.\\n\\n## What has changed?\\n\\nBefore v0.4.x, we had to entirely rely on the [meta cli](/docs/reference/meta-cli) to deploy typegraphs to a typegate instance.\\n\\nThis is no longer the case, as all core logic has been moved to the TypeScript/Python typegraph SDKs, both of which share the same WebAssembly-based **typegraph-core** behind the scenes. This provides some degree of assurance that you will have nearly identical experiences with each SDK.\\n\\n## What are the use-cases?\\n\\nSince typegraphs can be written using the programming language your preferred SDK is based on, you can dynamically create typegraphs with ease.\\n\\nThe missing piece was having an interface natively backed inside the SDK for doing deployment programmatically.\\n\\n### Programmatic deployment\\n\\n### Initial setup\\n\\nJust like any other dependency in your favorite programming language, each SDKs can be installed with your favorite package manager.\\n\\nYou can use one of the commands below to get started with the latest available version.\\n\\n\\n \\n \\n \\n \\n \\n \\n\\n\\n#### Configuration\\n\\nThis is analoguous to the yaml configuration file when you are using [meta cli](/docs/reference/meta-cli).\\n\\nIt\'s the place where you tell which typegate you want to deploy to, how you want the artifacts to be resolved, among other settings.\\n\\n\\n \\n\\n```python\\nconfig: TypegraphDeployParams = TypegraphDeployParams(\\n typegate=TypegateConnectionOptions(url=\\"\\", auth=BasicAuth(\\"\\", \\"\\")),\\n typegraph_path=os.path.join(cwd, \\"path-to-typegraph\\"),\\n prefix=\\"\\",\\n secrets={},\\n migrations_dir=path.join(\\"prisma-migrations\\", example.name),\\n migration_actions=None,\\n default_migration_action=MigrationAction(\\n apply=True,\\n reset=True, # allow destructive migrations\\n create=True,\\n ),\\n )\\n```\\n\\n \\n \\n\\n```typescript\\nconst config = {\\n typegate: {\\n url: \\"\\",\\n auth: new BasicAuth(\\"\\", \\"\\"),\\n },\\n typegraphPath: path.join(cwd, \\"path-to-typegraph.ts\\"),\\n prefix: \\"\\",\\n secrets: { POSTGRES: \\"\\" },\\n migrationsDir: path.join(\\"prisma-migrations\\", tg.name),\\n defaultMigrationAction: {\\n create: true,\\n reset: true, // allow destructive migrations\\n },\\n};\\n```\\n\\n \\n\\n\\n\\n### Deploy/remove\\n\\nNow, picture this, you have a lot of typegraphs and one or more typegate instance(s) running, you can easily make small scripts that does any specific job you want.\\n\\n```typescript\\n// ..\\nimport { tgDeploy, tgRemove } from \\"@typegraph/sdk/tg_deploy.js\\";\\n// ..\\n\\nconst BASIC_AUTH = loadMyAuthsFromSomeSource();\\nconst TYPEGATE_URL = \\"...\\";\\n\\nexport async function getTypegraphs() {\\n // Suppose we have these typegraphs..\\n // Let\'s enumerate them like this to simplify\\n return [\\n {\\n tg: await import(\\"path/to/shop-finances\\"),\\n location: \\"path/to/shop-finances.ts\\",\\n },\\n {\\n tg: await import(\\"path/to/shop-stats\\"),\\n location: \\"path/to/shop-stats.ts\\",\\n },\\n ];\\n}\\n\\nexport function getConfig(tgName: string, tgLocation: string) {\\n // Note: You can always develop various ways of constructing the configuration,\\n // like loading it from a file.\\n return {\\n typegate: {\\n url: \\"\\",\\n auth: new BasicAuth(\\"\\", \\"\\"),\\n },\\n typegraphPath: path.join(cwd, \\"path-to-typegraph.ts\\"),\\n prefix: \\"\\",\\n secrets: { POSTGRES: \\"\\" },\\n migrationsDir: path.join(\\"prisma-migrations\\", tg.name),\\n defaultMigrationAction: {\\n create: true,\\n reset: true, // allow destructive migrations\\n },\\n };\\n}\\n\\nexport async function deployAll() {\\n const typegraphs = await getTypegraphs();\\n for (const { tg, location } of typegraphs) {\\n try {\\n const config = getConfig(tg.name, location);\\n // use tgDeploy to deploy typegraphs, it will contain the response from typegate\\n const { typegate } = await tgDeploy(tg, config);\\n const selection = typegate?.data?.addTypegraph;\\n if (selection) {\\n const { messages } = selection;\\n console.log(messages.map(({ text }) => text).join(\\"\\\\n\\"));\\n } else {\\n throw new Error(JSON.stringify(typegate));\\n }\\n } catch (e) {\\n console.error(\\"[!] Failed deploying\\", tg.name);\\n console.error(e);\\n }\\n }\\n}\\n\\nexport async function undeployAll() {\\n const typegraphs = await getTypegraphs();\\n for (const { tg } of typegraphs) {\\n try {\\n // use tgRemove to remove typegraphs\\n const { typegate } = await tgRemove(\\"\\", {\\n baseUrl: TYPEGATE_URL,\\n auth: BASIC_AUTH,\\n });\\n console.log(typegate);\\n } catch (e) {\\n console.error(\\"Failed removing\\", tg.name);\\n console.error(e);\\n }\\n }\\n}\\n```\\n\\n### Going beyond\\n\\nWith these new additions, you can automate virtually anything programmatically on the typegraph side. Starting from having highly dynamic APIs to providing ways to deploy and configure them, you can even build a custom framework around the ecosystem!\\n\\nPlease tell us what you think and report any issues you found on [Github](https://github.com/metatypedev/metatype/issues).\\n\\n:::info Notes\\n\\nYou can check the [Programmatic deployment](/docs/guides/programmatic-deployment) reference page for more information.\\n\\n:::"},{"id":"/2023/11/27/node-compatibility","metadata":{"permalink":"/blog/2023/11/27/node-compatibility","editUrl":"https://github.com/metatypedev/metatype/tree/main/docs/metatype.dev/blog/2023-11-27-node-compatibility/index.mdx","source":"@site/blog/2023-11-27-node-compatibility/index.mdx","title":"The Node/Deno SDK is now available","description":"We are happy to announce that we have redesigned our SDKs to support Node/Deno and facilitate the integration of future languages. Most of the typegraph SDK is now written in Rust and shaped around a core interface running in WebAssembly.","date":"2023-11-27T00:00:00.000Z","tags":[],"readingTime":1.7,"hasTruncateMarker":false,"authors":[],"frontMatter":{},"unlisted":false,"prevItem":{"title":"Programmatic deployment (v0.4.x)","permalink":"/blog/2024/05/09/programmatic-deployment"},"nextItem":{"title":"Programmable glue for developers","permalink":"/blog/2023/06/18/programmable-glue"}},"content":"We are happy to announce that we have redesigned our SDKs to support Node/Deno and facilitate the integration of future languages. Most of the [typegraph SDK](/docs/reference/typegraph) is now written in Rust and shaped around a core interface running in WebAssembly.\\n\\n## Meet `wit`\\n\\nIn the realm of WebAssembly, the [wit-bindgen](https://github.com/bytecodealliance/wit-bindgen) project emerges as the most mature tool to create and maintain the language bindings for WebAssembly modules. This tool introduces WIT (WebAssembly Interface Types) as an Interface Definition Language (IDL) to describe the imports, exports, and capabilities of WebAssembly components seamlessly.\\n\\nFor example, Metatype implements the reactor pattern to handle requests as they come and delegate part of their execution in correct WASM runtime. The wit-bindgen helps there to define the interfaces between the guest (the Metatype runtime) and the host (the typegate) to ensure the correct serialization of the payloads. The `wit` definition could look like this:\\n\\n```\\npackage metatype:wit-wire;\\n\\ninterface typegate-wire {\\n hostcall: func(op-name: string, json: string) -> result;\\n}\\n\\ninterface mat-wire {\\n record handle-req {\\n op-name: string,\\n in-json: string,\\n }\\n\\n handle: func(req: handle-req) -> result;\\n}\\n\\nworld wit-wire {\\n import typegate-wire;\\n\\n export mat-wire;\\n}\\n```\\n\\nThe `wit` file is then used to generate the bindings for the host and the guest in Rust, TypeScript, Python, and other languages. The host bindings are used in the typegate to call the WASM runtime, and the guest bindings are used in the WASM runtime to call the typegate.\\n\\n## Install the v0.2.x series\\n\\nThe documentation contains now examples for Node and Deno.\\n\\n### Upgrade with Node\\n\\n```bash\\nnpm install @typegraph/sdk\\nmeta new --template node .\\n```\\n\\n### Upgrade with Deno\\n\\n```bash\\nmeta new --template deno .\\n```\\n\\n```typescript\\nimport { typegraph } from \\"npm:@typegraph/sdk/index.js\\";\\n```\\n\\n### Upgrade with Python\\n\\n```python\\npip3 install --upgrade typegraph\\npoetry add typegraph@latest\\n```\\n\\n## Give us feedback!\\n\\nThis new release enables us to provide a consistent experience across all languages and reduce the work to maintain the existing Python SDK.\\n\\nAs always, report issues and let us know what you think on [GitHub](https://github.com/metatypedev/metatype/discussions)."},{"id":"/2023/06/18/programmable-glue","metadata":{"permalink":"/blog/2023/06/18/programmable-glue","editUrl":"https://github.com/metatypedev/metatype/tree/main/docs/metatype.dev/blog/2023-06-18-programmable-glue/index.mdx","source":"@site/blog/2023-06-18-programmable-glue/index.mdx","title":"Programmable glue for developers","description":"We are introducing Metatype, a new project that allows developers to build modular and strongly typed APIs using typegraph as a programmable glue.","date":"2023-06-18T00:00:00.000Z","tags":[],"readingTime":1.295,"hasTruncateMarker":false,"authors":[],"frontMatter":{},"unlisted":false,"prevItem":{"title":"The Node/Deno SDK is now available","permalink":"/blog/2023/11/27/node-compatibility"},"nextItem":{"title":"Emulating your server nodes locally","permalink":"/blog/2023/03/15/emulating-servers"}},"content":"import { CompareLandscape } from \\"@site/src/components/CompareLandscape\\";\\nimport Metatype from \\"@site/shared/metatype-intro.mdx\\";\\nimport TGExample from \\"@site/src/components/TGExample\\";\\n\\n\\nWe are introducing Metatype, a new project that allows developers to build modular and strongly typed APIs using typegraph as a programmable glue.\\n\\n## What is Metatype?\\n\\n\\n\\n## What are virtual graphs?\\n\\nTypegraphs are a declarative way to expose all APIs, storage and business logic of your stack as a single graph. They take inspiration from domain-driven design principles and in the idea that the relation between of the data is as important as data itself, even though they might be in different locations or shapes.\\n\\n\\n\\nThese elements can then be combined and composed together similarly on how you would compose web components to create an interface in modern frontend practices. This allows developers to build modular and strongly typed APIs using typegraph as a programmable glue.\\n\\n## Where does this belong in the tech landscape?\\n\\nBefore Metatype, there was a gap in the technological landscape for a solution that specifically addressed the transactional, short-lived use cases. While there were existing tools for analytical or long-running use cases, such as Trino and Temporal, there was no generic engine for handling transactional, short-lived tasks.\\n\\n \\n\\n## Give it a try!\\n\\nLet us know what you think! Metatype is open source and we welcome any feedback or contributions. The community primarily lives on [GitHub](https://github.com/metatypedev/metatype).\\n\\n:::info Next steps\\n\\n[Build your first typegraph](/docs/tutorials/metatype-basics) or read more about the [concepts behind Metatype](/docs/concepts/mental-model).\\n\\n:::"},{"id":"/2023/03/15/emulating-servers","metadata":{"permalink":"/blog/2023/03/15/emulating-servers","editUrl":"https://github.com/metatypedev/metatype/tree/main/docs/metatype.dev/blog/2023-03-15-emulating-servers/index.mdx","source":"@site/blog/2023-03-15-emulating-servers/index.mdx","title":"Emulating your server nodes locally","description":"Introducing the Embedded Typegate","date":"2023-03-15T00:00:00.000Z","tags":[],"readingTime":3.07,"hasTruncateMarker":false,"authors":[],"frontMatter":{},"unlisted":false,"prevItem":{"title":"Programmable glue for developers","permalink":"/blog/2023/06/18/programmable-glue"}},"content":"import BlogIntro from \\"@site/src/components/BlogIntro\\";\\nimport UpgradeMetatype from \\"../../shared/upgrade/index.mdx\\";\\n\\n\\n\\n\\n## Introducing the Embedded Typegate\\n\\nThe embedded typegate is a feature that comes with the [Meta CLI](/docs/reference/meta-cli) which provides the option of spinning a typegate instance from the CLI with minimum configurations and installations needed from the developer. All that is required to access the _Embedded Typegate_ is to install _Meta CLI_. The spawned typegate instance behaves similarly to cloud-deployed typegates.\\n\\n## The motive\\n\\nThere are more than a couple of reasons why a developer would be tempted to use an emedded typegate. While developers can start a typegate instance using docker compose, the developer needs to install docker as a dependency to run the typegate container. Even though docker is familiar among many developers, it can sometimes be tricky and unbeknownst to some developers. We at metatype highly value the developer experience and one reason for adding the _embedded typegate_ feature to the _Meta CLI_ is for users to have a smooth experience with our system by providing a docker compose free experience.\\nThis feature provides a great utility for developers to author and test typegraphs in their local machine before deploying them to production level typegate instances on the cloud.\\nAdditionally, developers need not concern themselves with deployment configurations which are needed only during deployment. The only need to focus their energy and time in developing the right application and easily test them on _embedded typegate_ running from the terminal. To add more to what is said, as the typegate engine keeps evolving, users will be abstracted away from the different configurations which might be added on the future. The _Meta CLI_ will abstract much of what\'s not needed in a dev environment. Thus, leaving less headaches to developers on new changes.\\nUltimately, The _embedded typegate_ is designed to be a good dev environment friendly tool which faciliates development time.\\n\\n## Quick First hand example\\n\\n### Install the v0.3.x series\\n\\nEither of the two [Typegraph](/docs/reference/typegraph) SDKs are needed to author typegraphs. For this example, the node SDK will be used.\\n\\nFirst, make sure the _Meta CLI_ is installed.\\n\\n```shell\\ncurl -fsSL https://raw.githubusercontent.com/metatypedev/metatype/main/installer.sh | bash\\n```\\n\\nNext, create a new node project using this command.\\n\\n```shell\\nmeta new --template node\\n```\\n\\nThe above command will create a sample typegraph which you can use to test the embedded typegate.\\n\\nNow, you need to install the typegraph SDK by running the command down below. The previous command generates a `package.json` with the SDK specified as a dependency.\\n\\n```shell\\nnpm install\\n```\\n\\nBefore deploying the typegraph to the embedded typegate, Run the following commands below.\\n\\n```shell\\nmeta dev\\n```\\n\\nNow that there is running instance of a typegate, you can deploy the example typegraph. From another terminal, run the command below.\\n\\n```shell\\nmeta deploy -f api/example.ts --allow-dirty --create-migration --target dev --gate http://localhost:7890\\n```\\n\\nThe typegate runs on port 7890 by default. If you access [http://localhost:7890/example](http://localhost:7890/example) on your browser, you can see an GraphQL interface to interact with the deployed typegraph. You can test the example typegraph using the following graphql query below.\\n\\n```graphql\\nquery {\\n multilpy(first: 3, second: 5)\\n}\\n```\\n\\n\\n\\n## Learn more about Metatype\\n\\nWanna dive deep into the basics of _Metaype_? check our interactive [tutorial](/docs/tutorials/metatype-basics) revolving around the core features of the system."}]}}')}}]); \ No newline at end of file diff --git a/assets/js/b3219b4c.79a25fcd.js b/assets/js/b3219b4c.79a25fcd.js deleted file mode 100644 index 732df01102..0000000000 --- a/assets/js/b3219b4c.79a25fcd.js +++ /dev/null @@ -1 +0,0 @@ -"use strict";(self.webpackChunkwebsite=self.webpackChunkwebsite||[]).push([[3099],{83890:e=>{e.exports=JSON.parse('{"archive":{"blogPosts":[{"id":"/2024/08/27/distributed-execution-flow-paradigms","metadata":{"permalink":"/blog/2024/08/27/distributed-execution-flow-paradigms","editUrl":"https://github.com/metatypedev/metatype/tree/main/docs/metatype.dev/blog/2024-08-27-distributed-execution-flow-paradigms/index.mdx","source":"@site/blog/2024-08-27-distributed-execution-flow-paradigms/index.mdx","title":"Distributed execution flow paradigms","description":"In this age of cloud development and microservices architecture, problems start to arise with the increased workloads that run in the system. Imagine an e-commerce platform where a customer places an order for a product during a high-demand sale event. The order triggers a series of interconnected processes: payment processing, inventory checks, packaging, shipping, and final delivery. Each of these processes might be handled by different microservices, potentially running on different servers or even in different data centers. What happens if the payment service goes down right after the payment is authorized but before the inventory is updated? Or if the packaging service fails just after the inventory is deducted but before the item is packed? Without a robust mechanism to ensure that each step in the workflow completes successfully and that failures are properly handled, you could end up with unhappy customers, lost orders, and inventory discrepancies.","date":"2024-08-27T00:00:00.000Z","tags":[],"readingTime":10.93,"hasTruncateMarker":false,"authors":[],"frontMatter":{},"unlisted":false,"nextItem":{"title":"Python on WebAssembly: How?","permalink":"/blog/2024/08/26/python-on-webassembly"}},"content":"import TabItem from \\"@theme/TabItem\\";\\nimport SDKTabs from \\"@site/src/components/SDKTabs\\";\\n\\n\\nIn this age of cloud development and microservices architecture, problems start to arise with the increased workloads that run in the system. Imagine an e-commerce platform where a customer places an order for a product during a high-demand sale event. The order triggers a series of interconnected processes: payment processing, inventory checks, packaging, shipping, and final delivery. Each of these processes might be handled by different microservices, potentially running on different servers or even in different data centers. What happens if the payment service goes down right after the payment is authorized but before the inventory is updated? Or if the packaging service fails just after the inventory is deducted but before the item is packed? Without a robust mechanism to ensure that each step in the workflow completes successfully and that failures are properly handled, you could end up with unhappy customers, lost orders, and inventory discrepancies.\\n\\nHaving multiple components in your system introduces more failure points, which is a common phenomenon in complex systems. But one important behavior any application must ensure is that the execution flow reaches its completion. As systems grow in features and complexity, the likelihood of long-running processes increases. To ensure these processes complete as intended, several solutions have been introduced over the last few decades.\\nLet\'s explore some of the solutions that have been proposed to achieve workflow completeness.\\n\\n### 1. Event-Driven Architecture with Message Queues\\n\\nThis architecture relies heavily on services communicating by publishing and subscribing to events using message queues. Message queues are persistent storages that ensure data is not lost during failures or service unavailability. Components in a distributed system synchronize by using events/messages through these independent services. While this approach offers service decomposability and fault tolerance, it has some shortcomings. For example, using message queues comes with the overhead of managing messages (e.g., deduplication and message ordering). It also isn\u2019t ideal for systems requiring immediate consistency across components. Some technologies and patterns that utilize this architecture include:\\n\\n- [RabbitMQ](https://www.rabbitmq.com/)\\n- [Amazon SQS](https://aws.amazon.com/sqs/)\\n\\n![](eda.drawio.svg)\\n\\n
\\n Fig. Event Driven Architecture with Message Queues - RabbitMQ\\n
\\n\\n#### Advantages\\n\\n- Improved Scalability\\n- Enhanced Responsiveness\\n- Enhanced Fault Tolerance\\n- Simplified Complex Workflows\\n- Real-Time Data Processing\\n\\n#### Challenges\\n\\n- Event Ordering\\n- Data Consistency\\n- Monitoring and Debugging\\n- Event Deduplication\\n\\nYou can mitigate or reduce these challenges by following best practices like Event Sourcing, Idempotent Processing, CQRS (Command Query Responsibility Segregation), and Event Versioning.\\n\\n### 2. The [Saga Pattern](https://microservices.io/patterns/data/saga.html)\\n\\nThis design pattern aims to achieve consistency across different services in a distributed system by breaking complex transactions spanning multiple components into a series of local transactions. Each of these transactions triggers an event or message that starts the next transaction in the sequence. If any local transaction fails to complete, a series of compensating actions roll back the effects of preceding transactions. While the orchestration of local transactions can vary, the pattern aims to achieve consistency in a microservices-based system. Events are designed to be stored in durable storage systems or logs, providing a trail to reconstruct the system to a state after a failure. While the saga pattern is an effective way to ensure consistency, it can be challenging to implement timer/timeout-based workflows and to design and implement the compensating actions for local transactions.\\n\\n**Note**: In the Saga pattern, a compensating transaction must be idempotent and retryable. These principles ensure that transactions can be managed without manual intervention.\\n\\n![](saga.drawio.svg)\\n\\n
\\n Fig. The Saga Pattern for Order delivery system\\n
\\n\\n#### Advantages\\n\\n- Ensures data consistency in a distributed system without tight coupling.\\n- Provides Roll back if one of the operations in the sequence fails.\\n\\n#### Drawbacks\\n\\n- Might be challenging to implement initially.\\n- Hard to debug.\\n- Compensating transactions don\u2019t always work.\\n\\n### 3. [Stateful Orchestrators](https://docs.oracle.com/en/applications/jd-edwards/cross-product/9.2/eotos/creating-a-stateful-orchestration-release-9-2-8-3.html#u30249073)\\n\\nStateful orchestrators provide a solution for long-running workflows by maintaining the state of each step in a workflow. Each step in a workflow represents a task, and these tasks are represented as states inside workflows. Workflows are defined as state machines or directed acyclic graphs (DAGs). In this approach, an orchestrator handles task execution order, transitioning, handling retries, and maintaining state. In the event of a failure, the system can recover from the persisted state. Stateful orchestrators offer significant value in fault tolerance, consistency, and observability. It\u2019s one of the solutions proven effective in modern distributed computing. Some well-known services that provide this solution include:\\n\\n- [Apache Airflow](https://airflow.apache.org/docs/apache-airflow/stable/core-concepts/overview.html)\\n- [Azure Logic Apps](https://azure.microsoft.com/en-us/products/logic-apps)\\n\\n#### Advantages\\n\\n- **High Resiliency**: Stateful orchestrators provide high resiliency in case of outages, ensuring that workflows can continue from where they left off.\\n- **Data Persistence**: They allow you to keep, review, or reference data from previous events, which is useful for long-running processes.\\n- **Extended Runtime**: Stateful workflows can continue running for much longer than stateless workflows, making them suitable for complex and long-running tasks.\\n\\n#### Challenges\\n\\n- **Additional Complexity**: They introduce additional complexity, requiring you to manage issues such as load balancing, CPU and memory usage, and networking.\\n- **Cost**: With stateful workflows, you pay for the VMs that are running in the cluster, whereas with stateless workflows, you pay only for the actual compute resources consumed.\\n\\n### 4. Durable Execution\\n\\nDurable execution refers to the ability of a system to preserve the state of an application and persist execution despite failures or interruptions. Durable execution ensures that for every task, its inputs, outputs, call stack, and local variables are persisted. These constraints, or rather features, allow a system to automatically retry or continue running in the face of infrastructure or system failures, ultimately ensuring completion.\\n\\nDurable execution isn\u2019t a completely distinct solution from the ones listed above but rather incorporates some of their strengths while presenting a more comprehensive approach to achieving consistency, fault tolerance, data integrity, resilience for long-running processes, and observability.\\n\\n\\n
Fig. Durable workflow engine
\\n\\n#### Advantages\\n\\n- **Reduced Manual Intervention**: Minimizes the need for human intervention by handling retries and failures programmatically.\\n- **Improved Observability**: Provides a clear audit trail and visibility into the state of workflows, which aids in debugging and monitoring.\\n- **Scalability**: Scales efficiently across distributed systems while maintaining workflow integrity.\\n\\n#### Challenges\\n\\n- **Resource Intensive**: Persistent state storage and management can consume significant resources, especially in large-scale systems.\\n- **Latency**: The need to persist state and handle retries can introduce latency in the execution flow.\\n\\nAs durable execution grows to be a fundamental driver of distributed computing, some of the solutions which use this architecture are\\n\\n- [Temporal](https://temporal.io/)\\n- [Uber Cadence](https://cadenceworkflow.io/)\\n\\nAmong these, [Temporal](https://temporal.io/) has grown in influence, used by companies like SnapChat, HashiCorp, Stripe, DoorDash, and DataDog. Its success is driven by its practical application in real-world scenarios and the expertise of its founders.\\n\\nAt Metatype, we recognize the value of durable execution and are committed to making it accessible. Our [Temporal Runtime](/docs/reference/runtimes/temporal) integrates seamlessly into our declarative API development platform, enabling users to harness the power of Temporal directly within Metatype. For those interested in exploring further, our documentation provides a detailed guide on getting started with [Temporal Runtime](/docs/reference/runtimes/temporal).\\n\\nBelow is an example of how you can build a simple API to interact with an order delivery temporal workflow within Metatype.\\n\\n:::note\\nIf you are new to Metatype or haven\u2019t set it up yet in your development environment. You can follow this [guideline](/docs/tutorials/quick-start).\\n:::\\n\\nFor this example, the order delivery system will have few components/services such as Payment, Inventory and Delivery.\\n\\nYour temporal workflow definition should look similar to the one below.\\n\\n\\n\\n \\n\\n
\\n\\nActivities definition inside `src/activities.ts`:`\\n\\n```typescript\\nasync function sleep(time: number) {\\n return new Promise((resolve) => {\\n setTimeout(resolve, time);\\n });\\n}\\n\\nexport async function processPayment(orderId: string): Promise {\\n console.log(`Processing payment for order ${orderId}`);\\n // Simulate payment processing logic\\n await sleep(2);\\n return \\"Payment processed\\";\\n}\\n\\nexport async function checkInventory(orderId: string): Promise {\\n console.log(`Checking inventory for order ${orderId}`);\\n // Simulate inventory check logic\\n await sleep(2);\\n return \\"Inventory available\\";\\n}\\n\\nexport async function deliverOrder(orderId: string): Promise {\\n console.log(`Delivering order ${orderId}`);\\n // Simulate delivery logic\\n await sleep(5);\\n return \\"Order delivered\\";\\n}\\n```\\n\\n
\\n\\n
\\n\\nWorkflow definition inside `src/workflows.ts`:\\n```typescript import {proxyActivities} from \\"@temporalio/workflow\\";\\n\\nexport const { processPayment, checkInventory, deliverOrder } =\\n proxyActivities<{\\n processPayment(orderId: string): Promise;\\n checkInventory(orderId: string): Promise;\\n deliverOrder(orderId: string): Promise;\\n }>({\\n startToCloseTimeout: \\"10 seconds\\",\\n });\\n\\nexport async function OrderWorkflow(orderId: string): Promise {\\n const paymentResult = await processPayment(orderId);\\n const inventoryResult = await checkInventory(orderId);\\n const deliveryResult = await deliverOrder(orderId);\\n return `Order ${orderId} completed with results: ${paymentResult}, ${inventoryResult}, ${deliveryResult}`;\\n}\\n```\\n
\\n\\n
\\nWorker definintion inside `src/worker.ts`:\\n\\n```typescript\\nimport { NativeConnection, Worker } from \\"@temporalio/worker\\";\\nimport * as activities from \\"./activities\\";\\nimport { TASK_QUEUE_NAME } from \\"./shared\\";\\n\\nasync function run() {\\n const connection = await NativeConnection.connect({\\n address: \\"localhost:7233\\",\\n });\\n\\n const worker = await Worker.create({\\n connection,\\n namespace: \\"default\\",\\n taskQueue: TASK_QUEUE_NAME,\\n workflowsPath: require.resolve(\\"./workflows\\"),\\n activities,\\n });\\n\\n await worker.run();\\n}\\n\\nrun().catch((err) => {\\n console.error(err);\\n process.exit(1);\\n});\\n```\\n\\n
\\n\\nAfter you have setup the above components, now you need a client to start of any `OrderWorkflow`. Here is where metatype comes in, through the simple APIs [Temporal Runtime](/docs/reference/runtimes/temporal) exposes, you can communicate with your temporal cluster.\\nDown below is the workflow communication bridge for this system expressed within a [typegraph](/docs/reference/typegraph) which includes endpoints to start a new workflow and describe an existing one.\\n\\n```typescript\\nimport { Policy, t, typegraph } from \\"@typegraph/sdk/index.ts\\";\\nimport { TemporalRuntime } from \\"@typegraph/sdk/providers/temporal.ts\\";\\n\\ntypegraph(\\n {\\n name: \\"order_delivery\\",\\n },\\n (g: any) => {\\n const pub = Policy.public();\\n\\n const temporal = new TemporalRuntime({\\n name: \\"order_delivery\\",\\n hostSecret: \\"HOST\\",\\n namespaceSecret: \\"NAMESPACE\\",\\n });\\n\\n const workflow_id = \\"order-delivery-1\\";\\n\\n const order_id = t.string();\\n\\n g.expose(\\n {\\n start: temporal.startWorkflow(\\"OrderWorkflow\\", order_id),\\n describe: workflow_id\\n ? temporal.describeWorkflow().reduce({ workflow_id })\\n : temporal.describeWorkflow(),\\n },\\n pub,\\n );\\n },\\n);\\n```\\n\\n \\n\\n {/* break */}\\n \\n\\n
\\nActivities definition inside `activities.py`.\\n\\n```python\\nfrom temporalio import activity\\nimport time\\n\\n@activity.defn\\nasync def process_payment(order_id: str) -> str:\\n print(f\\"Processing payment for order {order_id}\\")\\n # Simulate payment processing logic\\n time.sleep(5)\\n return \\"Payment processed\\"\\n\\n@activity.defn\\nasync def check_inventory(order_id: str) -> str:\\n print(f\\"Checking inventory for order {order_id}\\")\\n # Simulate inventory check logic\\n time.sleep(4)\\n return \\"Inventory available\\"\\n\\n@activity.defn\\nasync def deliver_order(order_id: str) -> str:\\n print(f\\"Delivering order {order_id}\\")\\n time.sleep(8)\\n # Simulate delivery logic\\n return \\"Order delivered\\"\\n```\\n\\n
\\n\\n
\\nWorker defintion inside `run_worker.py`.\\n\\n```python\\nimport asyncio\\n\\nfrom temporalio.client import Client\\nfrom temporalio.worker import Worker\\n\\nfrom activities import process_payment, deliver_order, check_inventory\\nfrom shared import ORDER_DELIVERY_QUEUE\\nfrom workflows import OrderWorkflow\\n\\n\\nasync def main() -> None:\\n client: Client = await Client.connect(\\"localhost:7233\\", namespace=\\"default\\")\\n worker: Worker = Worker(\\n client,\\n task_queue=ORDER_DELIVERY_QUEUE,\\n workflows=[OrderWorkflow],\\n activities=[process_payment, check_inventory, deliver_order],\\n )\\n await worker.run()\\n\\n\\nif __name__ == \\"__main__\\":\\n asyncio.run(main())\\n```\\n\\n
\\n\\nAfter you have setup the above components, now you need a client to start of any `OrderWorkflow`. Here is where metatype comes in, through the simple APIs [Temporal Runtime](/docs/reference/runtimes/temporal) exposes, you can communicate with your temporal cluster.\\nDown below is the workflow communication bridge for this system expressed within a [typegraph](/docs/reference/typegraph) which includes endpoints to start a new workflow and describe an existing one.\\n\\n```python\\nfrom typegraph import t, typegraph, Policy, Graph\\nfrom typegraph.providers.temporal import TemporalRuntime\\n\\n\\n@typegraph()\\ndef example(g: Graph):\\n public = Policy.public()\\n\\n temporal = TemporalRuntime(\\n \\"example\\", \\"HOST\\", namespace_secret=\\"NAMESPACE\\"\\n )\\n\\n workflow_id = \\"order-delivery-1\\"\\n\\n order_id = t.string()\\n\\n g.expose(\\n public,\\n start=temporal.start_workflow(\\"OrderWorkflow\\", order_id),\\n describe=temporal.describe_workflow().reduce({\\"workflow_id\\": workflow_id})\\n if workflow_id\\n else temporal.describe_workflow(),\\n )\\n```\\n\\n \\n\\n\\n\\nYou need to add the secrets `HOST` and `NAMESPACE` under your typegraph name inside the `metatype.yaml` file. These secrets are important to connect with your temporal cluster and can be safely stored in the config file as shown below.\\n\\n
\\nmetatype.yaml\\n\\n```yaml\\ntypegate:\\n dev:\\n url: \\"http://localhost:7890\\"\\n username: admin\\n password: password\\n secrets:\\n example:\\n POSTGRES: \\"postgresql://postgres:password@postgres:5432/db\\"\\n MONGO: \\"mongodb://root:password@mongo:27017/db\\"\\n HOST: \\"http://localhost:7233\\"\\n NAMESPACE: \\"default\\"\\n```\\n\\n
\\n\\nYou need to add only the last two lines as the others are auto-generated. Note that secrets are defined under the `example` parent, which is the name of your typegraph. If the name doesn\'t match, you will face secret not found issues when deploying your typegraph.\\n\\nBefore deploying the above typegraph, you need to start the temporal server and the worker. You need to have [temporal](https://learn.temporal.io/getting_started/typescript/dev_environment/#set-up-a-local-temporal-service-for-development-with-temporal-cli) installed on your machine.\\n\\n
\\nBoot up temporal\\n\\nStart the temporal server.\\n\\n```bash\\ntemporal server start-dev\\n```\\n\\nStart the worker.\\n\\n\\n\\n\\n ```typescript npx ts-node src/worker.ts ```\\n\\n\\n```python python run_worker.py ```\\n\\n\\n
\\n\\nAfter booting the temporal server, run the command down below to get a locally spinning [typegate](/docs/reference/typegate) instance with your typegraph deployed.\\n\\n```bash\\nmeta dev\\n```\\n\\nAfter completing the above steps, you can access the web GraphQL client of the typegate at [`http://localhost:7890/example`](http://localhost:7890/example). Run this query inside the client to start your workflow.\\n\\n```graphql\\nmutation {\\n start(\\n workflow_id: \\"order-delivery-3\\"\\n task_queue: \\"order-delivery-queue\\"\\n args: [\\"order12\\"]\\n )\\n}\\n```\\n\\nAfter a successful run, you will get the following result which includes the `run_id` of the workflow which has just been started.\\n\\n\\n\\nYou can also check the temporal web UI to monitor your workflows and you should see a result similar to this one.\\n\\n\\n\\nYou can explore the [Temporal Runtime](/docs/reference/runtimes/temporal) for more info.\\n\\nThis wraps up the blog, thanks for reading until the end :)"},{"id":"/2024/08/26/python-on-webassembly","metadata":{"permalink":"/blog/2024/08/26/python-on-webassembly","editUrl":"https://github.com/metatypedev/metatype/tree/main/docs/metatype.dev/blog/2024-08-26-python-on-webassembly/index.mdx","source":"@site/blog/2024-08-26-python-on-webassembly/index.mdx","title":"Python on WebAssembly: How?","description":"Metatype\'s different language runtimes are nice, but integrating one is an entire story. Let\'s discover how we managed to implement one for Python.","date":"2024-08-26T00:00:00.000Z","tags":[],"readingTime":11.125,"hasTruncateMarker":false,"authors":[],"frontMatter":{},"unlisted":false,"prevItem":{"title":"Distributed execution flow paradigms","permalink":"/blog/2024/08/27/distributed-execution-flow-paradigms"},"nextItem":{"title":"Programmatic deployment (v0.4.x)","permalink":"/blog/2024/05/09/programmatic-deployment"}},"content":"Metatype\'s different language runtimes are nice, but integrating one is an entire story. Let\'s discover how we managed to implement one for Python.\\n\\n## Why?\\n\\nYou have probably heard of \\"Function as a Service\\" or FaaS. \\nIn simple terms, FaaS are platforms that allow users to run code in response to events without the hassle of managing the underlying infrastructure. \\nUsers submit their programs and the platform takes care of the rest including, usually, scaling, availability, and configuration.\\nAWS Lambda is one such example and FaaS as a whole are a popular implementation of the serverless model.\\n\\nMetatype has this model at heart with applications composed of small functions that respond to events like http requests and authorization checks. \\nThis is achieved through runtimes like the [`DenoRuntime`](/docs/reference/runtimes/deno) which implements a way to execute functions authored in Typescript using Web Workers as implemented by [Deno](https://docs.deno.com/runtime/manual/runtime/workers/) (not based on Deno Deploy). \\n\\n:::note\\nMetatype supports running multiple apps or typegraphs on a single deployed cluster but we\'re still in the kitchen on a hosted cloud solution. \\nSubscribe to the [blog](https://metatype.dev/blog/rss.xml) or the [Github](https://github.com/metatypedev/metatype) repository for updates.\\n:::\\n\\nImplementing the `DenoRuntime` was a very straightforward affair as the Typegate (the engine at the heart of Metatype) is primarily written in Typescript and runs on a slightly modified version of the Deno runtime.\\nWhat\'s more, JavaScript has single threaded and asynchronous semantics and the v8 engine that it commonly runs on is of very high-quality by all regards. \\nThese qualities lend themselves very well to the requirements of running a serverless platform like security (good sandboxing) and performance (low start-up latencies).\\nThis fact is reflected in the dominance of JavaScript in the serverless market though it doesn\'t hurt that it\'s also the most popular language in use today.\\n\\nAnother very popular language is Python; and its standard library can be quite resourceful for this type of use case.\\nHowever, as we shall see, integrating the Python runtime isn\'t as simple as integrating Deno.\\n\\n## What are the requirements?\\n\\nThere are a number of Python runtimes available but a set of extra factors limit what we can achieve.\\n\\n1. **Security**: functions should have limited access to the execution environment. Python doesn\'t have built-in features for sandboxing out of the box unlike Deno.\\n2. **Speed**: functions should run fast and with low latency. We\'re interested in metrics like cold-start latency and overhead of any cross process/system communication.\\n3. **User-friendliness**: functionalities provided in any of the languages supported by Metatype should, within reason, mirror each other and maintain a degree of uniformity. We support inline code snippets and external file references for `DenoRuntime` and this should be the case for Python as well.\\n4. **Interoperability**: functions running in Python will need to have access to other parts of the app running on the Typegate like being able to invoke other functions.\\n\\nThe Typegate is a TypeScript program with a bit of Rust sprinkled in. \\nIt runs as a traditional POSIX process. \\nThink Linux containers. \\nThis fact renders multi-processing, one of the readily apparent approaches, undesirable as it would require investing is robust worker process management and distribution schemes.\\nIt\'d be great if we could keep everything inside the Typegate process.\\n\\nOne solution that presents itself here is the [PyO3](https://pyo3.rs/) project which provide Rust bindings to different Python runtimes like CPython and PyPy.\\nIt\'d not only allow us to run Python code in-process but it also provide an easy way to expose the functions written in Rust to Python and vice-versa. \\nA good solution for the bidirectional communication needed for our interoperability requirements.\\n\\nUnfortunately, PyO3 doesn\'t have any provisions for sandboxing which is critical for our use case.\\nThis is where WebAssembly enters into the picture. \\nWebAssembly or Wasm for short is a executable bytecode format that originates from the web world and is designed for applications that run inside web-browsers. \\nThis use case shares most of our requirements and the Wasm world promises excellent sandboxing properties that should be perfect for our use case.\\nWe just have to find a way to run Python inside of it.\\n\\n## An aside on WASI \\n\\nWebAssembly System Interface (WASI) is an additional spec for the bytecode format that formalizes how Wasm programs access their host environment.\\nA lot like POSIX, this generally means OS capabilities such as file system access and networking but also, in it\'s latest iteration extends to any custom host defined functionality.\\n\\nWasm + WASI fits very well to our use case. As opposed to mutli-processing, we can instantiate, manage, and expose resources programmatically with ease.\\nAnd as luck would have it, some [community work](https://github.com/vmware-labs/webassembly-language-runtimes) has already been done at the time that led to wasm builds of CPython being available.\\n\\nUnfortunately, the WASI spec itself is a work in progress.\\nWhen we started out, only the limited \\"[preview1](https://github.com/WebAssembly/WASI/blob/main/legacy/preview1/docs.md)\\" implementation was supported by most runtimes.\\n`preview1` only focused on a standard set of host functionalities much like a `libc` implementation.\\nWell enough but any custom functionality meant having to rely on simple C ABI alike functions for _intra_-process communication.\\nIn order to make this work easier, we elected to bring PyO3 back into the picture so that all the IPC stuff is written in Rust, the language with the most support in the Wasm ecosystem today.\\n\\nAll in all, this would mean the python interpreter wrapped in a PyO3 based native API.\\nAn assembly that accepts user code as strings and then invokes them in response to events.\\nAll of this would be running inside a Wasm runtime, [WasmEdge](https://wasmedge.org/) in this case, which ticks of all of the sandboxing and security requirements.\\nThis approach is well described as the [Reactor pattern](https://wasmcloud.com/blog/webassembly-patterns-command-reactor-library#the-reactor-pattern), a common pattern used in Wasm land.\\n\\n\\"FIRST\\n\\n### File system access\\n\\nSince the PyO3 project doesn\'t support [statically linking](https://github.com/PyO3/pyo3/issues/416) the Python runtime, we\'ll need to find a way dynamically link `libpython`.\\nThankfully, Wasm does support [dynamic linking](https://github.com/WebAssembly/design/blob/main/DynamicLinking.md) and wasm builds of [`libpython`](https://github.com/vmware-labs/webassembly-language-runtimes/tree/main/python) are available curtsy of the WebAssembly Language Runtimes project. \\nBringing all of this together isn\'t as simple though as PyO3\'s tries to load `libpython` from certain _paths_, a concept that isn\'t exactly clearly defined in Wasm\'s post POSIX webtopia.\\n\\nOur first solution was to use [wasi-vfs](https://github.com/kateinoigakukun/wasi-vfs), a tool which allows you to embed a virtual file system, accessible through preview1 APIs, directly into your wasm binaries.\\nThis way, we could prepare a single wasm artifact that contains both the `libpython` build and the custom glue code.\\n\\nThis approach turned out to be quite hacky though and after encountering several issues, we ultimately decided to go with **preopens**.\\nPreopens are another virtual file-system solution where you map an actual file-system directory to a virtual directory visible to a running Wasm instance.\\nThis means we\'ll need to prepare the `libpython` Wasm file on disk before running the instance but it was an acceptable solution.\\nWe also use preopens to provide some of the user submitted code to our custom python runtime.\\n\\nThe following rust snippet demonstrates the preopens looked like in use:\\n\\n```rust\\nfn init_Python_vm() -> Result {\\n let preopens = vec![\\n // User script will be uploaded at ./src/Python which is virtually seen as /app\\n // Each script has access only to /app\\n \\"/app:./src/Python:readonly\\".to_owned()\\n ];\\n\\n // This follow the same idea as above, but for clarity\'s sake we decided to separate it\\n let pylib = PathBuf::from(\\"./vendor/libpython/usr/local/lib\\");\\n\\n // This is our wasm module reponsible for running Python scripts at runtime\\n // It assumes /app and libpython to be available in its world\\n let wasi_mod = PathBuf::from(\\"./build/Python-wasi-reactor.wasm\\");\\n\\n // Now we can instantiate the WASI module with all the configurations above\\n let rt = instantiate_custom_python_runtime(preopens, pylib, wasi_mod)?;\\n rt.run_func(None, \\"init_Python\\", params!())?;\\n\\n // ..\\n\\n Ok(rt)\\n}\\n```\\n\\n### WASI 0.2\\n\\nThe solution described above worked well to an extent but the limitations of preview1 and all the wrangling with PyO3 resulted in complexity that we were always ready to get rid of.\\nThis was exactly what we did after the Bytecode Alliance finalized [WASI 0.2](https://bytecodealliance.org/articles/WASI-0.2) back in January 2024 and with it, a slew of new opportunuties.\\n\\nWASI 0.2 introduces a whole new concept of components, wasm modules that come with pre-specifed interfaces using the [Wit](https://github.com/WebAssembly/component-model/blob/main/design/mvp/WIT.md) format and based on a whole new [ABI](https://github.com/WebAssembly/component-model/blob/main/design/mvp/CanonicalABI.md) to boot.\\nThese new capabilities suggest that it should possible to replace our PyO3 based glue code with the WASI based layer. \\nLet\'s see how.\\n\\nWe first used the new found WASI powers to implement support for Wasm based functions through the [`WasmRuntime`](/docs/reference/runtimes/wasm).\\nThis lead us to implement the [`wit_wire`](https://github.com/metatypedev/metatype/blob/2e692b9ae9e48b6e1a863130fc1bfbdd004cb631/src/wit/wit-wire.wit) protocol, a simple JSON based WIT interface that\'d be used by any wasm component that intenteds to run on the `WasmRuntime`.\\nSimple enough that it\'s reproduced down below in it\'s entirety.\\n\\n```wit\\npackage metatype:wit-wire;\\n\\n// what the host provides\\ninterface typegate-wire {\\n hostcall: func(op-name: string, json: string) -> result;\\n}\\n\\n// what\'s expected from the guest\\ninterface mat-wire {\\n\\n // init function called when we first make the component\\n init: func(args: init-args) -> result;\\n // general purpose event handler\\n handle: func(req: handle-req) -> result;\\n\\n type json-str = string;\\n\\n record init-args {\\n // the list of operations the application is expecting\\n // from this component\\n expected-ops: list\\n metatype-version: string,\\n }\\n\\n record mat-info {\\n op-name: string,\\n mat-title: string,\\n mat-data-json: string,\\n }\\n\\n record init-response {\\n ok: bool\\n }\\n\\n variant init-error {\\n version-mismatch(string),\\n unexpected-mat(mat-info),\\n other(string)\\n }\\n\\n record handle-req {\\n op-name: string,\\n in-json: json-str,\\n }\\n\\n variant handle-err {\\n no-handler,\\n in-json-err(string),\\n handler-err(string),\\n }\\n}\\n\\n// a world defines what interfaces get imported\\n// and exported\\nworld wit-wire {\\n import typegate-wire;\\n\\n export mat-wire;\\n}\\n\\n```\\n\\nSquint your eyes tight enough and the `wit_wire` protocol as implemented wasn\'t far off from what the PyO3 based glue code was doing in the previous implementation.\\nSpecifically, register a list of operations that the Typegate is expecting from the module and execute them for incoming event.\\nWe just need to add support for the operation metadata to contain extra items.\\nIn the case of the [`PythonRuntime`](/docs/reference/runtimes/python), this would be the Python code itself.\\n\\nNow that we have the `wit_wire` implementation taking care of bidirectional communication, we have little reason to keep the PyO3 based glue code around.\\nThis glue was doing a bit more than acting as a boundary though.\\nIt was also responsible for setting up the operating environment for the Python code.\\nFor example, we\'d need some kind of initialization to execute the user\'s Python snippets which are in free standing `lambda` form. \\nHow does one create components out of Python anyways?\\n\\n[componentize-py](https://github.com/bytecodealliance/componentize-py) is a tool authored by the Bytecode Alliance that allows you to produce WASI components that are authored in Python.\\nIt has code generation suite that emits guest bindings in Python for any WIT specification you feed it.\\nIt then takes your Python code written against these bindings and embeds them in a Wasm build of the Python interpreter to produce a component that supports the specified Wit.\\n\\nUnsurprisingly, componentize-py relies on PyO3 and preopens itself in addition to [component-init](https://github.com/dicej/component-init), a solution to pre-intialize components up to a certain point for improved startup latencies.\\nThis pre-intialization means we won\'t need to provide the actual preopens for the resulting component, baking the `libpython` object code directly into it as PyO3 will have dynamically loaded the object code by that point.\\nUltimately, this allows us to write all of our glue code in Python itself.\\n\\nWe still need a bit of Rust to support the `wit_wire` interface on the Typegate but this implementation is general across both the `PythonRuntime` and `WasmRuntime`.\\nWe\'d also moved to the [Wasmtime](https://wasmtime.dev/), also by Bytecode Alliance, for our wasm workloads at this point and their Rust bindings are a pleasure to use.\\nIt\'s all smooth sailing from here.\\n\\n## Cloudy skies?\\n\\nA final stumbling block for this approach was the many seconds Wasmtime spends cooking all your CPU cores when it compiles the fat wasm module that contains the Python interpreter, Pyo3 bindings and more.\\nThis happens because Wasmtime does\'t ([yet](https://github.com/bytecodealliance/rfcs/blob/main/accepted/wasmtime-baseline-compilation.md)) implement any schemes for tiered compilation, all code being greeted by their optimizing compiler, Cranelift.\\nAnd optimizations take time.\\nSure, you only pay this cost the first time you load the Python runtime module as Wasmtime has great support for caching including on-disk caching.\\nBut, 10+ second cold-starts, as measured on one developer\'s machine, are unacceptable in a system that primarily serves HTTP requests.\\nWhat to do?\\n\\nWasmtime has just the feature for this problem, [pre-compilation](https://docs.wasmtime.dev/cli-options.html#compile).\\nAhead-of-time compilation of wasm bytecode into a native instruction set.\\nSuch files are commonly given the `.cwasm` extesion, _c_ for compiled, and they are not a standalone executable but inteded to be run within Wasmtime\'s sandbox.\\nThis eliminates the compliation cost but the semantics of the source wasm bytecode and the runtime safe-guards means that this should be just as safe as JITting it (just-in-time compilation).\\nWe then statically embed this pre-compiled wasm artifact, after compressing it, in the Typegate binary removing the need for sidecar files while ensuring minimal cold-starts for our python workloads.\\nTo be concrete, this means _roughly_ around 200 ms of overhead for a cold function and 5 ms for a warm one.\\nGood enough.\\n\\nThis post describes the technical journey we took to arrive to the current implementation of the `PythonRuntime`. Hopefully, all details were clear enough and please direct any feedback, questions, and thoughts to the comments down below and our Github issues/discussion board."},{"id":"/2024/05/09/programmatic-deployment","metadata":{"permalink":"/blog/2024/05/09/programmatic-deployment","editUrl":"https://github.com/metatypedev/metatype/tree/main/docs/metatype.dev/blog/2024-05-09-programmatic-deployment/index.mdx","source":"@site/blog/2024-05-09-programmatic-deployment/index.mdx","title":"Programmatic deployment (v0.4.x)","description":"A new approach to deploying typegraphs has been introduced starting with version 0.4.0. This aims to facilitate the development of automation tools around the APIs you build within the Metatype ecosystem.","date":"2024-05-09T00:00:00.000Z","tags":[],"readingTime":3.405,"hasTruncateMarker":false,"authors":[],"frontMatter":{},"unlisted":false,"prevItem":{"title":"Python on WebAssembly: How?","permalink":"/blog/2024/08/26/python-on-webassembly"},"nextItem":{"title":"The Node/Deno SDK is now available","permalink":"/blog/2023/11/27/node-compatibility"}},"content":"import SDKTabs from \\"@site/src/components/SDKTabs\\";\\nimport TabItem from \\"@theme/TabItem\\";\\nimport UpgradePythonSDK from \\"../../shared/upgrade/python-sdk.mdx\\";\\nimport UpgradeTsSDK from \\"../../shared/upgrade/typescript-sdk.mdx\\";\\n\\n\\nA new approach to deploying typegraphs has been introduced starting with version 0.4.0. This aims to facilitate the development of automation tools around the APIs you build within the Metatype ecosystem.\\n\\n## What has changed?\\n\\nBefore v0.4.x, we had to entirely rely on the [meta cli](/docs/reference/meta-cli) to deploy typegraphs to a typegate instance.\\n\\nThis is no longer the case, as all core logic has been moved to the TypeScript/Python typegraph SDKs, both of which share the same WebAssembly-based **typegraph-core** behind the scenes. This provides some degree of assurance that you will have nearly identical experiences with each SDK.\\n\\n## What are the use-cases?\\n\\nSince typegraphs can be written using the programming language your preferred SDK is based on, you can dynamically create typegraphs with ease.\\n\\nThe missing piece was having an interface natively backed inside the SDK for doing deployment programmatically.\\n\\n### Programmatic deployment\\n\\n### Initial setup\\n\\nJust like any other dependency in your favorite programming language, each SDKs can be installed with your favorite package manager.\\n\\nYou can use one of the commands below to get started with the latest available version.\\n\\n\\n \\n \\n \\n \\n \\n \\n\\n\\n#### Configuration\\n\\nThis is analoguous to the yaml configuration file when you are using [meta cli](/docs/reference/meta-cli).\\n\\nIt\'s the place where you tell which typegate you want to deploy to, how you want the artifacts to be resolved, among other settings.\\n\\n\\n \\n\\n```python\\nconfig: TypegraphDeployParams = TypegraphDeployParams(\\n typegate=TypegateConnectionOptions(url=\\"\\", auth=BasicAuth(\\"\\", \\"\\")),\\n typegraph_path=os.path.join(cwd, \\"path-to-typegraph\\"),\\n prefix=\\"\\",\\n secrets={},\\n migrations_dir=path.join(\\"prisma-migrations\\", example.name),\\n migration_actions=None,\\n default_migration_action=MigrationAction(\\n apply=True,\\n reset=True, # allow destructive migrations\\n create=True,\\n ),\\n )\\n```\\n\\n \\n \\n\\n```typescript\\nconst config = {\\n typegate: {\\n url: \\"\\",\\n auth: new BasicAuth(\\"\\", \\"\\"),\\n },\\n typegraphPath: path.join(cwd, \\"path-to-typegraph.ts\\"),\\n prefix: \\"\\",\\n secrets: { POSTGRES: \\"\\" },\\n migrationsDir: path.join(\\"prisma-migrations\\", tg.name),\\n defaultMigrationAction: {\\n create: true,\\n reset: true, // allow destructive migrations\\n },\\n};\\n```\\n\\n \\n\\n\\n\\n### Deploy/remove\\n\\nNow, picture this, you have a lot of typegraphs and one or more typegate instance(s) running, you can easily make small scripts that does any specific job you want.\\n\\n```typescript\\n// ..\\nimport { tgDeploy, tgRemove } from \\"@typegraph/sdk/tg_deploy.js\\";\\n// ..\\n\\nconst BASIC_AUTH = loadMyAuthsFromSomeSource();\\nconst TYPEGATE_URL = \\"...\\";\\n\\nexport async function getTypegraphs() {\\n // Suppose we have these typegraphs..\\n // Let\'s enumerate them like this to simplify\\n return [\\n {\\n tg: await import(\\"path/to/shop-finances\\"),\\n location: \\"path/to/shop-finances.ts\\",\\n },\\n {\\n tg: await import(\\"path/to/shop-stats\\"),\\n location: \\"path/to/shop-stats.ts\\",\\n },\\n ];\\n}\\n\\nexport function getConfig(tgName: string, tgLocation: string) {\\n // Note: You can always develop various ways of constructing the configuration,\\n // like loading it from a file.\\n return {\\n typegate: {\\n url: \\"\\",\\n auth: new BasicAuth(\\"\\", \\"\\"),\\n },\\n typegraphPath: path.join(cwd, \\"path-to-typegraph.ts\\"),\\n prefix: \\"\\",\\n secrets: { POSTGRES: \\"\\" },\\n migrationsDir: path.join(\\"prisma-migrations\\", tg.name),\\n defaultMigrationAction: {\\n create: true,\\n reset: true, // allow destructive migrations\\n },\\n };\\n}\\n\\nexport async function deployAll() {\\n const typegraphs = await getTypegraphs();\\n for (const { tg, location } of typegraphs) {\\n try {\\n const config = getConfig(tg.name, location);\\n // use tgDeploy to deploy typegraphs, it will contain the response from typegate\\n const { typegate } = await tgDeploy(tg, config);\\n const selection = typegate?.data?.addTypegraph;\\n if (selection) {\\n const { messages } = selection;\\n console.log(messages.map(({ text }) => text).join(\\"\\\\n\\"));\\n } else {\\n throw new Error(JSON.stringify(typegate));\\n }\\n } catch (e) {\\n console.error(\\"[!] Failed deploying\\", tg.name);\\n console.error(e);\\n }\\n }\\n}\\n\\nexport async function undeployAll() {\\n const typegraphs = await getTypegraphs();\\n for (const { tg } of typegraphs) {\\n try {\\n // use tgRemove to remove typegraphs\\n const { typegate } = await tgRemove(\\"\\", {\\n baseUrl: TYPEGATE_URL,\\n auth: BASIC_AUTH,\\n });\\n console.log(typegate);\\n } catch (e) {\\n console.error(\\"Failed removing\\", tg.name);\\n console.error(e);\\n }\\n }\\n}\\n```\\n\\n### Going beyond\\n\\nWith these new additions, you can automate virtually anything programmatically on the typegraph side. Starting from having highly dynamic APIs to providing ways to deploy and configure them, you can even build a custom framework around the ecosystem!\\n\\nPlease tell us what you think and report any issues you found on [Github](https://github.com/metatypedev/metatype/issues).\\n\\n:::info Notes\\n\\nYou can check the [Programmatic deployment](/docs/guides/programmatic-deployment) reference page for more information.\\n\\n:::"},{"id":"/2023/11/27/node-compatibility","metadata":{"permalink":"/blog/2023/11/27/node-compatibility","editUrl":"https://github.com/metatypedev/metatype/tree/main/docs/metatype.dev/blog/2023-11-27-node-compatibility/index.mdx","source":"@site/blog/2023-11-27-node-compatibility/index.mdx","title":"The Node/Deno SDK is now available","description":"We are happy to announce that we have redesigned our SDKs to support Node/Deno and facilitate the integration of future languages. Most of the typegraph SDK is now written in Rust and shaped around a core interface running in WebAssembly.","date":"2023-11-27T00:00:00.000Z","tags":[],"readingTime":1.7,"hasTruncateMarker":false,"authors":[],"frontMatter":{},"unlisted":false,"prevItem":{"title":"Programmatic deployment (v0.4.x)","permalink":"/blog/2024/05/09/programmatic-deployment"},"nextItem":{"title":"Programmable glue for developers","permalink":"/blog/2023/06/18/programmable-glue"}},"content":"We are happy to announce that we have redesigned our SDKs to support Node/Deno and facilitate the integration of future languages. Most of the [typegraph SDK](/docs/reference/typegraph) is now written in Rust and shaped around a core interface running in WebAssembly.\\n\\n## Meet `wit`\\n\\nIn the realm of WebAssembly, the [wit-bindgen](https://github.com/bytecodealliance/wit-bindgen) project emerges as the most mature tool to create and maintain the language bindings for WebAssembly modules. This tool introduces WIT (WebAssembly Interface Types) as an Interface Definition Language (IDL) to describe the imports, exports, and capabilities of WebAssembly components seamlessly.\\n\\nFor example, Metatype implements the reactor pattern to handle requests as they come and delegate part of their execution in correct WASM runtime. The wit-bindgen helps there to define the interfaces between the guest (the Metatype runtime) and the host (the typegate) to ensure the correct serialization of the payloads. The `wit` definition could look like this:\\n\\n```\\npackage metatype:wit-wire;\\n\\ninterface typegate-wire {\\n hostcall: func(op-name: string, json: string) -> result;\\n}\\n\\ninterface mat-wire {\\n record handle-req {\\n op-name: string,\\n in-json: string,\\n }\\n\\n handle: func(req: handle-req) -> result;\\n}\\n\\nworld wit-wire {\\n import typegate-wire;\\n\\n export mat-wire;\\n}\\n```\\n\\nThe `wit` file is then used to generate the bindings for the host and the guest in Rust, TypeScript, Python, and other languages. The host bindings are used in the typegate to call the WASM runtime, and the guest bindings are used in the WASM runtime to call the typegate.\\n\\n## Install the v0.2.x series\\n\\nThe documentation contains now examples for Node and Deno.\\n\\n### Upgrade with Node\\n\\n```bash\\nnpm install @typegraph/sdk\\nmeta new --template node .\\n```\\n\\n### Upgrade with Deno\\n\\n```bash\\nmeta new --template deno .\\n```\\n\\n```typescript\\nimport { typegraph } from \\"npm:@typegraph/sdk/index.js\\";\\n```\\n\\n### Upgrade with Python\\n\\n```python\\npip3 install --upgrade typegraph\\npoetry add typegraph@latest\\n```\\n\\n## Give us feedback!\\n\\nThis new release enables us to provide a consistent experience across all languages and reduce the work to maintain the existing Python SDK.\\n\\nAs always, report issues and let us know what you think on [GitHub](https://github.com/metatypedev/metatype/discussions)."},{"id":"/2023/06/18/programmable-glue","metadata":{"permalink":"/blog/2023/06/18/programmable-glue","editUrl":"https://github.com/metatypedev/metatype/tree/main/docs/metatype.dev/blog/2023-06-18-programmable-glue/index.mdx","source":"@site/blog/2023-06-18-programmable-glue/index.mdx","title":"Programmable glue for developers","description":"We are introducing Metatype, a new project that allows developers to build modular and strongly typed APIs using typegraph as a programmable glue.","date":"2023-06-18T00:00:00.000Z","tags":[],"readingTime":1.295,"hasTruncateMarker":false,"authors":[],"frontMatter":{},"unlisted":false,"prevItem":{"title":"The Node/Deno SDK is now available","permalink":"/blog/2023/11/27/node-compatibility"},"nextItem":{"title":"Emulating your server nodes locally","permalink":"/blog/2023/03/15/emulating-servers"}},"content":"import { CompareLandscape } from \\"@site/src/components/CompareLandscape\\";\\nimport Metatype from \\"@site/shared/metatype-intro.mdx\\";\\nimport TGExample from \\"@site/src/components/TGExample\\";\\n\\n\\nWe are introducing Metatype, a new project that allows developers to build modular and strongly typed APIs using typegraph as a programmable glue.\\n\\n## What is Metatype?\\n\\n\\n\\n## What are virtual graphs?\\n\\nTypegraphs are a declarative way to expose all APIs, storage and business logic of your stack as a single graph. They take inspiration from domain-driven design principles and in the idea that the relation between of the data is as important as data itself, even though they might be in different locations or shapes.\\n\\n\\n\\nThese elements can then be combined and composed together similarly on how you would compose web components to create an interface in modern frontend practices. This allows developers to build modular and strongly typed APIs using typegraph as a programmable glue.\\n\\n## Where does this belong in the tech landscape?\\n\\nBefore Metatype, there was a gap in the technological landscape for a solution that specifically addressed the transactional, short-lived use cases. While there were existing tools for analytical or long-running use cases, such as Trino and Temporal, there was no generic engine for handling transactional, short-lived tasks.\\n\\n \\n\\n## Give it a try!\\n\\nLet us know what you think! Metatype is open source and we welcome any feedback or contributions. The community primarily lives on [GitHub](https://github.com/metatypedev/metatype).\\n\\n:::info Next steps\\n\\n[Build your first typegraph](/docs/tutorials/metatype-basics) or read more about the [concepts behind Metatype](/docs/concepts/mental-model).\\n\\n:::"},{"id":"/2023/03/15/emulating-servers","metadata":{"permalink":"/blog/2023/03/15/emulating-servers","editUrl":"https://github.com/metatypedev/metatype/tree/main/docs/metatype.dev/blog/2023-03-15-emulating-servers/index.mdx","source":"@site/blog/2023-03-15-emulating-servers/index.mdx","title":"Emulating your server nodes locally","description":"Introducing the Embedded Typegate","date":"2023-03-15T00:00:00.000Z","tags":[],"readingTime":3.07,"hasTruncateMarker":false,"authors":[],"frontMatter":{},"unlisted":false,"prevItem":{"title":"Programmable glue for developers","permalink":"/blog/2023/06/18/programmable-glue"}},"content":"import BlogIntro from \\"@site/src/components/BlogIntro\\";\\nimport UpgradeMetatype from \\"../../shared/upgrade/index.mdx\\";\\n\\n\\n\\n\\n## Introducing the Embedded Typegate\\n\\nThe embedded typegate is a feature that comes with the [Meta CLI](/docs/reference/meta-cli) which provides the option of spinning a typegate instance from the CLI with minimum configurations and installations needed from the developer. All that is required to access the _Embedded Typegate_ is to install _Meta CLI_. The spawned typegate instance behaves similarly to cloud-deployed typegates.\\n\\n## The motive\\n\\nThere are more than a couple of reasons why a developer would be tempted to use an emedded typegate. While developers can start a typegate instance using docker compose, the developer needs to install docker as a dependency to run the typegate container. Even though docker is familiar among many developers, it can sometimes be tricky and unbeknownst to some developers. We at metatype highly value the developer experience and one reason for adding the _embedded typegate_ feature to the _Meta CLI_ is for users to have a smooth experience with our system by providing a docker compose free experience.\\nThis feature provides a great utility for developers to author and test typegraphs in their local machine before deploying them to production level typegate instances on the cloud.\\nAdditionally, developers need not concern themselves with deployment configurations which are needed only during deployment. The only need to focus their energy and time in developing the right application and easily test them on _embedded typegate_ running from the terminal. To add more to what is said, as the typegate engine keeps evolving, users will be abstracted away from the different configurations which might be added on the future. The _Meta CLI_ will abstract much of what\'s not needed in a dev environment. Thus, leaving less headaches to developers on new changes.\\nUltimately, The _embedded typegate_ is designed to be a good dev environment friendly tool which faciliates development time.\\n\\n## Quick First hand example\\n\\n### Install the v0.3.x series\\n\\nEither of the two [Typegraph](/docs/reference/typegraph) SDKs are needed to author typegraphs. For this example, the node SDK will be used.\\n\\nFirst, make sure the _Meta CLI_ is installed.\\n\\n```shell\\ncurl -fsSL https://raw.githubusercontent.com/metatypedev/metatype/main/installer.sh | bash\\n```\\n\\nNext, create a new node project using this command.\\n\\n```shell\\nmeta new --template node\\n```\\n\\nThe above command will create a sample typegraph which you can use to test the embedded typegate.\\n\\nNow, you need to install the typegraph SDK by running the command down below. The previous command generates a `package.json` with the SDK specified as a dependency.\\n\\n```shell\\nnpm install\\n```\\n\\nBefore deploying the typegraph to the embedded typegate, Run the following commands below.\\n\\n```shell\\nmeta dev\\n```\\n\\nNow that there is running instance of a typegate, you can deploy the example typegraph. From another terminal, run the command below.\\n\\n```shell\\nmeta deploy -f api/example.ts --allow-dirty --create-migration --target dev --gate http://localhost:7890\\n```\\n\\nThe typegate runs on port 7890 by default. If you access [http://localhost:7890/example](http://localhost:7890/example) on your browser, you can see an GraphQL interface to interact with the deployed typegraph. You can test the example typegraph using the following graphql query below.\\n\\n```graphql\\nquery {\\n multilpy(first: 3, second: 5)\\n}\\n```\\n\\n\\n\\n## Learn more about Metatype\\n\\nWanna dive deep into the basics of _Metaype_? check our interactive [tutorial](/docs/tutorials/metatype-basics) revolving around the core features of the system."}]}}')}}]); \ No newline at end of file diff --git a/assets/js/cd86e9b3.23614bdc.js b/assets/js/cd86e9b3.a90c8e17.js similarity index 99% rename from assets/js/cd86e9b3.23614bdc.js rename to assets/js/cd86e9b3.a90c8e17.js index e0cd8c8730..9203eff7b2 100644 --- a/assets/js/cd86e9b3.23614bdc.js +++ b/assets/js/cd86e9b3.a90c8e17.js @@ -1 +1 @@ -(self.webpackChunkwebsite=self.webpackChunkwebsite||[]).push([[4947],{98143:(e,n,t)=>{"use strict";t.r(n),t.d(n,{assets:()=>c,contentTitle:()=>l,default:()=>u,frontMatter:()=>o,metadata:()=>d,toc:()=>p});var r=t(86070),s=t(25710),i=t(65671),a=t(7871);const o={},l=void 0,d={id:"reference/metagen/index",title:"index",description:"/typegrap/typegraphh---",source:"@site/docs/reference/metagen/index.mdx",sourceDirName:"reference/metagen",slug:"/reference/metagen/",permalink:"/docs/reference/metagen/",draft:!1,unlisted:!1,editUrl:"https://github.com/metatypedev/metatype/tree/main/docs/metatype.dev/docs/reference/metagen/index.mdx",tags:[],version:"current",frontMatter:{},sidebar:"docs",previous:{title:"Changelog",permalink:"/docs/reference/changelog"},next:{title:"Features overview",permalink:"/docs/concepts/features-overview/"}},c={},p=[{value:"/typegrap/typegraphh---\nsidebar_position: 50",id:"typegraptypegraphh---sidebar_position-50",level:2},{value:"Access through CLI",id:"access-through-cli",level:2},{value:"Access through SDK",id:"access-through-sdk",level:2},{value:"Generators",id:"generators",level:2},{value:"client_ts",id:"client_ts",level:3},{value:"client_py",id:"client_py",level:3},{value:"client_rs",id:"client_rs",level:3},{value:"fdk_typescript",id:"fdk_typescript",level:3},{value:"fdk_python",id:"fdk_python",level:3},{value:"fdk_rust",id:"fdk_rust",level:3}];function h(e){const n={a:"a",admonition:"admonition",code:"code",h1:"h1",h2:"h2",h3:"h3",li:"li",p:"p",pre:"pre",strong:"strong",table:"table",tbody:"tbody",td:"td",th:"th",thead:"thead",tr:"tr",ul:"ul",...(0,s.R)(),...e.components},{Details:o}=n;return o||function(e,n){throw new Error("Expected "+(n?"component":"object")+" `"+e+"` to be defined: you likely forgot to import, pass, or provide it.")}("Details",!0),(0,r.jsxs)(r.Fragment,{children:[(0,r.jsx)(n.h2,{id:"typegraptypegraphh---sidebar_position-50",children:"/typegrap/typegraphh---\nsidebar_position: 50"}),"\n","\n",(0,r.jsx)(n.h1,{id:"metagen",children:"Metagen"}),"\n",(0,r.jsx)(n.admonition,{title:"Beta",type:"warning",children:(0,r.jsx)(n.p,{children:"The following feature is not yet stable."})}),"\n",(0,r.jsx)(n.p,{children:"Metagen is a code-generator suite that contains implementations that help with development on the Metatype platform. 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We configure the generators through the ",(0,r.jsx)(n.a,{href:"/docs/reference/meta-cli/configuration-file",children:"standard configuration file"})," under the metagen key."]}),"\n",(0,r.jsx)(n.pre,{children:(0,r.jsx)(n.code,{className:"language-yaml",children:'typegates:\n # bla bla\n\ntypegraphs:\n # bla bla\n\nmetagen:\n targets:\n main:\n # generator to use\n - generator: fdk_rust\n # path to generate to\n path: ./bff/\n # typegraph path to use\n typegraph_path: ./typegraphs/svc-bff.ts\n # we can have multiple generators per target\n - generator: fdk_rust\n path: ./telemetry/\n typegraph_path: ./typegraphs/svc-telemetry.ts\n # generators might have custom keys\n stubbed_runtimes: ["wasm_wire", "deno"]\n # more than one targets avail if you need them\n iter:\n - generator: client_ts\n path: ./next_app/\n # name of typegraph to read from typegate\n typegraph: svc_bff\n'})}),"\n",(0,r.jsx)(n.p,{children:"This allows us to invoke the targets from the CLI."}),"\n",(0,r.jsx)(n.pre,{children:(0,r.jsx)(n.code,{className:"language-sh",children:"meta cli gen main\n"})}),"\n",(0,r.jsxs)(n.p,{children:["This will resolve the requisite typegraphs, serialize as needed and put the resulting files at the appropriate locations. 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i(e){let{python:n,typescript:t,rust:i,...a}=e;const o=[n&&{content:n.content,codeLanguage:"python",codeFileUrl:n.path},t&&{content:t.content,codeLanguage:"typescript",codeFileUrl:t.path},i&&{content:i.content,codeLanguage:"rust",codeFileUrl:i.path}].filter((e=>!!e));return(0,s.jsx)(r.A,{code:0==o.length?void 0:o,...a})}},14037:e=>{e.exports={content:'@typegraph(\n)\ndef metagen_deno(g: Graph):\n idv3 = t.struct(\n {\n "title": t.string(),\n "artist": t.string(),\n "releaseTime": t.datetime(),\n "mp3Url": t.uri(),\n # explicit type names help when generating code\n }\n ).rename("idv3")\n deno = DenoRuntime()\n\n g.expose(\n Policy.public(),\n remix=deno.import_(\n idv3,\n idv3,\n module="./metagen/ts/remix.ts",\n deps=["./metagen/ts/fdk.ts"],\n name="remix_track",\n ).rename("remix_track"), # explicit names help\n )',path:"../examples/typegraphs/metagen-deno.py"}},62292:e=>{e.exports={content:'await typegraph(\n {\n name: "metagen-py",\n },\n (g) => {\n const idv3 = t\n .struct({\n title: t.string(),\n artist: t.string(),\n releaseTime: t.datetime(),\n mp3Url: t.uri(),\n // explicit type names help when generating code\n })\n .rename("idv3");\n\n const python = new PythonRuntime();\n\n g.expose(\n {\n remix: python\n .import(idv3, idv3, {\n module: "./metagen/py/remix.py",\n deps: ["./metagen/py/remix_types.py"],\n name: "remix_track",\n })\n .rename("remix_track"), // explicit names help\n },\n Policy.public()\n );\n }\n);',path:"../examples/typegraphs/metagen-py.ts"}},28054:e=>{e.exports={content:'@typegraph(\n)\ndef metagen_rs(g: Graph):\n idv3 = t.struct(\n {\n "title": t.string(),\n "artist": t.string(),\n "releaseTime": t.datetime(),\n "mp3Url": t.uri(),\n # explicit type names help when generating code\n }\n ).rename("idv3")\n\n # the wire flavour is availible through a static\n # constructor\n wasm = WasmRuntime.wire("metagen/rust.wasm")\n\n g.expose(\n Policy.public(),\n remix=wasm.handler(\n idv3,\n idv3,\n name="remix_track",\n ).rename("remix_track"), # explicit names help\n )',path:"../examples/typegraphs/metagen-rs.py"}},86016:e=>{e.exports={content:'await typegraph(\n {\n name: "metagen-rs",\n },\n (g) => {\n const idv3 = t\n .struct({\n title: t.string(),\n artist: t.string(),\n releaseTime: t.datetime(),\n mp3Url: t.uri(),\n // explicit type names help when generating code\n })\n .rename("idv3");\n\n // the wire flavour is availible through a static\n // constructor\n const wasm = WasmRuntime.wire("metagen/rust.wasm");\n\n g.expose(\n {\n remix: wasm\n .handler(\n idv3,\n idv3,\n {\n name: "remix_track",\n }\n // the traits will map to the name of the materializer\n // and also the the name of the handler mentioned above\n )\n .rename("remix_track"),\n },\n Policy.public()\n );\n }\n);',path:"../examples/typegraphs/metagen-rs.ts"}},7797:e=>{e.exports={content:'import os\nfrom typegraph.graph.metagen import Metagen\n\n\n@typegraph(\n)\ndef metagen_sdk(g: Graph):\n idv3 = t.struct(\n {\n "title": t.string(),\n "artist": t.string(),\n "releaseTime": t.datetime(),\n "mp3Url": t.uri(),\n }\n ).rename("idv3")\n deno = DenoRuntime()\n\n g.expose(\n Policy.public(),\n remix=deno.import_(\n idv3,\n idv3,\n module="./metagen/ts/remix.ts",\n deps=["./metagen/ts/fdk.ts"],\n name="remix_track",\n ).rename("remix_track"),\n )\n\n\nif __name__ == "__main__" and False:\n metagen = Metagen(\n # the workspace root that our config is relative to\n os.path.dirname(os.path.abspath(__file__)),\n # the rest is pretty similar to the CLI config\n {\n "targets": {\n "main": [\n {\n "generator": "fdk_typescript",\n "typegraph_path": __file__,\n "path": "funcs/",\n },\n ],\n },\n },\n )\n tg = metagen_sdk()\n # dry_run doesn\'t write to disk\n items = metagen.dry_run(tg, "main", None)',path:"../examples/typegraphs/metagen-sdk.py"}},19507:e=>{e.exports={content:'import { Metagen } from "@typegraph/sdk/metagen.ts";\n\n// get typegraph desc here\nconst tg = await typegraph(\n {\n name: "metagen-sdk",\n },\n (g) => {\n const idv3 = t\n .struct({\n title: t.string(),\n artist: t.string(),\n releaseTime: t.datetime(),\n mp3Url: t.uri(),\n })\n .rename("idv3");\n\n const deno = new DenoRuntime();\n\n g.expose(\n {\n remix: deno\n .import(idv3, idv3, {\n module: "./metagen/ts/remix.ts",\n deps: ["./metagen/ts/fdk.ts"],\n name: "remix_track",\n })\n .rename("remix_track"),\n },\n Policy.public(),\n );\n },\n);\n\nif (false) {\n const myPath = import.meta.url.replace("file://", "");\n const metagen = new Metagen(\n // the workspace root that our config is relative to\n myPath + "/..",\n // this rest of the config is similmilar to the CLI config\n {\n targets: {\n main: [\n {\n generator: "fdk_typescript",\n typegraph_path: myPath,\n path: "funcs/",\n },\n ],\n },\n },\n );\n // dry_run doesn\'t write to disk\n metagen.dryRun(tg, "main");\n}',path:"../examples/typegraphs/metagen-sdk.ts"}},28434:e=>{e.exports={content:'from .remix_types import typed_remix_track, Idv3\n\n\n# the following decorator makes sure your function\n# adheres to the function types from the typegraph\n@typed_remix_track\ndef remix_track(inp: Idv3) -> Idv3:\n return Idv3(\n title=f"{inp.title} (Remix)",\n artist=f"{inp.artist} + DJ Cloud",\n releaseTime=inp.releaseTime,\n mp3Url="https://mp3.url/remix1",\n )',path:"../examples/typegraphs/metagen/py/remix.py"}},95696:e=>{e.exports={content:'from types import NoneType\nfrom typing import Callable, List, Union, get_origin, ForwardRef, Any\nfrom dataclasses import dataclass, asdict, fields\n\nFORWARD_REFS = {}\n\n\nclass Struct:\n def repr(self):\n return asdict(self)\n\n @staticmethod\n def try_new(dt_class, val: Any):\n # Object\n ftypes = {f.name: f.type for f in fields(dt_class)}\n attrs = {}\n for f in val:\n fval = val[f]\n ftype = ftypes[f]\n serialized = False\n # Union\n if get_origin(ftype) is Union:\n try:\n attrs[f] = Struct.try_union(ftype.__args__, fval)\n serialized = True\n except Exception:\n pass\n # List\n elif get_origin(ftype) is list:\n try:\n attrs[f] = Struct.try_typed_list(ftype.__args__, fval)\n serialized = True\n except Exception:\n pass\n # Any\n if not serialized:\n if isinstance(ftype, str) and ftype in FORWARD_REFS:\n klass = FORWARD_REFS[ftype]\n attrs[f] = Struct.new(klass, fval)\n else:\n attrs[f] = Struct.new(ftype, fval)\n return dt_class(**attrs)\n\n @staticmethod\n def try_typed_list(tpe: Any, items: Any):\n hint = tpe.__args__[0]\n klass = (\n FORWARD_REFS[hint.__forward_arg__] if isinstance(hint, ForwardRef) else hint\n )\n return [Struct.new(klass, v) for v in items]\n\n @staticmethod\n def try_union(variants: List[Any], val: Any):\n errors = []\n for variant in variants:\n try:\n if variant is NoneType:\n if val is None:\n return None\n else:\n continue\n if get_origin(variant) is list:\n if isinstance(val, list):\n return Struct.try_typed_list(variant, val)\n else:\n continue\n klass = FORWARD_REFS[variant.__forward_arg__]\n return Struct.try_new(klass, val)\n except Exception as e:\n errors.append(str(e))\n raise Exception("\\n".join(errors))\n\n @staticmethod\n def new(dt_class: Any, val: Any):\n try:\n return Struct.try_new(dt_class, val)\n except Exception:\n return val\n\n\n@dataclass\nclass Idv3(Struct):\n title: str\n artist: str\n releaseTime: str\n mp3Url: str\n\n\nFORWARD_REFS["Idv3"] = Idv3\n\n\ndef __repr(value: Any):\n if isinstance(value, Struct):\n return value.repr()\n return value\n\n\ndef typed_remix_track(user_fn: Callable[[Idv3], Idv3]):\n def exported_wrapper(raw_inp):\n inp: Idv3 = Struct.new(Idv3, raw_inp)\n out: Idv3 = user_fn(inp)\n if isinstance(out, list):\n return [__repr(v) for v in out]\n return __repr(out)\n\n return exported_wrapper',path:"../examples/typegraphs/metagen/py/remix_types.py"}},86496:e=>{e.exports={content:'// This file was @generated by metagen and is intended\n// to be generated again on subsequent metagen runs.\n#![cfg_attr(rustfmt, rustfmt_skip)]\n\n// gen-static-start\n#![allow(dead_code)]\n\npub mod wit {\n wit_bindgen::generate!({\n pub_export_macro: true,\n \n inline: "package metatype:wit-wire;\n\ninterface typegate-wire {\n hostcall: func(op-name: string, json: string) -> result;\n}\n\ninterface mat-wire {\n type json-str = string;\n\n record mat-info {\n op-name: string,\n mat-title: string,\n mat-hash: string,\n mat-data-json: string,\n }\n\n record init-args {\n metatype-version: string,\n expected-ops: list\n }\n\n record init-response {\n ok: bool\n }\n\n variant init-error {\n version-mismatch(string),\n unexpected-mat(mat-info),\n other(string)\n }\n\n init: func(args: init-args) -> result;\n\n record handle-req {\n op-name: string,\n in-json: json-str,\n }\n\n variant handle-err {\n no-handler,\n in-json-err(string),\n handler-err(string),\n }\n\n handle: func(req: handle-req) -> result;\n}\n\nworld wit-wire {\n import typegate-wire;\n\n export mat-wire;\n}\n"\n });\n}\n\nuse std::cell::RefCell;\nuse std::collections::HashMap;\n\nuse wit::exports::metatype::wit_wire::mat_wire::*;\nuse wit::metatype::wit_wire::typegate_wire::hostcall;\n\npub type HandlerFn = Box Result>;\n\npub struct ErasedHandler {\n mat_id: String,\n mat_trait: String,\n mat_title: String,\n handler_fn: HandlerFn,\n}\n\npub struct MatBuilder {\n handlers: HashMap,\n}\n\nimpl MatBuilder {\n pub fn new() -> Self {\n Self {\n handlers: Default::default(),\n }\n }\n\n pub fn register_handler(mut self, handler: ErasedHandler) -> Self {\n self.handlers.insert(handler.mat_trait.clone(), handler);\n self\n }\n}\n\npub struct Router {\n handlers: HashMap,\n}\n\nimpl Router {\n pub fn from_builder(builder: MatBuilder) -> Self {\n Self {\n handlers: builder.handlers,\n }\n }\n\n pub fn init(&self, args: InitArgs) -> Result {\n static MT_VERSION: &str = "0.5.0-rc.1";\n if args.metatype_version != MT_VERSION {\n return Err(InitError::VersionMismatch(MT_VERSION.into()));\n }\n for info in args.expected_ops {\n let mat_trait = stubs::op_to_trait_name(&info.op_name);\n if !self.handlers.contains_key(mat_trait) {\n return Err(InitError::UnexpectedMat(info));\n }\n }\n Ok(InitResponse { ok: true })\n }\n\n pub fn handle(&self, req: HandleReq) -> Result {\n let mat_trait = stubs::op_to_trait_name(&req.op_name);\n let Some(handler) = self.handlers.get(mat_trait) else {\n return Err(HandleErr::NoHandler);\n };\n let cx = Ctx {};\n (handler.handler_fn)(&req.in_json, cx)\n }\n}\n\npub type InitCallback = fn() -> anyhow::Result;\n\nthread_local! {\n pub static MAT_STATE: RefCell = panic!("MAT_STATE has not been initialized");\n}\n\npub struct Ctx {}\n\nimpl Ctx {\n pub fn gql(\n &self,\n query: &str,\n variables: impl Into,\n ) -> Result\n where\n O: serde::de::DeserializeOwned,\n {\n match hostcall(\n "gql",\n &serde_json::to_string(&serde_json::json!({\n "query": query,\n "variables": variables.into(),\n }))?,\n ) {\n Ok(json) => Ok(serde_json::from_str(&json[..])?),\n Err(json) => Err(GraphqlRunError::HostError(serde_json::from_str(&json)?)),\n }\n }\n}\n\n#[derive(Debug)]\npub enum GraphqlRunError {\n JsonError(serde_json::Error),\n HostError(serde_json::Value),\n}\n\nimpl std::error::Error for GraphqlRunError {}\n\nimpl From for GraphqlRunError {\n fn from(value: serde_json::Error) -> Self {\n Self::JsonError(value)\n }\n}\n\nimpl std::fmt::Display for GraphqlRunError {\n fn fmt(&self, f: &mut std::fmt::Formatter<\'_>) -> std::fmt::Result {\n match self {\n GraphqlRunError::JsonError(msg) => write!(f, "json error: {msg}"),\n GraphqlRunError::HostError(serde_json::Value::Object(map))\n if map.contains_key("message") =>\n {\n write!(f, "host error: {}", map["message"])\n }\n GraphqlRunError::HostError(val) => write!(f, "host error: {val:?}"),\n }\n }\n}\n\n#[macro_export]\nmacro_rules! init_mat {\n (hook: $init_hook:expr) => {\n struct MatWireGuest;\n use wit::exports::metatype::wit_wire::mat_wire::*;\n wit::export!(MatWireGuest with_types_in wit);\n\n #[allow(unused)]\n impl Guest for MatWireGuest {\n fn handle(req: HandleReq) -> Result {\n MAT_STATE.with(|router| {\n let router = router.borrow();\n router.handle(req)\n })\n }\n\n fn init(args: InitArgs) -> Result {\n let hook = $init_hook;\n let router = Router::from_builder(hook());\n let resp = router.init(args)?;\n MAT_STATE.set(router);\n Ok(resp)\n }\n }\n };\n}\n// gen-static-end\nuse types::*;\npub mod types {\n pub type Idv3TitleString = String;\n pub type Idv3ReleaseTimeStringDatetime = String;\n pub type Idv3Mp3UrlStringUri = String;\n #[derive(Debug, serde::Serialize, serde::Deserialize)]\n pub struct Idv3 {\n pub title: Idv3TitleString,\n pub artist: Idv3TitleString,\n #[serde(rename = "releaseTime")]\n pub release_time: Idv3ReleaseTimeStringDatetime,\n #[serde(rename = "mp3Url")]\n pub mp3_url: Idv3Mp3UrlStringUri,\n }\n}\npub mod stubs {\n use super::*;\n pub trait RemixTrack: Sized + \'static {\n fn erased(self) -> ErasedHandler {\n ErasedHandler {\n mat_id: "remix_track".into(),\n mat_title: "remix_track".into(),\n mat_trait: "RemixTrack".into(),\n handler_fn: Box::new(move |req, cx| {\n let req = serde_json::from_str(req)\n .map_err(|err| HandleErr::InJsonErr(format!("{err}")))?;\n let res = self\n .handle(req, cx)\n .map_err(|err| HandleErr::HandlerErr(format!("{err}")))?;\n serde_json::to_string(&res)\n .map_err(|err| HandleErr::HandlerErr(format!("{err}")))\n }),\n }\n }\n\n fn handle(&self, input: Idv3, cx: Ctx) -> anyhow::Result;\n }\n pub fn op_to_trait_name(op_name: &str) -> &\'static str {\n match op_name {\n "remix_track" => "RemixTrack",\n _ => panic!("unrecognized op_name: {op_name}"),\n }\n }\n}',path:"../examples/typegraphs/metagen/rs/fdk.rs"}},39028:e=>{e.exports={content:'mod fdk;\npub use fdk::*;\n\n// the macro sets up all the glue\ninit_mat! {\n // the hook is expected to return a MatBuilder instance\n hook: || {\n // initialize global stuff here if you need it\n MatBuilder::new()\n // register function handlers here\n // each trait will map to the name of the\n // handler found in the typegraph\n .register_handler(stubs::RemixTrack::erased(MyMat))\n }\n}\n\nstruct MyMat;\n\nimpl stubs::RemixTrack for MyMat {\n fn handle(&self, input: types::Idv3, _cx: Ctx) -> anyhow::Result {\n Ok(types::Idv3 {\n title: format!("{} (Remix)", input.title),\n artist: format!("{} + DJ Cloud", input.artist),\n release_time: input.release_time,\n mp3_url: "https://mp3.url/shumba2".to_string(),\n })\n }\n}',path:"../examples/typegraphs/metagen/rs/lib.rs"}},96280:e=>{e.exports={content:'// This file was @generated by metagen and is intended\n// to be generated again on subsequent metagen runs.\n\nexport type Ctx = {\n parent?: Record;\n /**\n * Request context extracted by auth extractors.\n */\n context?: Record;\n secrets: Record;\n effect: "create" | "update" | "delete" | "read" | undefined | null;\n meta: {\n url: string;\n token: string;\n };\n headers: Record;\n};\n\n/**\n * Access features on your typegraph deployment.\n */\nexport type Deployment = {\n gql: (query: readonly string[], ...args: unknown[]) => {\n run: (\n variables: Record,\n ) => Promise>;\n };\n};\n\nexport type Handler = (\n input: In,\n ctx: Ctx,\n tg: Deployment,\n) => Out | Promise;\n\nexport type StringDateTime = string;\nexport type StringUri = string;\nexport type Idv3 = {\n title: string;\n artist: string;\n releaseTime: StringDateTime;\n mp3Url: StringUri;\n};\n\n\nexport type RemixTrackHandler = Handler;',path:"../examples/typegraphs/metagen/ts/fdk.ts"}},13246:e=>{e.exports={content:'import type { RemixTrackHandler, Ctx, Idv3 } from "./fdk.ts";\n\n// the name of the export must match the one referred int he typegraph\nexport const remix_track: RemixTrackHandler = (inp, cx: Ctx) => {\n const out: Idv3 = {\n title: `${inp.title} (Remix)`,\n artist: `${inp.artist} + DJ Cloud`,\n releaseTime: new Date().toISOString(),\n // S3Runtime could be used to really provide this service\n mp3Url: `${cx.meta.url}/get_mp3`,\n };\n return out;\n};',path:"../examples/typegraphs/metagen/ts/remix.ts"}}}]); \ No 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50"}),"\n","\n",(0,r.jsx)(n.h1,{id:"metagen",children:"Metagen"}),"\n",(0,r.jsx)(n.admonition,{title:"Beta",type:"warning",children:(0,r.jsx)(n.p,{children:"The following feature is not yet stable."})}),"\n",(0,r.jsx)(n.p,{children:"Metagen is a code-generator suite that contains implementations that help with development on the Metatype platform. Today, this means a set of generators to:"}),"\n",(0,r.jsxs)(n.ul,{children:["\n",(0,r.jsx)(n.li,{children:"Generate code-first, typesafe clients for your typegraph"}),"\n",(0,r.jsxs)(n.li,{children:["Help with ",(0,r.jsx)(n.a,{href:"/docs/guides/external-functions",children:"custom functions"})," by generating types, serializers and bindings."]}),"\n"]}),"\n",(0,r.jsxs)(n.p,{children:["It's availaible bundled within the ",(0,r.jsx)(n.a,{href:"/docs/reference/meta-cli",children:"meta CLI"})," and the ",(0,r.jsx)(n.a,{href:"/docs/reference/typegraph#sdks",children:"typegraph SDKs"}),"."]}),"\n",(0,r.jsx)(n.h2,{id:"access-through-cli",children:"Access through CLI"}),"\n",(0,r.jsxs)(n.p,{children:["The meta-cli has a dedicated ",(0,r.jsx)(n.code,{children:"gen"})," command for interacting with metagen. We configure the generators through the ",(0,r.jsx)(n.a,{href:"/docs/reference/meta-cli/configuration-file",children:"standard configuration file"})," under the metagen key."]}),"\n",(0,r.jsx)(n.pre,{children:(0,r.jsx)(n.code,{className:"language-yaml",children:'typegates:\n # bla bla\n\ntypegraphs:\n # bla bla\n\nmetagen:\n targets:\n main:\n # generator to use\n - generator: fdk_rust\n # path to generate to\n path: ./bff/\n # typegraph path to use\n typegraph_path: ./typegraphs/svc-bff.ts\n # we can have multiple generators per target\n - generator: fdk_rust\n path: ./telemetry/\n typegraph_path: ./typegraphs/svc-telemetry.ts\n # generators might have custom keys\n stubbed_runtimes: ["wasm_wire", "deno"]\n # more than one targets avail if you need them\n iter:\n - generator: client_ts\n path: ./next_app/\n # name of typegraph to read from typegate\n typegraph: svc_bff\n'})}),"\n",(0,r.jsx)(n.p,{children:"This allows us to invoke the targets from the CLI."}),"\n",(0,r.jsx)(n.pre,{children:(0,r.jsx)(n.code,{className:"language-sh",children:"meta cli gen main\n"})}),"\n",(0,r.jsxs)(n.p,{children:["This will resolve the requisite typegraphs, serialize as needed and put the resulting files at the appropriate locations. If no target name is provied, the CLI will look for a target under the key ",(0,r.jsx)(n.code,{children:"main"})," and invoke it instead."]}),"\n",(0,r.jsx)(n.h2,{id:"access-through-sdk",children:"Access through SDK"}),"\n",(0,r.jsx)(n.p,{children:"Metagen is availaible through the SDK for programmatic access needs and can be helpful when writing tests or when relying on the CLI is not an option."}),"\n",(0,r.jsx)(i.A,{python:t(7797),typescript:t(19507),disablePlayground:!0}),"\n",(0,r.jsx)(n.h2,{id:"generators",children:"Generators"}),"\n",(0,r.jsxs)(n.admonition,{title:"Chicken or the egg?",type:"info",children:[(0,r.jsx)(n.p,{children:"As most of the generators are intended for types to be used by custom functions, they'll require that you declare the custom functions in your typegraph first. This begs the question, how does one declare custom functions that depend on artifacts that are yet to be generated? Typegraphs error out when referenced artifacts aren't found, how does it work in this scenario?"}),(0,r.jsxs)(n.p,{children:["To resolve this concern, the SDKs support a serialization mode that skips resolution of artifacts. This mode is activated when serialization is done for codegen purposes. What this means is that, ",(0,r.jsx)(n.strong,{children:"you can declare non-existent files in your typegraph and codegen should work"}),". Some generators are even smart enough to work around your expected files. Of course, if the files aren't present when you're trying to deply to the typegate, it'll raise an error."]})]}),"\n",(0,r.jsx)(n.h3,{id:"client_ts",children:(0,r.jsx)(n.code,{children:"client_ts"})}),"\n",(0,r.jsx)(n.p,{children:"This generator supports:"}),"\n",(0,r.jsxs)(n.ul,{children:["\n",(0,r.jsx)(n.li,{children:"Types and query builders based on your typegraph"}),"\n",(0,r.jsxs)(n.li,{children:[(0,r.jsx)(n.a,{href:"https://developer.mozilla.org/en-US/docs/Web/API/Fetch_API",children:(0,r.jsx)(n.code,{children:"fetch"})})," based ",(0,r.jsx)(n.code,{children:"GraphQlTransport"})," implementation","\n",(0,r.jsxs)(n.ul,{children:["\n",(0,r.jsxs)(n.li,{children:["Requires Node.js version ",(0,r.jsx)(n.code,{children:"v17.5.0"})," and ",(0,r.jsx)(n.a,{href:"https://nodejs.org/dist/latest-v18.x/docs/api/globals.html#fetch",children:"up"}),"."]}),"\n",(0,r.jsxs)(n.li,{children:["Requires using ",(0,r.jsx)(n.code,{children:"--experimental-fetch"})," flag if on Node.js version below v18.0.0"]}),"\n",(0,r.jsx)(n.li,{children:"Provides async queries"}),"\n"]}),"\n"]}),"\n",(0,r.jsx)(n.li,{children:"Prepared requests and aliases"}),"\n"]}),"\n",(0,r.jsxs)(n.p,{children:["Refer to the ",(0,r.jsx)(n.a,{href:"/docs/reference/typegraph/client/",children:"client reference"})," for usage guidelines and examples."]}),"\n",(0,r.jsx)(n.h3,{id:"client_py",children:(0,r.jsx)(n.code,{children:"client_py"})}),"\n",(0,r.jsx)(n.p,{children:"This generator supports:"}),"\n",(0,r.jsxs)(n.ul,{children:["\n",(0,r.jsx)(n.li,{children:"Types and query builders based on your typegraph"}),"\n",(0,r.jsxs)(n.li,{children:[(0,r.jsx)(n.code,{children:"urlib"})," based ",(0,r.jsx)(n.code,{children:"GraphQlTransport"})," implementation.","\n",(0,r.jsxs)(n.ul,{children:["\n",(0,r.jsx)(n.li,{children:"Provides sync and async queries"}),"\n"]}),"\n"]}),"\n",(0,r.jsx)(n.li,{children:"Prepared requests and aliases"}),"\n"]}),"\n",(0,r.jsxs)(n.p,{children:["Refer to the ",(0,r.jsx)(n.a,{href:"/docs/reference/typegraph/client/",children:"client reference"})," for usage guidelines and examples."]}),"\n",(0,r.jsx)(n.h3,{id:"client_rs",children:(0,r.jsx)(n.code,{children:"client_rs"})}),"\n",(0,r.jsx)(n.p,{children:"This generator supports:"}),"\n",(0,r.jsxs)(n.ul,{children:["\n",(0,r.jsx)(n.li,{children:"Types and query builders based on your typegraph"}),"\n",(0,r.jsxs)(n.li,{children:[(0,r.jsx)(n.a,{href:"https://lib.rs/crates/reqwest",children:(0,r.jsx)(n.code,{children:"reqwest"})})," based ",(0,r.jsx)(n.code,{children:"GraphQlTransport"})," implementation","\n",(0,r.jsxs)(n.ul,{children:["\n",(0,r.jsx)(n.li,{children:"Provides sync and async queries"}),"\n"]}),"\n"]}),"\n",(0,r.jsx)(n.li,{children:"Prepared requests and aliases"}),"\n"]}),"\n",(0,r.jsxs)(n.p,{children:["Refer to the ",(0,r.jsx)(n.a,{href:"/docs/reference/typegraph/client/",children:"client reference"})," for usage guidelines and examples."]}),"\n",(0,r.jsx)(n.h3,{id:"fdk_typescript",children:(0,r.jsx)(n.code,{children:"fdk_typescript"})}),"\n",(0,r.jsx)(n.p,{children:"This generator supports:"}),"\n",(0,r.jsxs)(n.ul,{children:["\n",(0,r.jsx)(n.li,{children:"Typescript types that map to typegraph types"}),"\n",(0,r.jsxs)(n.li,{children:["Stub function types for custom functions implementors that adhere to typegraph functions.","\n",(0,r.jsxs)(n.ul,{children:["\n",(0,r.jsxs)(n.li,{children:["By default, all function types from the ",(0,r.jsx)(n.code,{children:"DenoRuntime"})," get stub types."]}),"\n",(0,r.jsxs)(n.li,{children:["Use ",(0,r.jsx)(n.code,{children:"stubbed_runtimes"})," to select which runtimes get stubs."]}),"\n"]}),"\n"]}),"\n",(0,r.jsxs)(n.li,{children:[(0,r.jsx)(n.a,{href:"#client_ts",children:(0,r.jsx)(n.code,{children:"client_ts"})})," based typegraph client","\n",(0,r.jsxs)(n.ul,{children:["\n",(0,r.jsxs)(n.li,{children:["Special ",(0,r.jsx)(n.code,{children:"HostcallTransport"})," implementation"]}),"\n"]}),"\n"]}),"\n"]}),"\n",(0,r.jsx)(n.p,{children:"The following example showcases the generator."}),"\n",(0,r.jsx)(n.p,{children:"Typegraph:"}),"\n",(0,r.jsx)(i.A,{python:t(14037),typescript:t(14037),disablePlayground:!0}),"\n",(0,r.jsx)(n.p,{children:"Custom function:"}),"\n",(0,r.jsx)(i.A,{typescript:t(13246),disablePlayground:!0}),"\n",(0,r.jsxs)(o,{children:[(0,r.jsx)("summary",{children:(0,r.jsx)(n.p,{children:"Code generation sample."})}),(0,r.jsx)(i.A,{typescript:t(96280),disablePlayground:!0})]}),"\n",(0,r.jsx)(n.p,{children:"It supports the following extra configuration keys."}),"\n",(0,r.jsxs)(n.table,{children:[(0,r.jsx)(n.thead,{children:(0,r.jsxs)(n.tr,{children:[(0,r.jsx)(n.th,{children:"Key"}),(0,r.jsx)(n.th,{children:"Type"}),(0,r.jsx)(n.th,{children:"Default"}),(0,r.jsx)(n.th,{children:"Description"})]})}),(0,r.jsx)(n.tbody,{children:(0,r.jsxs)(n.tr,{children:[(0,r.jsx)(n.td,{children:(0,r.jsx)(n.code,{children:"stubbed_runtimes"})}),(0,r.jsx)(n.td,{children:(0,r.jsx)(n.code,{children:"string[]"})}),(0,r.jsx)(n.td,{children:(0,r.jsx)(n.code,{children:'["deno"]'})}),(0,r.jsx)(n.td,{children:"Runtimes for which to generate stub types."})]})})]}),"\n",(0,r.jsx)(n.h3,{id:"fdk_python",children:(0,r.jsx)(n.code,{children:"fdk_python"})}),"\n",(0,r.jsx)(n.p,{children:"This generator supports:"}),"\n",(0,r.jsxs)(n.ul,{children:["\n",(0,r.jsx)(n.li,{children:"Python classes that map to typegraph types"}),"\n",(0,r.jsxs)(n.li,{children:["Decorators for custom functions implementors that require adherance to typegraph function types.","\n",(0,r.jsxs)(n.ul,{children:["\n",(0,r.jsxs)(n.li,{children:["By default, all functions from the ",(0,r.jsx)(n.code,{children:"PythonRuntime"})," get stub types."]}),"\n",(0,r.jsxs)(n.li,{children:["TODO: ",(0,r.jsx)(n.code,{children:"stubbed_runtimes"})," for ",(0,r.jsx)(n.code,{children:"fdk_python"})]}),"\n"]}),"\n"]}),"\n",(0,r.jsx)(n.li,{children:"TODO: types for interacting with the typegate from within custom functions."}),"\n"]}),"\n",(0,r.jsx)(n.p,{children:"If the referenced module for the custom function is not found, the generator will also output stub implementation (in addition to the types) at the given type. It will not replace our code on a second run."}),"\n",(0,r.jsx)(n.p,{children:"The following example showcases the generator."}),"\n",(0,r.jsx)(n.p,{children:"Typegraph:"}),"\n",(0,r.jsx)(i.A,{typescript:t(62292),disablePlayground:!0}),"\n",(0,r.jsx)(n.p,{children:"Custom function:"}),"\n",(0,r.jsx)(i.A,{python:t(28434),disablePlayground:!0}),"\n",(0,r.jsxs)(o,{children:[(0,r.jsx)("summary",{children:(0,r.jsx)(n.p,{children:"Code generation sample."})}),(0,r.jsx)(i.A,{python:t(95696),disablePlayground:!0})]}),"\n",(0,r.jsx)(n.h3,{id:"fdk_rust",children:(0,r.jsx)(n.code,{children:"fdk_rust"})}),"\n",(0,r.jsx)(n.p,{children:"This generator generates types, serializers and bindings needed to implement custom functions in Rust. Rust implementations will need to be compiled to wasm components to be executed on the metatype platform and the generator assumes such usage."}),"\n",(0,r.jsx)(n.p,{children:"To be more specific, it supports:"}),"\n",(0,r.jsxs)(n.ul,{children:["\n",(0,r.jsxs)(n.li,{children:["Rust types that map to typegraph defined types","\n",(0,r.jsxs)(n.ul,{children:["\n",(0,r.jsxs)(n.li,{children:["Serialization is handled out of sight through ",(0,r.jsx)(n.a,{href:"https://lib.rs/serde_json",children:(0,r.jsx)(n.code,{children:"serde_json"})})]}),"\n"]}),"\n"]}),"\n",(0,r.jsxs)(n.li,{children:["Stub traits for custom functions implementors that adhere to typegraph functions.","\n",(0,r.jsxs)(n.ul,{children:["\n",(0,r.jsxs)(n.li,{children:["By default, all functions from the ",(0,r.jsx)(n.code,{children:"WasmRuntime"})," get stub types."]}),"\n",(0,r.jsxs)(n.li,{children:["The generator assumes the ",(0,r.jsx)(n.code,{children:"wire"})," based wasm interface is being targetted."]}),"\n",(0,r.jsxs)(n.li,{children:[(0,r.jsx)(n.code,{children:"stubbed_runtimes"})," key can be used to configure stub generation from additional runtimes."]}),"\n"]}),"\n"]}),"\n",(0,r.jsx)(n.li,{children:"Types for interacting with the typegate from within custom functions."}),"\n",(0,r.jsxs)(n.li,{children:["Glue code for setting up the wasm component to be run within the ",(0,r.jsx)(n.code,{children:"WasmRuntime"}),"."]}),"\n"]}),"\n",(0,r.jsx)(n.p,{children:"By default the generator will also output a library crate entrypoint and a functional Cargo.toml with all the required dependencies. These additional files wlil not be overwritten on a second run. The generator can also be configured to avoid generating them even if not present."}),"\n",(0,r.jsx)(n.p,{children:"The following example showcases the generator."}),"\n",(0,r.jsx)(n.p,{children:"Typegraph:"}),"\n",(0,r.jsx)(i.A,{python:t(28054),typescript:t(86016),disablePlayground:!0}),"\n",(0,r.jsx)(n.p,{children:"Custom function:"}),"\n",(0,r.jsx)(a.A,{language:"rust",children:t(39028).content}),"\n",(0,r.jsxs)(o,{children:[(0,r.jsx)("summary",{children:"Code generation sample."}),(0,r.jsx)(a.A,{language:"rust",children:t(86496).content})]}),"\n",(0,r.jsx)(n.p,{children:"It supports the following extra configuration keys."}),"\n",(0,r.jsxs)(n.table,{children:[(0,r.jsx)(n.thead,{children:(0,r.jsxs)(n.tr,{children:[(0,r.jsx)(n.th,{children:"Key"}),(0,r.jsx)(n.th,{children:"Type"}),(0,r.jsx)(n.th,{children:"Default"}),(0,r.jsx)(n.th,{children:"Description"})]})}),(0,r.jsxs)(n.tbody,{children:[(0,r.jsxs)(n.tr,{children:[(0,r.jsx)(n.td,{children:(0,r.jsx)(n.code,{children:"stubbed_runtimes"})}),(0,r.jsx)(n.td,{children:(0,r.jsx)(n.code,{children:"string[]"})}),(0,r.jsx)(n.td,{children:(0,r.jsx)(n.code,{children:'["wasm_wire"]'})}),(0,r.jsx)(n.td,{children:"Runtimes for which to generate stub types."})]}),(0,r.jsxs)(n.tr,{children:[(0,r.jsx)(n.td,{children:(0,r.jsx)(n.code,{children:"crate_name"})}),(0,r.jsx)(n.td,{children:(0,r.jsx)(n.code,{children:"string"})}),(0,r.jsx)(n.td,{children:(0,r.jsx)(n.code,{children:"${typegraphName}_fdk"})}),(0,r.jsxs)(n.td,{children:["Name to assign to crate when generating ",(0,r.jsx)(n.code,{children:"Cargo.toml"}),"."]})]}),(0,r.jsxs)(n.tr,{children:[(0,r.jsx)(n.td,{children:(0,r.jsx)(n.code,{children:"skip_cargo_toml"})}),(0,r.jsx)(n.td,{children:(0,r.jsx)(n.code,{children:"boolean"})}),(0,r.jsx)(n.td,{children:(0,r.jsx)(n.code,{children:"false"})}),(0,r.jsxs)(n.td,{children:["Do not generate ",(0,r.jsx)(n.code,{children:"Cargo.toml"}),"."]})]}),(0,r.jsxs)(n.tr,{children:[(0,r.jsx)(n.td,{children:(0,r.jsx)(n.code,{children:"skip_lib_rs"})}),(0,r.jsx)(n.td,{children:(0,r.jsx)(n.code,{children:"boolean"})}),(0,r.jsx)(n.td,{children:(0,r.jsx)(n.code,{children:"false"})}),(0,r.jsxs)(n.td,{children:["Do not generate ",(0,r.jsx)(n.code,{children:"lib.rs"}),", the sample entrypoint."]})]})]})]})]})}function u(e={}){const{wrapper:n}={...(0,s.R)(),...e.components};return n?(0,r.jsx)(n,{...e,children:(0,r.jsx)(h,{...e})}):h(e)}},65671:(e,n,t)=>{"use strict";t.d(n,{A:()=>i});var r=t(98302),s=(t(30758),t(86070));function i(e){let{python:n,typescript:t,rust:i,...a}=e;const o=[n&&{content:n.content,codeLanguage:"python",codeFileUrl:n.path},t&&{content:t.content,codeLanguage:"typescript",codeFileUrl:t.path},i&&{content:i.content,codeLanguage:"rust",codeFileUrl:i.path}].filter((e=>!!e));return(0,s.jsx)(r.A,{code:0==o.length?void 0:o,...a})}},14037:e=>{e.exports={content:'@typegraph(\n)\ndef metagen_deno(g: Graph):\n idv3 = t.struct(\n {\n "title": t.string(),\n "artist": t.string(),\n "releaseTime": t.datetime(),\n "mp3Url": t.uri(),\n # explicit type names help when generating code\n }\n ).rename("idv3")\n deno = DenoRuntime()\n\n g.expose(\n Policy.public(),\n remix=deno.import_(\n idv3,\n idv3,\n module="./metagen/ts/remix.ts",\n deps=["./metagen/ts/fdk.ts"],\n name="remix_track",\n ).rename("remix_track"), # explicit names help\n )',path:"../examples/typegraphs/metagen-deno.py"}},62292:e=>{e.exports={content:'await typegraph(\n {\n name: "metagen-py",\n },\n (g) => {\n const idv3 = t\n .struct({\n title: t.string(),\n artist: t.string(),\n releaseTime: t.datetime(),\n mp3Url: t.uri(),\n // explicit type names help when generating code\n })\n .rename("idv3");\n\n const python = new PythonRuntime();\n\n g.expose(\n {\n remix: python\n .import(idv3, idv3, {\n module: "./metagen/py/remix.py",\n deps: ["./metagen/py/remix_types.py"],\n name: "remix_track",\n })\n .rename("remix_track"), // explicit names help\n },\n Policy.public()\n );\n }\n);',path:"../examples/typegraphs/metagen-py.ts"}},28054:e=>{e.exports={content:'@typegraph(\n)\ndef metagen_rs(g: Graph):\n idv3 = t.struct(\n {\n "title": t.string(),\n "artist": t.string(),\n "releaseTime": t.datetime(),\n "mp3Url": t.uri(),\n # explicit type names help when generating code\n }\n ).rename("idv3")\n\n # the wire flavour is availible through a static\n # constructor\n wasm = WasmRuntime.wire("metagen/rust.wasm")\n\n g.expose(\n Policy.public(),\n remix=wasm.handler(\n idv3,\n idv3,\n name="remix_track",\n ).rename("remix_track"), # explicit names help\n )',path:"../examples/typegraphs/metagen-rs.py"}},86016:e=>{e.exports={content:'await typegraph(\n {\n name: "metagen-rs",\n },\n (g) => {\n const idv3 = t\n .struct({\n title: t.string(),\n artist: t.string(),\n releaseTime: t.datetime(),\n mp3Url: t.uri(),\n // explicit type names help when generating code\n })\n .rename("idv3");\n\n // the wire flavour is availible through a static\n // constructor\n const wasm = WasmRuntime.wire("metagen/rust.wasm");\n\n g.expose(\n {\n remix: wasm\n .handler(\n idv3,\n idv3,\n {\n name: "remix_track",\n }\n // the traits will map to the name of the materializer\n // and also the the name of the handler mentioned above\n )\n .rename("remix_track"),\n },\n Policy.public()\n );\n }\n);',path:"../examples/typegraphs/metagen-rs.ts"}},7797:e=>{e.exports={content:'import os\nfrom typegraph.graph.metagen import Metagen\n\n\n@typegraph(\n)\ndef metagen_sdk(g: Graph):\n idv3 = t.struct(\n {\n "title": t.string(),\n "artist": t.string(),\n "releaseTime": t.datetime(),\n "mp3Url": t.uri(),\n }\n ).rename("idv3")\n deno = DenoRuntime()\n\n g.expose(\n Policy.public(),\n remix=deno.import_(\n idv3,\n idv3,\n module="./metagen/ts/remix.ts",\n deps=["./metagen/ts/fdk.ts"],\n name="remix_track",\n ).rename("remix_track"),\n )\n\n\nif __name__ == "__main__" and False:\n metagen = Metagen(\n # the workspace root that our config is relative to\n os.path.dirname(os.path.abspath(__file__)),\n # the rest is pretty similar to the CLI config\n {\n "targets": {\n "main": [\n {\n "generator": "fdk_typescript",\n "typegraph_path": __file__,\n "path": "funcs/",\n },\n ],\n },\n },\n )\n tg = metagen_sdk()\n # dry_run doesn\'t write to disk\n items = metagen.dry_run(tg, "main", None)',path:"../examples/typegraphs/metagen-sdk.py"}},19507:e=>{e.exports={content:'import { Metagen } from "@typegraph/sdk/metagen.ts";\n\n// get typegraph desc here\nconst tg = await typegraph(\n {\n name: "metagen-sdk",\n },\n (g) => {\n const idv3 = t\n .struct({\n title: t.string(),\n artist: t.string(),\n releaseTime: t.datetime(),\n mp3Url: t.uri(),\n })\n .rename("idv3");\n\n const deno = new DenoRuntime();\n\n g.expose(\n {\n remix: deno\n .import(idv3, idv3, {\n module: "./metagen/ts/remix.ts",\n deps: ["./metagen/ts/fdk.ts"],\n name: "remix_track",\n })\n .rename("remix_track"),\n },\n Policy.public(),\n );\n },\n);\n\nif (false) {\n const myPath = import.meta.url.replace("file://", "");\n const metagen = new Metagen(\n // the workspace root that our config is relative to\n myPath + "/..",\n // this rest of the config is similmilar to the CLI config\n {\n targets: {\n main: [\n {\n generator: "fdk_typescript",\n typegraph_path: myPath,\n path: "funcs/",\n },\n ],\n },\n },\n );\n // dry_run doesn\'t write to disk\n metagen.dryRun(tg, "main");\n}',path:"../examples/typegraphs/metagen-sdk.ts"}},28434:e=>{e.exports={content:'from .remix_types import typed_remix_track, Idv3\n\n\n# the following decorator makes sure your function\n# adheres to the function types from the typegraph\n@typed_remix_track\ndef remix_track(inp: Idv3) -> Idv3:\n return Idv3(\n title=f"{inp.title} (Remix)",\n artist=f"{inp.artist} + DJ Cloud",\n releaseTime=inp.releaseTime,\n mp3Url="https://mp3.url/remix1",\n )',path:"../examples/typegraphs/metagen/py/remix.py"}},95696:e=>{e.exports={content:'from types import NoneType\nfrom typing import Callable, List, Union, get_origin, ForwardRef, Any\nfrom dataclasses import dataclass, asdict, fields\n\nFORWARD_REFS = {}\n\n\nclass Struct:\n def repr(self):\n return asdict(self)\n\n @staticmethod\n def try_new(dt_class, val: Any):\n # Object\n ftypes = {f.name: f.type for f in fields(dt_class)}\n attrs = {}\n for f in val:\n fval = val[f]\n ftype = ftypes[f]\n serialized = False\n # Union\n if get_origin(ftype) is Union:\n try:\n attrs[f] = Struct.try_union(ftype.__args__, fval)\n serialized = True\n except Exception:\n pass\n # List\n elif get_origin(ftype) is list:\n try:\n attrs[f] = Struct.try_typed_list(ftype.__args__, fval)\n serialized = True\n except Exception:\n pass\n # Any\n if not serialized:\n if isinstance(ftype, str) and ftype in FORWARD_REFS:\n klass = FORWARD_REFS[ftype]\n attrs[f] = Struct.new(klass, fval)\n else:\n attrs[f] = Struct.new(ftype, fval)\n return dt_class(**attrs)\n\n @staticmethod\n def try_typed_list(tpe: Any, items: Any):\n hint = tpe.__args__[0]\n klass = (\n FORWARD_REFS[hint.__forward_arg__] if isinstance(hint, ForwardRef) else hint\n )\n return [Struct.new(klass, v) for v in items]\n\n @staticmethod\n def try_union(variants: List[Any], val: Any):\n errors = []\n for variant in variants:\n try:\n if variant is NoneType:\n if val is None:\n return None\n else:\n continue\n if get_origin(variant) is list:\n if isinstance(val, list):\n return Struct.try_typed_list(variant, val)\n else:\n continue\n klass = FORWARD_REFS[variant.__forward_arg__]\n return Struct.try_new(klass, val)\n except Exception as e:\n errors.append(str(e))\n raise Exception("\\n".join(errors))\n\n @staticmethod\n def new(dt_class: Any, val: Any):\n try:\n return Struct.try_new(dt_class, val)\n except Exception:\n return val\n\n\n@dataclass\nclass Idv3(Struct):\n title: str\n artist: str\n releaseTime: str\n mp3Url: str\n\n\nFORWARD_REFS["Idv3"] = Idv3\n\n\ndef __repr(value: Any):\n if isinstance(value, Struct):\n return value.repr()\n return value\n\n\ndef typed_remix_track(user_fn: Callable[[Idv3], Idv3]):\n def exported_wrapper(raw_inp):\n inp: Idv3 = Struct.new(Idv3, raw_inp)\n out: Idv3 = user_fn(inp)\n if isinstance(out, list):\n return [__repr(v) for v in out]\n return __repr(out)\n\n return exported_wrapper',path:"../examples/typegraphs/metagen/py/remix_types.py"}},86496:e=>{e.exports={content:'// This file was @generated by metagen and is intended\n// to be generated again on subsequent metagen runs.\n#![cfg_attr(rustfmt, rustfmt_skip)]\n\n// gen-static-start\n#![allow(dead_code)]\n\npub mod wit {\n wit_bindgen::generate!({\n pub_export_macro: true,\n \n inline: "package metatype:wit-wire;\n\ninterface typegate-wire {\n hostcall: func(op-name: string, json: string) -> result;\n}\n\ninterface mat-wire {\n type json-str = string;\n\n record mat-info {\n op-name: string,\n mat-title: string,\n mat-hash: string,\n mat-data-json: string,\n }\n\n record init-args {\n metatype-version: string,\n expected-ops: list\n }\n\n record init-response {\n ok: bool\n }\n\n variant init-error {\n version-mismatch(string),\n unexpected-mat(mat-info),\n other(string)\n }\n\n init: func(args: init-args) -> result;\n\n record handle-req {\n op-name: string,\n in-json: json-str,\n }\n\n variant handle-err {\n no-handler,\n in-json-err(string),\n handler-err(string),\n }\n\n handle: func(req: handle-req) -> result;\n}\n\nworld wit-wire {\n import typegate-wire;\n\n export mat-wire;\n}\n"\n });\n}\n\nuse std::cell::RefCell;\nuse std::collections::HashMap;\n\nuse wit::exports::metatype::wit_wire::mat_wire::*;\nuse wit::metatype::wit_wire::typegate_wire::hostcall;\n\npub type HandlerFn = Box Result>;\n\npub struct ErasedHandler {\n mat_id: String,\n mat_trait: String,\n mat_title: String,\n handler_fn: HandlerFn,\n}\n\npub struct MatBuilder {\n handlers: HashMap,\n}\n\nimpl MatBuilder {\n pub fn new() -> Self {\n Self {\n handlers: Default::default(),\n }\n }\n\n pub fn register_handler(mut self, handler: ErasedHandler) -> Self {\n self.handlers.insert(handler.mat_trait.clone(), handler);\n self\n }\n}\n\npub struct Router {\n handlers: HashMap,\n}\n\nimpl Router {\n pub fn from_builder(builder: MatBuilder) -> Self {\n Self {\n handlers: builder.handlers,\n }\n }\n\n pub fn init(&self, args: InitArgs) -> Result {\n static MT_VERSION: &str = "0.5.0-rc.3";\n if args.metatype_version != MT_VERSION {\n return Err(InitError::VersionMismatch(MT_VERSION.into()));\n }\n for info in args.expected_ops {\n let mat_trait = stubs::op_to_trait_name(&info.op_name);\n if !self.handlers.contains_key(mat_trait) {\n return Err(InitError::UnexpectedMat(info));\n }\n }\n Ok(InitResponse { ok: true })\n }\n\n pub fn handle(&self, req: HandleReq) -> Result {\n let mat_trait = stubs::op_to_trait_name(&req.op_name);\n let Some(handler) = self.handlers.get(mat_trait) else {\n return Err(HandleErr::NoHandler);\n };\n let cx = Ctx {};\n (handler.handler_fn)(&req.in_json, cx)\n }\n}\n\npub type InitCallback = fn() -> anyhow::Result;\n\nthread_local! {\n pub static MAT_STATE: RefCell = panic!("MAT_STATE has not been initialized");\n}\n\npub struct Ctx {}\n\nimpl Ctx {\n pub fn gql(\n &self,\n query: &str,\n variables: impl Into,\n ) -> Result\n where\n O: serde::de::DeserializeOwned,\n {\n match hostcall(\n "gql",\n &serde_json::to_string(&serde_json::json!({\n "query": query,\n "variables": variables.into(),\n }))?,\n ) {\n Ok(json) => Ok(serde_json::from_str(&json[..])?),\n Err(json) => Err(GraphqlRunError::HostError(serde_json::from_str(&json)?)),\n }\n }\n}\n\n#[derive(Debug)]\npub enum GraphqlRunError {\n JsonError(serde_json::Error),\n HostError(serde_json::Value),\n}\n\nimpl std::error::Error for GraphqlRunError {}\n\nimpl From for GraphqlRunError {\n fn from(value: serde_json::Error) -> Self {\n Self::JsonError(value)\n }\n}\n\nimpl std::fmt::Display for GraphqlRunError {\n fn fmt(&self, f: &mut std::fmt::Formatter<\'_>) -> std::fmt::Result {\n match self {\n GraphqlRunError::JsonError(msg) => write!(f, "json error: {msg}"),\n GraphqlRunError::HostError(serde_json::Value::Object(map))\n if map.contains_key("message") =>\n {\n write!(f, "host error: {}", map["message"])\n }\n GraphqlRunError::HostError(val) => write!(f, "host error: {val:?}"),\n }\n }\n}\n\n#[macro_export]\nmacro_rules! init_mat {\n (hook: $init_hook:expr) => {\n struct MatWireGuest;\n use wit::exports::metatype::wit_wire::mat_wire::*;\n wit::export!(MatWireGuest with_types_in wit);\n\n #[allow(unused)]\n impl Guest for MatWireGuest {\n fn handle(req: HandleReq) -> Result {\n MAT_STATE.with(|router| {\n let router = router.borrow();\n router.handle(req)\n })\n }\n\n fn init(args: InitArgs) -> Result {\n let hook = $init_hook;\n let router = Router::from_builder(hook());\n let resp = router.init(args)?;\n MAT_STATE.set(router);\n Ok(resp)\n }\n }\n };\n}\n// gen-static-end\nuse types::*;\npub mod types {\n pub type Idv3TitleString = String;\n pub type Idv3ReleaseTimeStringDatetime = String;\n pub type Idv3Mp3UrlStringUri = String;\n #[derive(Debug, serde::Serialize, serde::Deserialize)]\n pub struct Idv3 {\n pub title: Idv3TitleString,\n pub artist: Idv3TitleString,\n #[serde(rename = "releaseTime")]\n pub release_time: Idv3ReleaseTimeStringDatetime,\n #[serde(rename = "mp3Url")]\n pub mp3_url: Idv3Mp3UrlStringUri,\n }\n}\npub mod stubs {\n use super::*;\n pub trait RemixTrack: Sized + \'static {\n fn erased(self) -> ErasedHandler {\n ErasedHandler {\n mat_id: "remix_track".into(),\n mat_title: "remix_track".into(),\n mat_trait: "RemixTrack".into(),\n handler_fn: Box::new(move |req, cx| {\n let req = serde_json::from_str(req)\n .map_err(|err| HandleErr::InJsonErr(format!("{err}")))?;\n let res = self\n .handle(req, cx)\n .map_err(|err| HandleErr::HandlerErr(format!("{err}")))?;\n serde_json::to_string(&res)\n .map_err(|err| HandleErr::HandlerErr(format!("{err}")))\n }),\n }\n }\n\n fn handle(&self, input: Idv3, cx: Ctx) -> anyhow::Result;\n }\n pub fn op_to_trait_name(op_name: &str) -> &\'static str {\n match op_name {\n "remix_track" => "RemixTrack",\n _ => panic!("unrecognized op_name: {op_name}"),\n }\n }\n}',path:"../examples/typegraphs/metagen/rs/fdk.rs"}},39028:e=>{e.exports={content:'mod fdk;\npub use fdk::*;\n\n// the macro sets up all the glue\ninit_mat! {\n // the hook is expected to return a MatBuilder instance\n hook: || {\n // initialize global stuff here if you need it\n MatBuilder::new()\n // register function handlers here\n // each trait will map to the name of the\n // handler found in the typegraph\n .register_handler(stubs::RemixTrack::erased(MyMat))\n }\n}\n\nstruct MyMat;\n\nimpl stubs::RemixTrack for MyMat {\n fn handle(&self, input: types::Idv3, _cx: Ctx) -> anyhow::Result {\n Ok(types::Idv3 {\n title: format!("{} (Remix)", input.title),\n artist: format!("{} + DJ Cloud", input.artist),\n release_time: input.release_time,\n mp3_url: "https://mp3.url/shumba2".to_string(),\n })\n }\n}',path:"../examples/typegraphs/metagen/rs/lib.rs"}},96280:e=>{e.exports={content:'// This file was @generated by metagen and is intended\n// to be generated again on subsequent metagen runs.\n\nexport type Ctx = {\n parent?: Record;\n /**\n * Request context extracted by auth extractors.\n */\n context?: Record;\n secrets: Record;\n effect: "create" | "update" | "delete" | "read" | undefined | null;\n meta: {\n url: string;\n token: string;\n };\n headers: Record;\n};\n\n/**\n * Access features on your typegraph deployment.\n */\nexport type Deployment = {\n gql: (query: readonly string[], ...args: unknown[]) => {\n run: (\n variables: Record,\n ) => Promise>;\n };\n};\n\nexport type Handler = (\n input: In,\n ctx: Ctx,\n tg: Deployment,\n) => Out | Promise;\n\nexport type StringDateTime = string;\nexport type StringUri = string;\nexport type Idv3 = {\n title: string;\n artist: string;\n releaseTime: StringDateTime;\n mp3Url: StringUri;\n};\n\n\nexport type RemixTrackHandler = Handler;',path:"../examples/typegraphs/metagen/ts/fdk.ts"}},13246:e=>{e.exports={content:'import type { RemixTrackHandler, Ctx, Idv3 } from "./fdk.ts";\n\n// the name of the export must match the one referred int he typegraph\nexport const remix_track: RemixTrackHandler = (inp, cx: Ctx) => {\n const out: Idv3 = {\n title: `${inp.title} (Remix)`,\n artist: `${inp.artist} + DJ Cloud`,\n releaseTime: new Date().toISOString(),\n // S3Runtime could be used to really provide this service\n mp3Url: `${cx.meta.url}/get_mp3`,\n };\n return out;\n};',path:"../examples/typegraphs/metagen/ts/remix.ts"}}}]); \ No newline at end of file diff --git a/assets/js/e1da19f3.3808ee05.js b/assets/js/e1da19f3.699c7064.js similarity index 99% rename from assets/js/e1da19f3.3808ee05.js rename to assets/js/e1da19f3.699c7064.js index d8b1983345..d47bf04ba7 100644 --- a/assets/js/e1da19f3.3808ee05.js +++ b/assets/js/e1da19f3.699c7064.js @@ -1 +1 @@ -(self.webpackChunkwebsite=self.webpackChunkwebsite||[]).push([[4191],{48372:(e,n,t)=>{"use strict";t.r(n),t.d(n,{assets:()=>c,contentTitle:()=>l,default:()=>h,frontMatter:()=>o,metadata:()=>d,toc:()=>u});var r=t(86070),i=t(25710),a=t(65671),s=t(7871);const o={sidebar_position:50},l="Wasm functions",d={id:"guides/wasm-functions/index",title:"Wasm functions",description:"The following feature is not yet stable.",source:"@site/docs/guides/wasm-functions/index.mdx",sourceDirName:"guides/wasm-functions",slug:"/guides/wasm-functions/",permalink:"/docs/guides/wasm-functions/",draft:!1,unlisted:!1,editUrl:"https://github.com/metatypedev/metatype/tree/main/docs/metatype.dev/docs/guides/wasm-functions/index.mdx",tags:[],version:"current",sidebarPosition:50,frontMatter:{sidebar_position:50},sidebar:"docs",previous:{title:"Secure your requests",permalink:"/docs/guides/securing-requests/"},next:{title:"Self-host the Typegate",permalink:"/docs/guides/self-hosting"}},c={},u=[{value:"Tooling",id:"tooling",level:2},{value:"Typegraph",id:"typegraph",level:2},{value:"Metagen",id:"metagen",level:2},{value:"Building",id:"building",level:2}];function m(e){const n={a:"a",admonition:"admonition",code:"code",h1:"h1",h2:"h2",li:"li",ol:"ol",p:"p",pre:"pre",...(0,i.R)(),...e.components},{Details:o}=n;return o||function(e,n){throw new Error("Expected "+(n?"component":"object")+" `"+e+"` to be defined: you likely forgot to import, pass, or provide it.")}("Details",!0),(0,r.jsxs)(r.Fragment,{children:[(0,r.jsx)(n.h1,{id:"wasm-functions",children:"Wasm functions"}),"\n",(0,r.jsx)(n.admonition,{title:"Beta",type:"warning",children:(0,r.jsx)(n.p,{children:"The following feature is not yet stable."})}),"\n",(0,r.jsxs)(n.p,{children:["The ",(0,r.jsx)(n.a,{href:"/docs/reference/runtimes/wasm",children:(0,r.jsx)(n.code,{children:"WasmRuntime"})})," enables one to use any langauge/ecosystem with a toolchain capable of producing wasm artifacts to author ",(0,r.jsx)(n.a,{href:"/docs/guides/external-functions",children:"custom functions"}),". ",(0,r.jsx)(n.a,{href:"https://rust-lang.org",children:"Rust"})," is one such a language and has shaped up to be the hotspot of development in the wasm ecosystem (The Metatype itself platform has many rusty parts). In this guide, we'll see how to set up a workflow for using Rust for our custom functions."]}),"\n",(0,r.jsx)(n.h2,{id:"tooling",children:"Tooling"}),"\n",(0,r.jsx)(n.p,{children:"We need to install several programs to be able to produce the components. The following checklist contains links to get you started:"}),"\n",(0,r.jsxs)(n.ol,{children:["\n",(0,r.jsxs)(n.li,{children:["Rust compiler toolchain: this guide assumes moderate familiartiy of development with rust and won't spend many words on how to get it functional. In any case, you can get started with rust ",(0,r.jsx)(n.a,{href:"https://www.rust-lang.org/learn/get-started",children:"here"}),"."]}),"\n",(0,r.jsxs)(n.li,{children:[(0,r.jsx)(n.code,{children:"wasm32-unknown-unknown"})," target for rustc: This is the backend that rustc uses to produce wasi compatible wasm components. If you're using ",(0,r.jsx)(n.code,{children:"rustup"})," to manage your toolchain, Cargo will automatically install the target when you're building."]}),"\n",(0,r.jsxs)(n.li,{children:[(0,r.jsx)(n.code,{children:"wasm-tools"}),": this is the swiss army knife for working with wasm artifacts, courtesy of the ",(0,r.jsx)(n.a,{href:"https://bytecodealliance.org/",children:"Bytecode Alliance"}),". Installation instructions can be found ",(0,r.jsx)(n.a,{href:"https://github.com/bytecodealliance/wasm-tools/",children:"here"}),"."]}),"\n"]}),"\n",(0,r.jsx)(n.h2,{id:"typegraph",children:"Typegraph"}),"\n",(0,r.jsxs)(n.p,{children:["The ",(0,r.jsx)(n.code,{children:"WasmRuntime"})," currently comes in two flavours that are both based on the wasm component spec. This guide focues on the ",(0,r.jsx)(n.code,{children:"wire"})," flavour, where your component is expected to implement a standard WIT interface that's designed around a simple Json based RPC wire format. Thankfully, all of that boilerplate is easy to automate away and that's exactly what we'll do using ",(0,r.jsx)(n.a,{href:"/docs/reference/metagen",children:"metagen"})," to generate the binding code."]}),"\n",(0,r.jsx)(n.p,{children:"Before anything though, we need to author the typegraph:"}),"\n",(0,r.jsx)(a.A,{python:t(28054),typescript:t(86016),disablePlayground:!0}),"\n",(0,r.jsxs)(n.p,{children:["Note that the ",(0,r.jsx)(n.code,{children:"WasmRuntime"})," constructor mentions a non-existent wasm file on disk. This won't be a problem for the metagen generators but we'll need to produce the artifact before we deploy the typegraph. We'll see what buliding the artifact entails in just a minute."]}),"\n",(0,r.jsx)(n.h2,{id:"metagen",children:"Metagen"}),"\n",(0,r.jsxs)(n.p,{children:["We can now tackle the boilerplate. Metagen bundles the ",(0,r.jsx)(n.a,{href:"/docs/reference/metagen#fdk_rust",children:(0,r.jsx)(n.code,{children:"fdk_rust"})})," generator which can generate all the glue code along with Rust types that correspond to our typegraph types. Let's configure a metagen target in our configuration file to get just that done."]}),"\n",(0,r.jsx)(n.pre,{children:(0,r.jsx)(n.code,{className:"language-yaml",children:"metagen:\n targets:\n metagen_rs:\n # this is the generator we're interested in\n - generator: fdk_rust\n # the location where to put the generated files\n path: ./metagen/rs/\n # the path to our typegraph\n typegraph_path: ./metagen-rs.ts\n"})}),"\n",(0,r.jsxs)(n.p,{children:["The configuration file is read by the ",(0,r.jsx)(n.a,{href:"/docs/reference/meta-cli",children:"meta CLI"})," which also bundles the metagen suite. This means we can invoke the target from the command line like so:"]}),"\n",(0,r.jsx)(n.pre,{children:(0,r.jsx)(n.code,{className:"language-bash",children:"meta gen metagen_rs\n"})}),"\n",(0,r.jsx)(n.p,{children:"This should give us the following files:"}),"\n",(0,r.jsx)(n.pre,{children:(0,r.jsx)(n.code,{className:"language-shell",children:"\u276f lsd --tree metagen/rs/\n\uf115 rs\n\u251c\u2500\u2500 \ue7a8 Cargo.toml\n\u251c\u2500\u2500 \ue7a8 lib.rs\n\u2514\u2500\u2500 \ue7a8 fdk.rs\n"})}),"\n",(0,r.jsxs)(n.p,{children:["By default, the ",(0,r.jsx)(n.code,{children:"fdk_rust"})," generator outputs all the necessary files required to build our wasm file. This includes the ",(0,r.jsx)(n.code,{children:"Cargo.toml"})," manifest for our Rust crate."]}),"\n",(0,r.jsx)(s.A,{language:"toml",children:t(86858).content}),"\n",(0,r.jsxs)(n.p,{children:[(0,r.jsx)(n.code,{children:"fdk_rust"})," will not overwrite a ",(0,r.jsx)(n.code,{children:"Cargo.toml"})," file discovered at generation path so you can add other dependencies if need be."]}),"\n",(0,r.jsxs)(n.p,{children:["The ",(0,r.jsx)(n.code,{children:"fdk.rs"})," file contains all the glue code including the typegraph types."]}),"\n",(0,r.jsxs)(o,{children:[(0,r.jsx)("summary",{children:(0,r.jsx)(n.p,{children:"Code generation sample. It's collapsed here as it's for the most part an\nuninteresting implementation detail."})}),(0,r.jsx)(s.A,{language:"rust",children:t(86496).content})]}),"\n",(0,r.jsx)(n.p,{children:"When working on the typegraph, we can run metagen again to regenerate this file and get the latest types."}),"\n",(0,r.jsxs)(n.p,{children:["The generator also includes a sample ",(0,r.jsx)(n.code,{children:"lib.rs"})," entrypoint file for our crate. We'll modify it now to implement our custom function."]}),"\n",(0,r.jsx)(s.A,{language:"rust",children:t(39028).content}),"\n",(0,r.jsx)(n.h2,{id:"building",children:"Building"}),"\n",(0,r.jsx)(n.p,{children:"We'll now use the rust toolchain and wasm-tools to build the wasm component. This requires multiple commands. It's presented below as a shell script that you can modify from."}),"\n",(0,r.jsx)(n.pre,{children:(0,r.jsx)(n.code,{className:"language-bash",children:"# flags to make script execution visible\nset -eux\n\n# regenerate code before building\nmeta gen metagen_rs\n\n# variablize common names\nTARGET=wasm32-wasi\nCRATE_NAME=metagen_rs_fdk\n\n# build in release mode for smallest sizes\ncargo build -p $CRATE_NAME --target $TARGET --release\n# use wasm-tools to change wasm file into wasm component\nwasm-tools component new \\\n # rust builds the wasm file under the name of the crate\n ./target/$TARGET/debug/$CRATE_NAME.wasm \\\n -o ./target/rust-component.wasm \\\n\n# copy the component to a location that we specified\n# in our typegraph\ncp ./target/rust-component.wasm ./rust.wasm\n"})}),"\n",(0,r.jsxs)(n.p,{children:["Put the shell script into a file like ",(0,r.jsx)(n.code,{children:"build.sh"})," and execute it with a posix compatible shell like ",(0,r.jsx)(n.code,{children:"bash"}),". You should now have all the files to deploy your typegraph."]}),"\n",(0,r.jsx)(a.A,{typegraph:"metagen-rs",typescript:t(86016),python:t(28054),query:t(48734)})]})}function h(e={}){const{wrapper:n}={...(0,i.R)(),...e.components};return n?(0,r.jsx)(n,{...e,children:(0,r.jsx)(m,{...e})}):m(e)}},65671:(e,n,t)=>{"use strict";t.d(n,{A:()=>a});var r=t(98302),i=(t(30758),t(86070));function a(e){let{python:n,typescript:t,rust:a,...s}=e;const o=[n&&{content:n.content,codeLanguage:"python",codeFileUrl:n.path},t&&{content:t.content,codeLanguage:"typescript",codeFileUrl:t.path},a&&{content:a.content,codeLanguage:"rust",codeFileUrl:a.path}].filter((e=>!!e));return(0,i.jsx)(r.A,{code:0==o.length?void 0:o,...s})}},48734:e=>{var n={kind:"Document",definitions:[{kind:"OperationDefinition",operation:"query",variableDefinitions:[],directives:[],selectionSet:{kind:"SelectionSet",selections:[{kind:"Field",name:{kind:"Name",value:"remix"},arguments:[{kind:"Argument",name:{kind:"Name",value:"title"},value:{kind:"StringValue",value:"Lovefool",block:!1}},{kind:"Argument",name:{kind:"Name",value:"artist"},value:{kind:"StringValue",value:"The Cardigans",block:!1}},{kind:"Argument",name:{kind:"Name",value:"releaseTime"},value:{kind:"StringValue",value:"1996-06-29T10:30:40.340Z",block:!1}},{kind:"Argument",name:{kind:"Name",value:"mp3Url"},value:{kind:"StringValue",value:"https://mus.ic/lovefool.mp3",block:!1}}],directives:[],selectionSet:{kind:"SelectionSet",selections:[{kind:"Field",name:{kind:"Name",value:"title"},arguments:[],directives:[]},{kind:"Field",name:{kind:"Name",value:"artist"},arguments:[],directives:[]},{kind:"Field",name:{kind:"Name",value:"releaseTime"},arguments:[],directives:[]},{kind:"Field",name:{kind:"Name",value:"mp3Url"},arguments:[],directives:[]}]}}]}}],loc:{start:0,end:213}};n.loc.source={body:'query {\n remix(\n title: "Lovefool"\n artist: "The Cardigans"\n releaseTime: "1996-06-29T10:30:40.340Z"\n mp3Url: "https://mus.ic/lovefool.mp3"\n ) {\n title\n artist\n releaseTime\n mp3Url\n }\n}\n',name:"GraphQL request",locationOffset:{line:1,column:1}};function t(e,n){if("FragmentSpread"===e.kind)n.add(e.name.value);else if("VariableDefinition"===e.kind){var r=e.type;"NamedType"===r.kind&&n.add(r.name.value)}e.selectionSet&&e.selectionSet.selections.forEach((function(e){t(e,n)})),e.variableDefinitions&&e.variableDefinitions.forEach((function(e){t(e,n)})),e.definitions&&e.definitions.forEach((function(e){t(e,n)}))}var r={};n.definitions.forEach((function(e){if(e.name){var n=new Set;t(e,n),r[e.name.value]=n}})),e.exports=n},28054:e=>{e.exports={content:'@typegraph(\n)\ndef metagen_rs(g: Graph):\n idv3 = t.struct(\n {\n "title": t.string(),\n "artist": t.string(),\n "releaseTime": t.datetime(),\n "mp3Url": t.uri(),\n # explicit type names help when generating code\n }\n ).rename("idv3")\n\n # the wire flavour is availible through a static\n # constructor\n wasm = WasmRuntime.wire("metagen/rust.wasm")\n\n g.expose(\n Policy.public(),\n remix=wasm.handler(\n idv3,\n idv3,\n name="remix_track",\n ).rename("remix_track"), # explicit names help\n )',path:"../examples/typegraphs/metagen-rs.py"}},86016:e=>{e.exports={content:'await typegraph(\n {\n name: "metagen-rs",\n },\n (g) => {\n const idv3 = t\n .struct({\n title: t.string(),\n artist: t.string(),\n releaseTime: t.datetime(),\n mp3Url: t.uri(),\n // explicit type names help when generating code\n })\n .rename("idv3");\n\n // the wire flavour is availible through a static\n // constructor\n const wasm = WasmRuntime.wire("metagen/rust.wasm");\n\n g.expose(\n {\n remix: wasm\n .handler(\n idv3,\n idv3,\n {\n name: "remix_track",\n }\n // the traits will map to the name of the materializer\n // and also the the name of the handler mentioned above\n )\n .rename("remix_track"),\n },\n Policy.public()\n );\n }\n);',path:"../examples/typegraphs/metagen-rs.ts"}},86858:e=>{e.exports={content:'package.name = "metagen_rs_fdk"\npackage.edition = "2021"\npackage.version = "0.0.1"\n\n# we need to use a specific library crate type to build\n# wasm components in rust\n[lib]\npath = "lib.rs"\ncrate-type = ["cdylib", "rlib"]\n\n# the following dependencies are used by the generated code\n[dependencies]\nanyhow = "1" # error handling\nserde = { version = "1", features = ["derive"] } # serialization\nserde_json = "1" #json serialization\nwit-bindgen = "0.22.0" # wasm component biding\n\n# we set the following flags to minimize code size\n# when buliding in the release mode\n# this keeps our wasm files small\n[profile.release]\nstrip = "symbols"\nopt-level = "z"',path:"../examples/typegraphs/metagen/rs/Cargo.toml"}},86496:e=>{e.exports={content:'// This file was @generated by metagen and is intended\n// to be generated again on subsequent metagen runs.\n#![cfg_attr(rustfmt, rustfmt_skip)]\n\n// gen-static-start\n#![allow(dead_code)]\n\npub mod wit {\n wit_bindgen::generate!({\n pub_export_macro: true,\n \n inline: "package metatype:wit-wire;\n\ninterface typegate-wire {\n hostcall: func(op-name: string, json: string) -> result;\n}\n\ninterface mat-wire {\n type json-str = string;\n\n record mat-info {\n op-name: string,\n mat-title: string,\n mat-hash: string,\n mat-data-json: string,\n }\n\n record init-args {\n metatype-version: string,\n expected-ops: list\n }\n\n record init-response {\n ok: bool\n }\n\n variant init-error {\n version-mismatch(string),\n unexpected-mat(mat-info),\n other(string)\n }\n\n init: func(args: init-args) -> result;\n\n record handle-req {\n op-name: string,\n in-json: json-str,\n }\n\n variant handle-err {\n no-handler,\n in-json-err(string),\n handler-err(string),\n }\n\n handle: func(req: handle-req) -> result;\n}\n\nworld wit-wire {\n import typegate-wire;\n\n export mat-wire;\n}\n"\n });\n}\n\nuse std::cell::RefCell;\nuse std::collections::HashMap;\n\nuse wit::exports::metatype::wit_wire::mat_wire::*;\nuse wit::metatype::wit_wire::typegate_wire::hostcall;\n\npub type HandlerFn = Box Result>;\n\npub struct ErasedHandler {\n mat_id: String,\n mat_trait: String,\n mat_title: String,\n handler_fn: HandlerFn,\n}\n\npub struct MatBuilder {\n handlers: HashMap,\n}\n\nimpl MatBuilder {\n pub fn new() -> Self {\n Self {\n handlers: Default::default(),\n }\n }\n\n pub fn register_handler(mut self, handler: ErasedHandler) -> Self {\n self.handlers.insert(handler.mat_trait.clone(), handler);\n self\n }\n}\n\npub struct Router {\n handlers: HashMap,\n}\n\nimpl Router {\n pub fn from_builder(builder: MatBuilder) -> Self {\n Self {\n handlers: builder.handlers,\n }\n }\n\n pub fn init(&self, args: InitArgs) -> Result {\n static MT_VERSION: &str = "0.5.0-rc.1";\n if args.metatype_version != MT_VERSION {\n return Err(InitError::VersionMismatch(MT_VERSION.into()));\n }\n for info in args.expected_ops {\n let mat_trait = stubs::op_to_trait_name(&info.op_name);\n if !self.handlers.contains_key(mat_trait) {\n return Err(InitError::UnexpectedMat(info));\n }\n }\n Ok(InitResponse { ok: true })\n }\n\n pub fn handle(&self, req: HandleReq) -> Result {\n let mat_trait = stubs::op_to_trait_name(&req.op_name);\n let Some(handler) = self.handlers.get(mat_trait) else {\n return Err(HandleErr::NoHandler);\n };\n let cx = Ctx {};\n (handler.handler_fn)(&req.in_json, cx)\n }\n}\n\npub type InitCallback = fn() -> anyhow::Result;\n\nthread_local! {\n pub static MAT_STATE: RefCell = panic!("MAT_STATE has not been initialized");\n}\n\npub struct Ctx {}\n\nimpl Ctx {\n pub fn gql(\n &self,\n query: &str,\n variables: impl Into,\n ) -> Result\n where\n O: serde::de::DeserializeOwned,\n {\n match hostcall(\n "gql",\n &serde_json::to_string(&serde_json::json!({\n "query": query,\n "variables": variables.into(),\n }))?,\n ) {\n Ok(json) => Ok(serde_json::from_str(&json[..])?),\n Err(json) => Err(GraphqlRunError::HostError(serde_json::from_str(&json)?)),\n }\n }\n}\n\n#[derive(Debug)]\npub enum GraphqlRunError {\n JsonError(serde_json::Error),\n HostError(serde_json::Value),\n}\n\nimpl std::error::Error for GraphqlRunError {}\n\nimpl From for GraphqlRunError {\n fn from(value: serde_json::Error) -> Self {\n Self::JsonError(value)\n }\n}\n\nimpl std::fmt::Display for GraphqlRunError {\n fn fmt(&self, f: &mut std::fmt::Formatter<\'_>) -> std::fmt::Result {\n match self {\n GraphqlRunError::JsonError(msg) => write!(f, "json error: {msg}"),\n GraphqlRunError::HostError(serde_json::Value::Object(map))\n if map.contains_key("message") =>\n {\n write!(f, "host error: {}", map["message"])\n }\n GraphqlRunError::HostError(val) => write!(f, "host error: {val:?}"),\n }\n }\n}\n\n#[macro_export]\nmacro_rules! init_mat {\n (hook: $init_hook:expr) => {\n struct MatWireGuest;\n use wit::exports::metatype::wit_wire::mat_wire::*;\n wit::export!(MatWireGuest with_types_in wit);\n\n #[allow(unused)]\n impl Guest for MatWireGuest {\n fn handle(req: HandleReq) -> Result {\n MAT_STATE.with(|router| {\n let router = router.borrow();\n router.handle(req)\n })\n }\n\n fn init(args: InitArgs) -> Result {\n let hook = $init_hook;\n let router = Router::from_builder(hook());\n let resp = router.init(args)?;\n MAT_STATE.set(router);\n Ok(resp)\n }\n }\n };\n}\n// gen-static-end\nuse types::*;\npub mod types {\n pub type Idv3TitleString = String;\n pub type Idv3ReleaseTimeStringDatetime = String;\n pub type Idv3Mp3UrlStringUri = String;\n #[derive(Debug, serde::Serialize, serde::Deserialize)]\n pub struct Idv3 {\n pub title: Idv3TitleString,\n pub artist: Idv3TitleString,\n #[serde(rename = "releaseTime")]\n pub release_time: Idv3ReleaseTimeStringDatetime,\n #[serde(rename = "mp3Url")]\n pub mp3_url: Idv3Mp3UrlStringUri,\n }\n}\npub mod stubs {\n use super::*;\n pub trait RemixTrack: Sized + \'static {\n fn erased(self) -> ErasedHandler {\n ErasedHandler {\n mat_id: "remix_track".into(),\n mat_title: "remix_track".into(),\n mat_trait: "RemixTrack".into(),\n handler_fn: Box::new(move |req, cx| {\n let req = serde_json::from_str(req)\n .map_err(|err| HandleErr::InJsonErr(format!("{err}")))?;\n let res = self\n .handle(req, cx)\n .map_err(|err| HandleErr::HandlerErr(format!("{err}")))?;\n serde_json::to_string(&res)\n .map_err(|err| HandleErr::HandlerErr(format!("{err}")))\n }),\n }\n }\n\n fn handle(&self, input: Idv3, cx: Ctx) -> anyhow::Result;\n }\n pub fn op_to_trait_name(op_name: &str) -> &\'static str {\n match op_name {\n "remix_track" => "RemixTrack",\n _ => panic!("unrecognized op_name: {op_name}"),\n }\n }\n}',path:"../examples/typegraphs/metagen/rs/fdk.rs"}},39028:e=>{e.exports={content:'mod fdk;\npub use fdk::*;\n\n// the macro sets up all the glue\ninit_mat! {\n // the hook is expected to return a MatBuilder instance\n hook: || {\n // initialize global stuff here if you need it\n MatBuilder::new()\n // register function handlers here\n // each trait will map to the name of the\n // handler found in the typegraph\n .register_handler(stubs::RemixTrack::erased(MyMat))\n }\n}\n\nstruct MyMat;\n\nimpl stubs::RemixTrack for MyMat {\n fn handle(&self, input: types::Idv3, _cx: Ctx) -> anyhow::Result {\n Ok(types::Idv3 {\n title: format!("{} (Remix)", input.title),\n artist: format!("{} + DJ Cloud", input.artist),\n release_time: input.release_time,\n mp3_url: "https://mp3.url/shumba2".to_string(),\n })\n }\n}',path:"../examples/typegraphs/metagen/rs/lib.rs"}}}]); \ No newline at end of file +(self.webpackChunkwebsite=self.webpackChunkwebsite||[]).push([[4191],{48372:(e,n,t)=>{"use strict";t.r(n),t.d(n,{assets:()=>c,contentTitle:()=>l,default:()=>h,frontMatter:()=>o,metadata:()=>d,toc:()=>u});var r=t(86070),i=t(25710),a=t(65671),s=t(7871);const o={sidebar_position:50},l="Wasm functions",d={id:"guides/wasm-functions/index",title:"Wasm functions",description:"The following feature is not yet stable.",source:"@site/docs/guides/wasm-functions/index.mdx",sourceDirName:"guides/wasm-functions",slug:"/guides/wasm-functions/",permalink:"/docs/guides/wasm-functions/",draft:!1,unlisted:!1,editUrl:"https://github.com/metatypedev/metatype/tree/main/docs/metatype.dev/docs/guides/wasm-functions/index.mdx",tags:[],version:"current",sidebarPosition:50,frontMatter:{sidebar_position:50},sidebar:"docs",previous:{title:"Secure your requests",permalink:"/docs/guides/securing-requests/"},next:{title:"Self-host the Typegate",permalink:"/docs/guides/self-hosting"}},c={},u=[{value:"Tooling",id:"tooling",level:2},{value:"Typegraph",id:"typegraph",level:2},{value:"Metagen",id:"metagen",level:2},{value:"Building",id:"building",level:2}];function m(e){const n={a:"a",admonition:"admonition",code:"code",h1:"h1",h2:"h2",li:"li",ol:"ol",p:"p",pre:"pre",...(0,i.R)(),...e.components},{Details:o}=n;return o||function(e,n){throw new Error("Expected "+(n?"component":"object")+" `"+e+"` to be defined: you likely forgot to import, pass, or provide it.")}("Details",!0),(0,r.jsxs)(r.Fragment,{children:[(0,r.jsx)(n.h1,{id:"wasm-functions",children:"Wasm functions"}),"\n",(0,r.jsx)(n.admonition,{title:"Beta",type:"warning",children:(0,r.jsx)(n.p,{children:"The following feature is not yet stable."})}),"\n",(0,r.jsxs)(n.p,{children:["The ",(0,r.jsx)(n.a,{href:"/docs/reference/runtimes/wasm",children:(0,r.jsx)(n.code,{children:"WasmRuntime"})})," enables one to use any langauge/ecosystem with a toolchain capable of producing wasm artifacts to author ",(0,r.jsx)(n.a,{href:"/docs/guides/external-functions",children:"custom functions"}),". ",(0,r.jsx)(n.a,{href:"https://rust-lang.org",children:"Rust"})," is one such a language and has shaped up to be the hotspot of development in the wasm ecosystem (The Metatype itself platform has many rusty parts). In this guide, we'll see how to set up a workflow for using Rust for our custom functions."]}),"\n",(0,r.jsx)(n.h2,{id:"tooling",children:"Tooling"}),"\n",(0,r.jsx)(n.p,{children:"We need to install several programs to be able to produce the components. The following checklist contains links to get you started:"}),"\n",(0,r.jsxs)(n.ol,{children:["\n",(0,r.jsxs)(n.li,{children:["Rust compiler toolchain: this guide assumes moderate familiartiy of development with rust and won't spend many words on how to get it functional. In any case, you can get started with rust ",(0,r.jsx)(n.a,{href:"https://www.rust-lang.org/learn/get-started",children:"here"}),"."]}),"\n",(0,r.jsxs)(n.li,{children:[(0,r.jsx)(n.code,{children:"wasm32-unknown-unknown"})," target for rustc: This is the backend that rustc uses to produce wasi compatible wasm components. If you're using ",(0,r.jsx)(n.code,{children:"rustup"})," to manage your toolchain, Cargo will automatically install the target when you're building."]}),"\n",(0,r.jsxs)(n.li,{children:[(0,r.jsx)(n.code,{children:"wasm-tools"}),": this is the swiss army knife for working with wasm artifacts, courtesy of the ",(0,r.jsx)(n.a,{href:"https://bytecodealliance.org/",children:"Bytecode Alliance"}),". Installation instructions can be found ",(0,r.jsx)(n.a,{href:"https://github.com/bytecodealliance/wasm-tools/",children:"here"}),"."]}),"\n"]}),"\n",(0,r.jsx)(n.h2,{id:"typegraph",children:"Typegraph"}),"\n",(0,r.jsxs)(n.p,{children:["The ",(0,r.jsx)(n.code,{children:"WasmRuntime"})," currently comes in two flavours that are both based on the wasm component spec. This guide focues on the ",(0,r.jsx)(n.code,{children:"wire"})," flavour, where your component is expected to implement a standard WIT interface that's designed around a simple Json based RPC wire format. Thankfully, all of that boilerplate is easy to automate away and that's exactly what we'll do using ",(0,r.jsx)(n.a,{href:"/docs/reference/metagen",children:"metagen"})," to generate the binding code."]}),"\n",(0,r.jsx)(n.p,{children:"Before anything though, we need to author the typegraph:"}),"\n",(0,r.jsx)(a.A,{python:t(28054),typescript:t(86016),disablePlayground:!0}),"\n",(0,r.jsxs)(n.p,{children:["Note that the ",(0,r.jsx)(n.code,{children:"WasmRuntime"})," constructor mentions a non-existent wasm file on disk. This won't be a problem for the metagen generators but we'll need to produce the artifact before we deploy the typegraph. We'll see what buliding the artifact entails in just a minute."]}),"\n",(0,r.jsx)(n.h2,{id:"metagen",children:"Metagen"}),"\n",(0,r.jsxs)(n.p,{children:["We can now tackle the boilerplate. Metagen bundles the ",(0,r.jsx)(n.a,{href:"/docs/reference/metagen#fdk_rust",children:(0,r.jsx)(n.code,{children:"fdk_rust"})})," generator which can generate all the glue code along with Rust types that correspond to our typegraph types. Let's configure a metagen target in our configuration file to get just that done."]}),"\n",(0,r.jsx)(n.pre,{children:(0,r.jsx)(n.code,{className:"language-yaml",children:"metagen:\n targets:\n metagen_rs:\n # this is the generator we're interested in\n - generator: fdk_rust\n # the location where to put the generated files\n path: ./metagen/rs/\n # the path to our typegraph\n typegraph_path: ./metagen-rs.ts\n"})}),"\n",(0,r.jsxs)(n.p,{children:["The configuration file is read by the ",(0,r.jsx)(n.a,{href:"/docs/reference/meta-cli",children:"meta CLI"})," which also bundles the metagen suite. This means we can invoke the target from the command line like so:"]}),"\n",(0,r.jsx)(n.pre,{children:(0,r.jsx)(n.code,{className:"language-bash",children:"meta gen metagen_rs\n"})}),"\n",(0,r.jsx)(n.p,{children:"This should give us the following files:"}),"\n",(0,r.jsx)(n.pre,{children:(0,r.jsx)(n.code,{className:"language-shell",children:"\u276f lsd --tree metagen/rs/\n\uf115 rs\n\u251c\u2500\u2500 \ue7a8 Cargo.toml\n\u251c\u2500\u2500 \ue7a8 lib.rs\n\u2514\u2500\u2500 \ue7a8 fdk.rs\n"})}),"\n",(0,r.jsxs)(n.p,{children:["By default, the ",(0,r.jsx)(n.code,{children:"fdk_rust"})," generator outputs all the necessary files required to build our wasm file. This includes the ",(0,r.jsx)(n.code,{children:"Cargo.toml"})," manifest for our Rust crate."]}),"\n",(0,r.jsx)(s.A,{language:"toml",children:t(86858).content}),"\n",(0,r.jsxs)(n.p,{children:[(0,r.jsx)(n.code,{children:"fdk_rust"})," will not overwrite a ",(0,r.jsx)(n.code,{children:"Cargo.toml"})," file discovered at generation path so you can add other dependencies if need be."]}),"\n",(0,r.jsxs)(n.p,{children:["The ",(0,r.jsx)(n.code,{children:"fdk.rs"})," file contains all the glue code including the typegraph types."]}),"\n",(0,r.jsxs)(o,{children:[(0,r.jsx)("summary",{children:(0,r.jsx)(n.p,{children:"Code generation sample. It's collapsed here as it's for the most part an\nuninteresting implementation detail."})}),(0,r.jsx)(s.A,{language:"rust",children:t(86496).content})]}),"\n",(0,r.jsx)(n.p,{children:"When working on the typegraph, we can run metagen again to regenerate this file and get the latest types."}),"\n",(0,r.jsxs)(n.p,{children:["The generator also includes a sample ",(0,r.jsx)(n.code,{children:"lib.rs"})," entrypoint file for our crate. We'll modify it now to implement our custom function."]}),"\n",(0,r.jsx)(s.A,{language:"rust",children:t(39028).content}),"\n",(0,r.jsx)(n.h2,{id:"building",children:"Building"}),"\n",(0,r.jsx)(n.p,{children:"We'll now use the rust toolchain and wasm-tools to build the wasm component. This requires multiple commands. It's presented below as a shell script that you can modify from."}),"\n",(0,r.jsx)(n.pre,{children:(0,r.jsx)(n.code,{className:"language-bash",children:"# flags to make script execution visible\nset -eux\n\n# regenerate code before building\nmeta gen metagen_rs\n\n# variablize common names\nTARGET=wasm32-wasi\nCRATE_NAME=metagen_rs_fdk\n\n# build in release mode for smallest sizes\ncargo build -p $CRATE_NAME --target $TARGET --release\n# use wasm-tools to change wasm file into wasm component\nwasm-tools component new \\\n # rust builds the wasm file under the name of the crate\n ./target/$TARGET/debug/$CRATE_NAME.wasm \\\n -o ./target/rust-component.wasm \\\n\n# copy the component to a location that we specified\n# in our typegraph\ncp ./target/rust-component.wasm ./rust.wasm\n"})}),"\n",(0,r.jsxs)(n.p,{children:["Put the shell script into a file like ",(0,r.jsx)(n.code,{children:"build.sh"})," and execute it with a posix compatible shell like ",(0,r.jsx)(n.code,{children:"bash"}),". You should now have all the files to deploy your typegraph."]}),"\n",(0,r.jsx)(a.A,{typegraph:"metagen-rs",typescript:t(86016),python:t(28054),query:t(48734)})]})}function h(e={}){const{wrapper:n}={...(0,i.R)(),...e.components};return n?(0,r.jsx)(n,{...e,children:(0,r.jsx)(m,{...e})}):m(e)}},65671:(e,n,t)=>{"use strict";t.d(n,{A:()=>a});var r=t(98302),i=(t(30758),t(86070));function a(e){let{python:n,typescript:t,rust:a,...s}=e;const o=[n&&{content:n.content,codeLanguage:"python",codeFileUrl:n.path},t&&{content:t.content,codeLanguage:"typescript",codeFileUrl:t.path},a&&{content:a.content,codeLanguage:"rust",codeFileUrl:a.path}].filter((e=>!!e));return(0,i.jsx)(r.A,{code:0==o.length?void 0:o,...s})}},48734:e=>{var 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)',path:"../examples/typegraphs/metagen-rs.py"}},86016:e=>{e.exports={content:'await typegraph(\n {\n name: "metagen-rs",\n },\n (g) => {\n const idv3 = t\n .struct({\n title: t.string(),\n artist: t.string(),\n releaseTime: t.datetime(),\n mp3Url: t.uri(),\n // explicit type names help when generating code\n })\n .rename("idv3");\n\n // the wire flavour is availible through a static\n // constructor\n const wasm = WasmRuntime.wire("metagen/rust.wasm");\n\n g.expose(\n {\n remix: wasm\n .handler(\n idv3,\n idv3,\n {\n name: "remix_track",\n }\n // the traits will map to the name of the materializer\n // and also the the name of the handler mentioned above\n )\n .rename("remix_track"),\n },\n Policy.public()\n );\n }\n);',path:"../examples/typegraphs/metagen-rs.ts"}},86858:e=>{e.exports={content:'package.name = "metagen_rs_fdk"\npackage.edition = "2021"\npackage.version = "0.0.1"\n\n# we need to use a specific library crate type to build\n# wasm components in rust\n[lib]\npath = "lib.rs"\ncrate-type = ["cdylib", "rlib"]\n\n# the following dependencies are used by the generated code\n[dependencies]\nanyhow = "1" # error handling\nserde = { version = "1", features = ["derive"] } # serialization\nserde_json = "1" #json serialization\nwit-bindgen = "0.22.0" # wasm component biding\n\n# we set the following flags to minimize code size\n# when buliding in the release mode\n# this keeps our wasm files small\n[profile.release]\nstrip = "symbols"\nopt-level = "z"',path:"../examples/typegraphs/metagen/rs/Cargo.toml"}},86496:e=>{e.exports={content:'// This file was @generated by metagen and is intended\n// to be generated again on subsequent metagen runs.\n#![cfg_attr(rustfmt, rustfmt_skip)]\n\n// gen-static-start\n#![allow(dead_code)]\n\npub mod wit {\n wit_bindgen::generate!({\n pub_export_macro: true,\n \n inline: "package metatype:wit-wire;\n\ninterface typegate-wire {\n hostcall: func(op-name: string, json: string) -> result;\n}\n\ninterface mat-wire {\n type json-str = string;\n\n record mat-info {\n op-name: string,\n mat-title: string,\n mat-hash: string,\n mat-data-json: string,\n }\n\n record init-args {\n metatype-version: string,\n expected-ops: list\n }\n\n record init-response {\n ok: bool\n }\n\n variant init-error {\n version-mismatch(string),\n unexpected-mat(mat-info),\n other(string)\n }\n\n init: func(args: init-args) -> result;\n\n record handle-req {\n op-name: string,\n in-json: json-str,\n }\n\n variant handle-err {\n no-handler,\n in-json-err(string),\n handler-err(string),\n }\n\n handle: func(req: handle-req) -> result;\n}\n\nworld wit-wire {\n import typegate-wire;\n\n export mat-wire;\n}\n"\n });\n}\n\nuse std::cell::RefCell;\nuse std::collections::HashMap;\n\nuse wit::exports::metatype::wit_wire::mat_wire::*;\nuse wit::metatype::wit_wire::typegate_wire::hostcall;\n\npub type HandlerFn = Box Result>;\n\npub struct ErasedHandler {\n mat_id: String,\n mat_trait: String,\n mat_title: String,\n handler_fn: HandlerFn,\n}\n\npub struct MatBuilder {\n handlers: HashMap,\n}\n\nimpl MatBuilder {\n pub fn new() -> Self {\n Self {\n handlers: Default::default(),\n }\n }\n\n pub fn register_handler(mut self, handler: ErasedHandler) -> Self {\n self.handlers.insert(handler.mat_trait.clone(), handler);\n self\n }\n}\n\npub struct Router {\n handlers: HashMap,\n}\n\nimpl Router {\n pub fn from_builder(builder: MatBuilder) -> Self {\n Self {\n handlers: builder.handlers,\n }\n }\n\n pub fn init(&self, args: InitArgs) -> Result {\n static MT_VERSION: &str = "0.5.0-rc.3";\n if args.metatype_version != MT_VERSION {\n return Err(InitError::VersionMismatch(MT_VERSION.into()));\n }\n for info in args.expected_ops {\n let mat_trait = stubs::op_to_trait_name(&info.op_name);\n if !self.handlers.contains_key(mat_trait) {\n return Err(InitError::UnexpectedMat(info));\n }\n }\n Ok(InitResponse { ok: true })\n }\n\n pub fn handle(&self, req: HandleReq) -> Result {\n let mat_trait = stubs::op_to_trait_name(&req.op_name);\n let Some(handler) = self.handlers.get(mat_trait) else {\n return Err(HandleErr::NoHandler);\n };\n let cx = Ctx {};\n (handler.handler_fn)(&req.in_json, cx)\n }\n}\n\npub type InitCallback = fn() -> anyhow::Result;\n\nthread_local! {\n pub static MAT_STATE: RefCell = panic!("MAT_STATE has not been initialized");\n}\n\npub struct Ctx {}\n\nimpl Ctx {\n pub fn gql(\n &self,\n query: &str,\n variables: impl Into,\n ) -> Result\n where\n O: serde::de::DeserializeOwned,\n {\n match hostcall(\n "gql",\n &serde_json::to_string(&serde_json::json!({\n "query": query,\n "variables": variables.into(),\n }))?,\n ) {\n Ok(json) => Ok(serde_json::from_str(&json[..])?),\n Err(json) => Err(GraphqlRunError::HostError(serde_json::from_str(&json)?)),\n }\n }\n}\n\n#[derive(Debug)]\npub enum GraphqlRunError {\n JsonError(serde_json::Error),\n HostError(serde_json::Value),\n}\n\nimpl std::error::Error for GraphqlRunError {}\n\nimpl From for GraphqlRunError {\n fn from(value: serde_json::Error) -> Self {\n Self::JsonError(value)\n }\n}\n\nimpl std::fmt::Display for GraphqlRunError {\n fn fmt(&self, f: &mut std::fmt::Formatter<\'_>) -> std::fmt::Result {\n match self {\n GraphqlRunError::JsonError(msg) => write!(f, "json error: {msg}"),\n GraphqlRunError::HostError(serde_json::Value::Object(map))\n if map.contains_key("message") =>\n {\n write!(f, "host error: {}", map["message"])\n }\n GraphqlRunError::HostError(val) => write!(f, "host error: {val:?}"),\n }\n }\n}\n\n#[macro_export]\nmacro_rules! init_mat {\n (hook: $init_hook:expr) => {\n struct MatWireGuest;\n use wit::exports::metatype::wit_wire::mat_wire::*;\n wit::export!(MatWireGuest with_types_in wit);\n\n #[allow(unused)]\n impl Guest for MatWireGuest {\n fn handle(req: HandleReq) -> Result {\n MAT_STATE.with(|router| {\n let router = router.borrow();\n router.handle(req)\n })\n }\n\n fn init(args: InitArgs) -> Result {\n let hook = $init_hook;\n let router = Router::from_builder(hook());\n let resp = router.init(args)?;\n MAT_STATE.set(router);\n Ok(resp)\n }\n }\n };\n}\n// gen-static-end\nuse types::*;\npub mod types {\n pub type Idv3TitleString = String;\n pub type Idv3ReleaseTimeStringDatetime = String;\n pub type Idv3Mp3UrlStringUri = String;\n #[derive(Debug, serde::Serialize, serde::Deserialize)]\n pub struct Idv3 {\n pub title: Idv3TitleString,\n pub artist: Idv3TitleString,\n #[serde(rename = "releaseTime")]\n pub release_time: Idv3ReleaseTimeStringDatetime,\n #[serde(rename = "mp3Url")]\n pub mp3_url: Idv3Mp3UrlStringUri,\n }\n}\npub mod stubs {\n use super::*;\n pub trait RemixTrack: Sized + \'static {\n fn erased(self) -> ErasedHandler {\n ErasedHandler {\n mat_id: "remix_track".into(),\n mat_title: "remix_track".into(),\n mat_trait: "RemixTrack".into(),\n handler_fn: Box::new(move |req, cx| {\n let req = serde_json::from_str(req)\n .map_err(|err| HandleErr::InJsonErr(format!("{err}")))?;\n let res = self\n .handle(req, cx)\n .map_err(|err| HandleErr::HandlerErr(format!("{err}")))?;\n serde_json::to_string(&res)\n .map_err(|err| HandleErr::HandlerErr(format!("{err}")))\n }),\n }\n }\n\n fn handle(&self, input: Idv3, cx: Ctx) -> anyhow::Result;\n }\n pub fn op_to_trait_name(op_name: &str) -> &\'static str {\n match op_name {\n "remix_track" => "RemixTrack",\n _ => panic!("unrecognized op_name: {op_name}"),\n }\n }\n}',path:"../examples/typegraphs/metagen/rs/fdk.rs"}},39028:e=>{e.exports={content:'mod fdk;\npub use fdk::*;\n\n// the macro sets up all the glue\ninit_mat! {\n // the hook is expected to return a MatBuilder instance\n hook: || {\n // initialize global stuff here if you need it\n MatBuilder::new()\n // register function handlers here\n // each trait will map to the name of the\n // handler found in the typegraph\n .register_handler(stubs::RemixTrack::erased(MyMat))\n }\n}\n\nstruct MyMat;\n\nimpl stubs::RemixTrack for MyMat {\n fn handle(&self, input: types::Idv3, _cx: Ctx) -> anyhow::Result {\n Ok(types::Idv3 {\n title: format!("{} (Remix)", input.title),\n artist: format!("{} + DJ Cloud", input.artist),\n release_time: input.release_time,\n mp3_url: "https://mp3.url/shumba2".to_string(),\n })\n }\n}',path:"../examples/typegraphs/metagen/rs/lib.rs"}}}]); \ No newline at end of file diff --git a/assets/js/main.4b8c6419.js b/assets/js/main.f7552bc2.js similarity index 99% rename from assets/js/main.4b8c6419.js rename to assets/js/main.f7552bc2.js index 0515e5a155..508471cb55 100644 --- a/assets/js/main.4b8c6419.js +++ b/assets/js/main.f7552bc2.js @@ -1,2 +1,2 @@ -/*! 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z-index: ").concat(2147483699,";\n background-color: ").concat(f,"cc;\n display: flex;\n align-items: center;\n justify-content: center;\n }\n\n .gleap-image-view-image {\n width: 90%;\n height: auto;\n max-width: 90%;\n max-height: 90%;\n object-fit: contain;\n }\n\n .gleap-image-view-close {\n position: fixed;\n top: 20px;\n right: 20px;\n width: 32px;\n height: 32px;\n opacity: 0.8;\n z-index: ").concat(2147483740,";\n box-shadow: 0px 5px 18px rgba(0, 0, 0, 0.16);\n cursor: pointer;\n }\n\n .gleap-image-view-close:hover {\n opacity: 1;\n }\n\n .gleap-image-view-close svg path {\n fill: ").concat(a,";\n }\n\n [dir=rtl].gleap-frame-container {\n right: auto;\n left: ").concat(i,"px;\n bottom: ").concat(61+s,'px;\n }\n\n .gleap-frame-container--loading iframe {\n opacity: 0;\n }\n\n .gleap-frame-container--loading::before {\n content: " ";\n position: fixed;\n top: 0px;\n left: 0px;\n right: 0px;\n height: 100%;\n max-height: 380px;\n background: linear-gradient(\n 130deg,\n ').concat(g," 0%,\n ").concat(t,' 100%\n );\n }\n \n .gleap-frame-container--loading::after {\n content: " ";\n position: fixed;\n top: 0px;\n left: 0px;\n right: 0px;\n height: 100%;\n height: 100%;\n max-height: 380px;\n background: linear-gradient(\n 180deg,\n transparent 60%,\n ').concat(a,"1A 70%,\n ").concat(a," 100%\n );\n }\n\n .gleap-frame-container--loading-nogradient::before {\n max-height: 340px;\n background: ").concat(t," !important;\n }\n\n .gleap-frame-container--loading-nofade::after {\n display: none !important;\n }\n\n .gleap-frame-container--survey {\n bottom: ").concat(s,"px !important;\n }\n\n .gleap-frame-container--extended {\n max-width: 690px !important;\n }\n\n .gleap-frame-container--survey-full {\n position: fixed;\n top: 0 !important;\n left: 0 !important;\n bottom: 0 !important;\n right: 0 !important;\n width: 100vw !important;\n max-width: 100vw !important;\n height: 100vh !important;\n background-color: rgba(0, 0, 0, 0.5);\n backdrop-filter: blur(6px);\n display: flex !important;\n justify-content: center !important;\n align-items: center !important;\n max-height: 100vh !important;\n border-radius: 0 !important;\n animation-name: none !important;\n }\n\n .gleap-frame-container--survey-full .gleap-frame-container-inner {\n max-width: 640px !important;\n width: calc(100% - 24px);\n border-radius: ").concat(x,"px;\n overflow: hidden;\n }\n\n .gleap-frame-container--classic {\n right: ").concat(i,"px;\n bottom: ").concat(s,"px;\n }\n\n [dir=rtl].gleap-frame-container--classic {\n right: auto;\n left: ").concat(i,"px;\n bottom: ").concat(s,"px;\n }\n\n .gleap-frame-container--no-button {\n bottom: ").concat(s,"px;\n }\n\n [dir=rtl].gleap-frame-container--classic-left {\n bottom: ").concat(s,"px;\n }\n\n .gleap-frame-container--classic-left {\n right: auto;\n left: ").concat(i,"px;\n bottom: ").concat(s,"px;\n }\n\n [dir=rtl].gleap-frame-container--classic-left {\n left: auto;\n right: ").concat(i,"px;\n bottom: ").concat(s,"px;\n }\n\n .gleap-frame-container--modern-left {\n right: auto;\n left: ").concat(i,"px;\n bottom: ").concat(61+s,"px;\n }\n\n [dir=rtl].gleap-frame-container--modern-left {\n left: auto;\n right: ").concat(i,"px;\n bottom: ").concat(61+s,"px;\n }\n\n .gleap-frame-container--animate {\n pointer-events: auto !important;\n }\n\n @keyframes gleapFadeInUp {\n from {\n opacity: 0;\n transform: translate3d(0, 100%, 0);\n }\n to {\n opacity: 1;\n transform: translate3d(0, 0, 0);\n }\n }\n\n @keyframes gleapFadeInUpMobile {\n from {\n opacity: 0;\n transform: translate3d(0, 10%, 0);\n }\n to {\n opacity: 1;\n transform: translate3d(0, 0, 0);\n }\n }\n\n .gleap-notification-container {\n position: fixed;\n bottom: ").concat(E,"px;\n right: ").concat(i,"px;\n z-index: ").concat(2147483630,";\n display: flex;\n flex-direction: column;\n align-items: flex-end;\n width: 100%;\n max-width: min(340px, 80vw);\n }\n\n .gleap-notification-container--left {\n left: ").concat(4+i,"px;\n right: initial !important;\n }\n\n [dir=rtl].gleap-notification-container {\n left: ").concat(4+i,"px;\n right: initial !important;\n }\n\n [dir=rtl].gleap-notification-container--left {\n left: initial !important;\n right: ").concat(i,"px !important;\n align-items: flex-start !important;\n }\n\n .gleap-notification-container--no-button {\n bottom: ").concat(s,"px;\n }\n\n .gleap-notification-item {\n animation-duration: 0.7s;\n animation-fill-mode: both;\n animation-name: bbFadeInOpacity;\n }\n\n .gleap-notification-close {\n border-radius: 100%;\n width: 28px;\n height: 28px;\n background-color: ").concat(v,";\n display: flex;\n justify-content: center;\n align-items: center;\n margin-bottom: 8px;\n cursor: pointer;\n visibility: hidden;\n pointer-events: none;\n }\n\n .gleap-notification-container:hover .gleap-notification-close {\n visibility: visible;\n pointer-events: auto;\n animation-duration: 0.7s;\n animation-fill-mode: both;\n animation-name: bbFadeInOpacity;\n }\n\n @media only screen and (max-width: 450px) {\n .gleap-notification-close {\n visibility: visible;\n pointer-events: auto;\n animation-duration: 0.7s;\n animation-fill-mode: both;\n animation-name: bbFadeInOpacity;\n }\n }\n\n .gleap-notification-close svg {\n width: 45%;\n height: 45%;\n object-fit: contain;\n fill: ").concat(a,";\n }\n\n .gleap-notification-item-checklist-container {\n display: flex;\n animation: fadeIn;\n animation-duration: .45s;\n background-color: ").concat(a,";\n border-radius: ").concat(v,";\n box-sizing: border-box;\n cursor: pointer;\n flex-direction: column;\n overflow: hidden;\n box-shadow: 0px 5px 30px rgba(0, 0, 0, 0.2);\n border-radius: ").concat(k,"px;\n margin-bottom: 12px;\n }\n\n .gleap-notification-item-checklist-content {\n align-items: flex-start;\n display: flex;\n flex-direction: column;\n padding: 15px;\n width: 100%;\n width: min(310px, 70vw);\n max-width: min(310px, 70vw);\n }\n\n .gleap-notification-item-checklist-content-title {\n color: ").concat(f,";\n font-size: 15px;\n font-weight: 500;\n line-height: 21px;\n margin-bottom: 10px;\n max-width: 100%;\n -webkit-line-clamp: 3;\n -webkit-box-orient: vertical;\n overflow: hidden;\n }\n\n .gleap-notification-item-checklist-content-progress {\n width: 100%;\n height: 8px;\n border-radius: 8px;\n background-color: ").concat(y,";\n }\n\n .gleap-notification-item-checklist-content-progress-inner {\n height: 100%;\n border-radius: 8px;\n background-color: ").concat(e,";\n }\n\n .gleap-notification-item-checklist-content-next {\n color: ").concat(v,";\n font-size: 15px;\n font-weight: normal;\n line-height: 21px;\n margin-top: 10px;\n max-width: 100%;\n white-space: nowrap;\n overflow: hidden;\n text-overflow: ellipsis;\n display: flex;\n align-items: center;\n }\n\n .gleap-notification-item-checklist-content-next svg {\n height: 18px;\n margin-right: 5px;\n width: auto;\n }\n\n .gleap-notification-item-checklist-content-next b {\n font-size: 15px;\n font-weight: normal;\n color: ").concat(f,";\n }\n\n .gleap-notification-item-news {\n width: 100%;\n cursor: pointer;\n }\n\n .gleap-notification-item-news-content {\n align-items: flex-start;\n display: flex;\n flex-direction: column;\n padding: 15px;\n }\n\n .gleap-notification-item-news-preview {\n color: ").concat(v,";\n font-size: 15px;\n line-height: 21px;\n font-weight: 400;\n overflow-wrap: break-word;\n word-break: break-word;\n display: block;\n display: -webkit-box;\n -webkit-line-clamp: 2;\n -webkit-box-orient: vertical;\n overflow: hidden;\n }\n\n .gleap-notification-item-news-sender {\n display: flex;\n align-items: center;\n color: ").concat(v,";\n font-size: 15px;\n line-height: 21px;\n font-weight: 400;\n }\n \n .gleap-notification-item-news-content-title {\n color: ").concat(f,";\n font-size: 15px;\n font-weight: 500;\n line-height: 21px;\n margin-bottom: 6px;\n max-width: 100%;\n -webkit-line-clamp: 3;\n -webkit-box-orient: vertical;\n overflow: hidden;\n }\n\n .gleap-notification-item-news-sender img {\n border-radius: 100%;\n height: 20px;\n margin-right: 8px;\n object-fit: cover;\n width: 20px;\n }\n\n [dir=rtl] .gleap-notification-item-news-sender img {\n margin-left: 8px;\n margin-right: 0px !important;\n }\n\n .gleap-notification-item-news-container {\n display: flex;\n animation: fadeIn;\n animation-duration: .45s;\n background-color: ").concat(a,";\n border-radius: ").concat(v,";\n box-sizing: border-box;\n cursor: pointer;\n flex-direction: column;\n overflow: hidden;\n box-shadow: 0px 5px 30px rgba(0, 0, 0, 0.2);\n border-radius: ").concat(k,"px;\n margin-bottom: 12px;\n }\n\n .gleap-notification-item-news-image {\n background-color: ").concat(v,";\n height: 170px;\n object-fit: cover;\n width: 100%;\n }\n\n .gleap-notification-item-news:hover .gleap-notification-item-news-content-title {\n color: ").concat(e,";\n }\n\n .gleap-notification-item {\n display: flex;\n align-items: flex-end;\n cursor: pointer;\n }\n\n .gleap-notification-item img {\n width: 32px;\n height: 32px;\n min-width: 32px;\n border-radius: 100%;\n object-fit: cover;\n margin-right: 8px;\n margin-bottom: 12px;\n cursor: pointer;\n }\n\n [dir=rtl] .gleap-notification-item img {\n margin-left: 8px;\n margin-right: 0px !important;\n }\n\n .gleap-notification-item-container {\n box-shadow: 0px 5px 30px rgba(0, 0, 0, 0.2);\n border-radius: ").concat(k,"px;\n border-bottom-left-radius: 0px;\n padding: 20px;\n background-color: ").concat(a,";\n margin-bottom: 12px;\n cursor: pointer;\n font-size: 15px;\n line-height: 21px;\n color: ").concat(f,';\n position: relative;\n }\n\n .gleap-notification-item-container::after {\n content: " ";\n position: absolute;\n bottom: 0px;\n width: 0px;\n height: 0px;\n left: -6px;\n border-style: solid;\n border-width: 0px 0px 10px 6px;\n border-color: transparent transparent ').concat(a,";\n }\n\n .gleap-notification-item-sender {\n color: ").concat(v,";\n line-height: 20px;\n }\n\n .gleap-notification-item-content {\n line-height: 20px;\n color: ").concat(f,";\n margin-top: 4px;\n min-width: min(200px, 50vw);\n word-wrap: break-word;\n word-break: break-word;\n }\n\n .gleap-frame-container-inner {\n position: relative;\n width: 100%;\n height: calc(100vh - ").concat(130+s,"px);\n max-height: ").concat(700,'px;\n }\n\n .gleap-frame-container--survey .gleap-frame-container-inner {\n height: calc(100vh - 40px);\n }\n \n .gleap-frame-container-inner:before {\n content: " ";\n position: absolute;\n width: 100%;\n height: calc(100% - ').concat(x,"px);\n top: ").concat(x,"px;\n background-color: ").concat(a,";\n z-index: -1;\n }\n \n .gleap-frame-container iframe {\n height: 100% !important;\n width: 100% !important;\n max-width: 100% !important;\n display: block;\n pointer-events: auto;\n }\n \n .gleap-frame-container--hidden {\n display: none !important;\n pointer-events: none;\n animation: none !important;\n }\n \n .bb-feedback-button {\n margin: 0px;\n position: fixed;\n bottom: ").concat(s,"px;\n right: ").concat(i,"px;\n border-radius: 30px;\n cursor: pointer;\n -webkit-tap-highlight-color: transparent;\n background-color: transparent;\n color: #000000;\n z-index: ").concat(2147483630,";\n box-sizing: border-box;\n display: flex;\n align-items: center;\n padding: 0px;\n }\n\n [dir=rtl].bb-feedback-button {\n bottom: ").concat(s,"px;\n right: auto;\n left: ").concat(i,"px;\n }\n \n .bb-feedback-button--bottomleft {\n bottom: ").concat(s,"px;\n right: auto;\n left: ").concat(i,"px;\n }\n\n [dir=rtl].bb-feedback-button--bottomleft {\n bottom: ").concat(s,"px;\n right: ").concat(i,'px;\n left: auto;\n }\n \n .bb-feedback-button--disabled {\n display: none !important;\n }\n\n .bb-feedback-button--hidden {\n display: none !important;\n }\n \n .bb-feedback-button-text {\n padding: 8px 12px;\n display: flex;\n flex-direction: column;\n align-items: flex-start;\n justify-content: center;\n background-color: #fff;\n border-radius: 8px;\n box-shadow: 0px 0px 14px 0px rgba(0, 0, 0, 0.15);\n position: relative;\n z-index: 99;\n }\n \n .bb-feedback-button-text:before {\n content: "";\n position: absolute;\n box-shadow: rgba(0, 0, 0, 0.04) 6px 6px 5px;\n transform: rotate(315deg);\n bottom: 16px;\n right: -4px;\n border-width: 10px;\n border-style: solid;\n border-color: transparent #fff #fff transparent;\n }\n \n .bb-feedback-button--bottomleft .bb-feedback-button-text:before {\n display: none;\n }\n \n .bb-feedback-button-text:after {\n content: "";\n position: absolute;\n bottom: 12px;\n right: 0px;\n background-color: #fff;\n width: 5px;\n height: 30px;\n }\n \n .bb-feedback-button-text-title {\n font-family: sans-serif;\n font-size: 14px;\n color: #666;\n line-height: 18px;\n max-width: 220px;\n }\n \n .bb-feedback-button-text-title b {\n color: #000000;\n font-weight: 600;\n }\n\n .bb-notification-bubble {\n position: absolute;\n top: -5px;\n right: -5px;\n min-width: 20px;\n padding: 0px 4px;\n height: 20px;\n border-radius: 20px;\n background-color: red;\n color: #fff;\n font-size: 11px;\n font-family: sans-serif;\n text-align: center;\n line-height: 20px;\n }\n\n .bb-notification-bubble--hidden {\n display: none;\n }\n \n .bb-feedback-button-icon {\n width: 48px;\n height: 48px;\n border-radius: 48px;\n background-color: #485bff;\n transition: box-shadow, transform 0.2s ease-in-out;\n box-shadow: 0px 1px 3px rgba(0, 0, 0, 0.15), 0px 0px 20px rgba(0, 0, 0, 0.1);\n position: relative;\n }\n \n .bb-feedback-button-classic {\n cursor: pointer;\n -webkit-tap-highlight-color: transparent;\n top: 50%;\n right: 0px;\n position: fixed;\n transform: rotate(-90deg) translate(50%, -50%);\n transform-origin: 100% 50%;\n padding: 9px 20px;\n text-align: center;\n background-color: #485bff;\n border-top-left-radius: 8px;\n border-top-right-radius: 8px;\n font-family: sans-serif;\n font-size: 16px;\n color: #fff;\n box-shadow: 0px 0px 14px 0px rgba(0, 0, 0, 0.25);\n }\n\n [dir=rtl].bb-feedback-button .bb-feedback-button-classic {\n top: 50%;\n left: 0px;\n right: auto;\n transform: rotate(90deg) translate(-50%, -100%);\n transform-origin: 0% 0%;\n }\n \n .bb-feedback-button-classic--left {\n top: 50%;\n left: 0px;\n right: auto;\n transform: rotate(90deg) translate(-50%, -100%);\n transform-origin: 0% 0%;\n }\n\n [dir=rtl].bb-feedback-button .bb-feedback-button-classic--left {\n top: 50%;\n right: 0px;\n left: auto;\n transform: rotate(-90deg) translate(50%, -50%);\n transform-origin: 100% 50%;\n }\n \n .bb-feedback-button-classic--bottom {\n top: auto;\n bottom: 0px;\n transform: none;\n right: ').concat(i,"px;\n left: auto;\n }\n \n [dir=rtl].bb-feedback-button .bb-feedback-button-classic--bottom {\n top: auto;\n bottom: 0px;\n transform: none;\n left: ").concat(i,"px;\n right: auto;\n }\n\n .bb-feedback-button--classic-button-style {\n animation-duration: 0.2s;\n animation-fill-mode: both;\n animation-name: bbFadeInOpacity;\n }\n \n .bb-feedback-button--open.bb-feedback-button--classic-button-style {\n animation-duration: 0.2s;\n animation-fill-mode: both;\n animation-name: bbFadeOutRight;\n }\n \n .bb-feedback-button .bb-logo-logo {\n position: absolute;\n width: 30px;\n height: 30px;\n top: 9px;\n left: 9px;\n object-fit: contain;\n animation-duration: 0.3s;\n animation-fill-mode: both;\n animation-name: bbZoomIn;\n }\n \n .bb-feedback-button .bb-logo-arrowdown {\n position: absolute;\n width: 14px;\n height: 14px;\n top: 17px;\n left: 17px;\n object-fit: contain;\n animation-duration: 0.3s;\n animation-fill-mode: both;\n }\n \n .bb-feedback-button .bb-logo-arrowdown {\n animation-name: bbZoomOut;\n }\n \n .bb-feedback-button--open .bb-logo-arrowdown {\n animation-name: bbZoomIn;\n }\n \n .bb-feedback-button--open .bb-logo-logo {\n animation-name: bbZoomOut;\n }\n \n .bb-feedback-button-icon:hover {\n box-shadow: 0px 1px 3px rgba(0, 0, 0, 0.25), 0px 0px 20px rgba(0, 0, 0, 0.2);\n transform: scale(1.1);\n }\n \n .bb-feedback-button--open .bb-feedback-button-text {\n animation-name: bbFadeOutDown;\n }\n \n .bb-feedback-button--open .bb-feedback-button-icon {\n display: flex;\n }\n \n .bb-capture-svg {\n position: fixed;\n z-index: ").concat(2147483614,";\n top: 0px;\n left: 0px;\n right: 0px;\n width: 100%;\n height: 100%;\n padding: 0px;\n margin: 0px;\n cursor: crosshair;\n }\n\n .bb-capture-svg--preview {\n cursor: auto !important;\n }\n \n .bb-rec-on-circle {\n animation-name: bbRecIconFade;\n animation-duration: 2s;\n animation-iteration-count: infinite;\n animation-direction: alternate;\n }\n \n .bb-rec-on-cont {\n animation-name: bbRecIconContFade;\n animation-duration: 2s;\n animation-iteration-count: infinite;\n animation-direction: alternate;\n }\n \n .bb-capture-editor-drag-info {\n position: fixed;\n top: -200px;\n left: 0px;\n z-index: ").concat(2147483616,";\n transition: opacity 0.3s ease-in-out;\n }\n \n .bb-capture-editor-drag-info svg {\n width: 24px;\n height: 24px;\n }\n \n .bb-capture-editor-borderlayer {\n position: fixed;\n top: 0px;\n left: 0px;\n width: 100vw;\n height: 100vh;\n border: 4px solid ").concat(e,";\n cursor: crosshair;\n z-index: ").concat(2147483610,";\n box-sizing: border-box;\n pointer-events: none;\n }\n \n .bb-capture-editor-notrecording .bb-capture-editor-borderlayer {\n background-color: rgba(0, 0, 0, 0.8);\n }\n\n .bb-capture-editor-recording .bb-capture-editor-borderlayer {\n border: 4px solid #eb144c !important;\n }\n \n .bb-capture-editor-recording .bb-capture-dismiss {\n display: none;\n }\n \n .bb-capture-editor-item-inactive {\n opacity: 0.3;\n cursor: not-allowed !important;\n }\n \n .bb-capture-editor-notrecording .bb-capture-toolbar-drawingitem {\n opacity: 0.3;\n cursor: not-allowed !important;\n }\n \n .bb-capture-editor-notrecording .bb-capture-editor-drag-info {\n display: none;\n }\n \n .bb-capture-editor-notrecording .bb-capture-svg {\n pointer-events: none !important;\n }\n \n .bb-capture-toolbar {\n position: fixed;\n top: 20px;\n left: 50%;\n transform: translateX(-50%);\n z-index: ").concat(2147483618,";\n background-color: #fff;\n padding: 5px;\n display: flex;\n align-items: center;\n border-radius: 8px;\n box-shadow: 0px 1px 3px rgba(0, 0, 0, 0.15), 0px 0px 20px rgba(0, 0, 0, 0.1);\n transition: opacity 0.3s ease-in-out;\n }\n \n .bb-capture-dismiss {\n position: fixed;\n top: 0px;\n right: 0px;\n z-index: ").concat(2147483618,";\n cursor: pointer;\n -webkit-tap-highlight-color: transparent;\n width: 36px;\n height: 36px;\n display: flex;\n justify-content: center;\n align-items: center;\n background-color: ").concat(e,";\n border-bottom-left-radius: ").concat(C,"px;\n }\n\n [dir=rtl] .bb-capture-dismiss {\n top: 0px;\n left: 0px;\n right: auto;\n border-bottom-left-radius: 0px !important;\n border-bottom-right-radius: ").concat(C,"px;\n }\n \n .bb-capture-dismiss svg path {\n fill: ").concat(d,';\n }\n \n .bb-capture-dismiss svg {\n width: 20px;\n height: 20px;\n object-fit: contain;\n }\n \n .bb-capture-button-next {\n font-family: sans-serif;\n box-sizing: border-box;\n font-weight: 600;\n text-align: center;\n width: auto;\n cursor: pointer;\n -webkit-tap-highlight-color: transparent;\n margin: 0px;\n line-height: 36px;\n padding: 0px 12px;\n font-size: 15px;\n margin-left: 12px;\n }\n\n [dir=rtl].bb-capture-editor .bb-capture-button-next {\n margin-left: auto;\n margin-right: 12px;\n }\n \n .bb-capture-toolbar-item-spacer {\n width: 1px;\n height: 38px;\n min-width: 1px;\n margin: 0px 5px;\n }\n \n .bb-capture-toolbar-item {\n width: 42px;\n height: 38px;\n min-width: 42px;\n display: flex;\n align-items: center;\n justify-content: center;\n cursor: pointer;\n -webkit-tap-highlight-color: transparent;\n position: relative;\n margin-right: 5px;\n }\n \n .bb-capture-toolbar-item svg {\n width: 23px;\n height: 23px;\n object-fit: contain;\n }\n \n .bb-capture-toolbar-item-selectedcolor {\n border-radius: 100%;\n width: 20px;\n height: 20px;\n background-color: #db4035;\n }\n \n .bb-capture-toolbar-item[data-type="undo"] svg {\n width: 18px;\n height: 18px;\n }\n \n .bb-capture-toolbar-item[data-active="true"] {\n position: relative;\n }\n \n .bb-capture-preview {\n display: none;\n background-color: rgba(0, 0, 0, 0.6);\n position: fixed;\n top: 0px;\n left: 0px;\n width: 100vw;\n height: 100vh;\n justify-content: center;\n align-items: center;\n z-index: ').concat(2147483620,";\n }\n \n .bb-capture-preview-inner {\n background-color: #fff;\n padding: 0px;\n box-shadow: 0px 1px 3px rgba(0, 0, 0, 0.15), 0px 0px 20px rgba(0, 0, 0, 0.1);\n border-radius: 8px;\n flex-direction: column;\n max-width: 640px;\n width: 100%;\n margin: 20px;\n }\n \n .bb-capture-preview-inner video {\n border-radius: 8px 8px 0px 0px;\n display: block;\n border: 0px;\n outline: none;\n width: 100%;\n max-height: 60vh;\n }\n \n .bb-capture-preview-buttons {\n display: flex;\n justify-content: space-between;\n padding: 14px;\n }\n \n .bb-capture-preview-retrybutton {\n font-family: sans-serif;\n border-radius: 21px;\n box-sizing: border-box;\n padding: 12px 26px;\n font-size: 16px;\n line-height: 19px;\n font-weight: 600;\n text-align: center;\n margin-top: 0px;\n margin-bottom: 0px;\n cursor: pointer;\n -webkit-tap-highlight-color: transparent;\n }\n \n .bb-capture-preview-sendbutton {\n font-family: sans-serif;\n border-radius: 21px;\n box-sizing: border-box;\n padding: 12px 26px;\n font-size: 16px;\n line-height: 19px;\n font-weight: 600;\n text-align: center;\n margin-top: 0px;\n margin-bottom: 0px;\n cursor: pointer;\n -webkit-tap-highlight-color: transparent;\n }\n \n .bb-capture-preview-retrybutton:hover,\n .bb-capture-preview-sendbutton:hover {\n opacity: 0.9;\n }\n \n .bb-capture-toolbar-item-recording {\n margin-right: 0px;\n }\n \n .bb-capture-toolbar-item-recording svg {\n width: 33px;\n height: 33px;\n }\n \n .bb-capture-toolbar-item-colorpicker {\n position: fixed;\n top: 70px;\n left: 50%;\n transform: translateX(-50%);\n z-index: ").concat(2147483618,';\n background-color: #fff;\n display: none;\n padding: 10px;\n box-shadow: 0px 1px 3px rgba(0, 0, 0, 0.15), 0px 0px 20px rgba(0, 0, 0, 0.1);\n border-radius: 8px;\n }\n \n .bb-capture-toolbar-item-color {\n width: 20px;\n height: 20px;\n border-radius: 100%;\n margin-right: 12px;\n box-shadow: 0px 0px 3px rgba(0, 0, 0, 0.15);\n cursor: pointer;\n -webkit-tap-highlight-color: transparent;\n }\n \n .bb-capture-toolbar-item-color:hover {\n box-shadow: 0px 0px 6px rgba(0, 0, 0, 0.25);\n }\n \n .bb-capture-toolbar-item-color:last-of-type {\n margin-right: 0px;\n }\n \n [dir=rtl].bb-capture-editor .bb-capture-toolbar-item-color {\n margin-right: auto;\n margin-left: 12px;\n }\n \n [dir=rtl].bb-capture-editor .bb-capture-toolbar-item-color:last-of-type {\n margin-right: auto;\n margin-left: 0px;\n }\n \n .bb-capture-toolbar-item-recording[data-active="true"] svg:first-of-type {\n display: none;\n }\n \n .bb-capture-toolbar-item-recording[data-active="true"] svg:nth-of-type(2) {\n display: block;\n }\n \n .bb-capture-toolbar-item-recording[data-active="false"] svg:first-of-type {\n display: block;\n }\n \n .bb-capture-toolbar-item-recording[data-active="false"] svg:nth-of-type(2) {\n display: none;\n }\n \n .bb-capture-toolbar-item--active {\n background-color: #eee;\n }\n \n .bb-capture-toolbar-item:hover svg {\n opacity: 1;\n }\n \n .bb-capture-toolbar-item--active {\n background-color: #f8f8f8;\n }\n \n .bb-capture-toolbar-item--active svg {\n opacity: 1;\n }\n \n .bb-capture-toolbar-item--inactivecross::before {\n content: "";\n position: absolute;\n top: 0;\n right: 0;\n bottom: 0;\n left: 0;\n height: 3px;\n width: 26px;\n margin: auto;\n border-radius: 4px;\n background-color: #e80000;\n transform: rotate(45deg);\n }\n \n .bb-capture-toolbar-item--inactivecross svg {\n fill: #eee;\n }\n \n .bb-capture-toolbar-item-timer {\n text-align: left;\n line-height: 32px;\n font-size: 14px;\n font-family: sans-serif;\n margin: 5px;\n min-width: 40px;\n display: none;\n }\n \n .bb-capture-toolbar-item .bb-tooltip {\n background-color: #555;\n color: #fff;\n visibility: hidden;\n font-size: 14px;\n font-family: sans-serif;\n text-align: center;\n padding: 5px 10px;\n position: absolute;\n z-index: 1;\n top: 45px;\n left: 0px;\n transform: translateX(calc(-50% + 21px));\n opacity: 0;\n transition: opacity 0.3s;\n white-space: nowrap;\n }\n \n .bb-capture-toolbar-item .bb-tooltip::after {\n content: "";\n position: absolute;\n bottom: 100%;\n left: 50%;\n margin-left: -5px;\n border-width: 5px;\n border-style: solid;\n transform: rotate(180deg);\n border-color: #555 transparent transparent transparent;\n }\n \n .bb-capture-toolbar-item:hover .bb-tooltip {\n visibility: visible;\n opacity: 1;\n }\n \n .bb-capture-options {\n display: none;\n }\n \n .bb-capture-options--active {\n display: flex;\n }\n\n @keyframes bbFadeOutRight {\n from {\n opacity: 1;\n }\n \n to {\n opacity: 0;\n }\n }\n \n @keyframes bbFadeOutDown {\n from {\n opacity: 1;\n }\n \n to {\n opacity: 0;\n transform: translate3d(0, 100%, 0);\n }\n }\n \n @keyframes bbFadeInOpacity {\n from {\n opacity: 0;\n }\n \n to {\n opacity: 1;\n }\n }\n \n @keyframes bbZoomOut {\n from {\n opacity: 1;\n }\n \n 50% {\n opacity: 0;\n transform: scale3d(0.3, 0.3, 0.3);\n }\n \n to {\n opacity: 0;\n }\n }\n \n @keyframes bbZoomIn {\n from {\n opacity: 0;\n transform: scale3d(0.3, 0.3, 0.3);\n }\n \n 50% {\n opacity: 1;\n }\n }\n \n @keyframes bbRecIconContFade {\n 0% {\n fill: #b10802;\n }\n 50% {\n fill: #ff0000;\n }\n 100% {\n fill: #b10802;\n }\n } \n .bb-capture-preview-retrybutton {\n color: ').concat(f,";\n border-radius: ").concat(w,"px;\n background-color: ").concat(y,";\n }\n .bb-capture-preview-retrybutton:hover {\n background-color: ").concat(b,";\n }\n @keyframes bb-suc-fill {\n 100% {\n box-shadow: inset 0px 0px 0px 30px ").concat(e,";\n }\n }\n .bb-capture-toolbar-item-spacer {\n background-color: ").concat(y,";\n }\n .bb-tooltip {\n border-radius: ").concat(S,"px;\n }\n @keyframes bbRecIconFade {\n 0% {\n fill: transparent;\n }\n 50% {\n fill: ").concat(b,";\n }\n 100% {\n fill: transparent;\n }\n }\n .bb-capture-preview-sendbutton {\n color: ").concat(d,";\n background-color: ").concat(e,";\n border-radius: ").concat(w,"px;\n }\n .bb-capture-button-next {\n color: ").concat(d,";\n background-color: ").concat(e,";\n border-radius: ").concat(C,"px;\n }\n .bb-capture-preview-inner {\n background-color: ").concat(a,";\n border-radius: ").concat(S,"px;\n }\n .bb-capture-toolbar-item-timer {\n color: ").concat(v,";\n }\n .bb-svg-path {\n fill: ").concat(f,";\n }\n .bb-capture-toolbar-item {\n border-radius: ").concat(S,"px;\n }\n .bb-capture-toolbar {\n background-color: ").concat(a,";\n border-radius: ").concat(S,"px;\n }\n .bb-capture-toolbar-item-colorpicker {\n background-color: ").concat(a,";\n }\n .bb-capture-toolbar-item--active {\n background-color: ").concat(y,";\n }\n .bb-feedback-button-classic {\n border-top-left-radius: ").concat(S,"px;\n border-top-right-radius: ").concat(S,"px;\n }\n .bb-logo-logo--default path {\n fill: ").concat(p,";\n }\n .bb-logo-arrowdown {\n fill: ").concat(p,";\n }\n .bb-feedback-button-icon {\n background-color: ").concat(n,";\n }\n .bb-feedback-button-classic {\n background-color: ").concat(n,";\n color: ").concat(p,";\n }\n\n @media only screen and (max-width: 450px) {\n [dir=rtl].gleap-frame-container,\n .gleap-frame-container {\n left: 0px;\n right: 0px;\n width: 100vw;\n max-width: 100vw;\n min-height: 100vh;\n min-height: -webkit-fill-available;\n max-height: -webkit-fill-available;\n top: 0px;\n bottom: 0px;\n border-radius: 0px;\n animation-name: gleapFadeInUpMobile;\n }\n\n .gleap-frame-container-inner {\n width: 100vw;\n height: 100%;\n }\n\n .gleap-frame-container:not(.gleap-frame-container--survey):not(.gleap-frame-container--survey-full) .gleap-frame-container-inner {\n max-height: calc(var(--glvh, 1vh) * 100) !important;\n }\n\n .gleap-frame-container--survey {\n height: auto !important;\n top: initial !important;\n bottom: 0px !important;\n min-height: initial !important;\n }\n\n .gleap-frame-container--survey .gleap-frame-container-inner {\n height: 100vh !important;\n }\n\n .bb-tooltip {\n display: none !important;\n }\n \n .bb-capture-toolbar-item-colorpicker {\n top: 75px;\n }\n \n .bb-capture-button-next {\n margin-left: auto;\n }\n \n .bb-capture-dismiss {\n display: none;\n }\n \n .bb-capture-toolbar {\n top: 15px;\n right: 15px;\n left: 15px;\n width: auto;\n transform: none;\n }\n\n .bb-capture-editor-drag-info {\n display: none;\n }\n \n .bb-capture-editor-borderlayer {\n border-width: 4px;\n }\n }\n \n @media print {\n .bb-feedback-button {\n display: none !important;\n }\n \n .gleap-frame-container {\n display: none !important;\n }\n }\n\n .gleap-tour-sender {\n display: flex;\n align-items: center;\n justify-content: flex-start;\n margin-bottom: 20px;\n }\n\n .gleap-tour-sender-image {\n width: 32px;\n height: 32px;\n border-radius: 32px;\n margin-right: 10px;\n background-size: cover;\n background-repeat: no-repeat;\n }\n\n .gleap-tour-popover.gleap-tour-popover-post {\n min-width: 550px;\n max-width: 550px;\n }\n\n @media only screen and (max-width: 450px) {\n .gleap-tour-popover.gleap-tour-popover-post {\n min-width: calc(100vw - 40px);\n max-width: calc(100vw - 40px);\n }\n }\n\n .gleap-tour-message,\n .gleap-tour-message p,\n .gleap-tour-message ul {\n color: ").concat(f,";\n }\n\n .gleap-tour-message p {\n line-height: 1.3;\n }\n\n .gleap-tour-message ul {\n line-height: 1.3;\n padding-left: 20px;\n margin-top: 10px;\n margin-bottom: 10px;\n }\n\n .gleap-tour-message {\n max-height: calc(80vh - 100px) !important;\n overflow-y: auto;\n min-width: 270px;\n }\n\n .gleap-tour-message iframe {\n width: 100%;\n height: 300px;\n margin-top: 10px;\n margin-bottom: 10px;\n border: none;\n outline: none;\n display: block;\n }\n\n .gleap-tour-sender-name {\n font-size: 15px;\n }\n\n .gleap-tour-video {\n width: 100%;\n max-width: 100%;\n }\n\n .gleap-tour-video--playing .gleap-tour-video-playpause {\n opacity: 0;\n }\n \n .gleap-tour-video--playing:hover .gleap-tour-video-playpause {\n opacity: 1;\n }\n\n .gleap-tour-popover-video-pointer {\n padding: 0px !important;\n border-radius: 8px;\n position: relative;\n background-color: transparent !important;\n }\n\n .gleap-tour-popover-video-pointer .gleap-tour-popover-footer {\n position: absolute;\n top: 0px;\n left: 20px;\n right: 20px;\n opacity: 0;\n transition: opacity 200ms ease-in-out;\n }\n\n .gleap-tour-popover-video-pointer .gleap-tour-popover-footer button {\n padding: 5px 12px;\n }\n\n .gleap-tour-popover-video-pointer.gleap-tour-popover-can-close .gleap-tour-popover-footer {\n right: 40px !important;\n }\n\n .gleap-tour-popover-video-pointer:hover .gleap-tour-popover-footer {\n opacity: 1;\n }\n\n .gleap-tour-popover-pointer.gleap-tour-popover-no-sender .gleap-tour-message {\n padding-right: 20px;\n }\n\n .gleap-tour-video video {\n width: 100%;\n max-width: 100%;\n height: auto;\n border: none;\n outline: none;\n display: block;\n border-radius: 8px;\n }\n\n .gleap-admin-collapse-ui {\n z-index: ").concat(2147483635,";\n cursor: pointer;\n position: fixed;\n bottom: 75px;\n right: 20px;\n width: 32px;\n height: 32px;\n border-radius: 100%;\n background-color: #fff;\n display: flex;\n justify-content: center;\n align-items: center;\n box-shadow: rgba(0, 0, 0, 0.16) 0px 10px 36px 0px, rgba(0, 0, 0, 0.06) 0px 0px 0px 1px;\n }\n\n .gleap-admin-collapse-ui svg {\n width: 20px;\n height: 14px;\n margin-top: 6px;\n fill: #000 !important;\n }\n\n .gleap-admin-collapse-ui-active {\n bottom: 20px !important;\n }\n\n .gleap-admin-collapse-ui-active svg {\n transform: rotate(180deg);\n }\n\n .gleap-admin-frame-container-active {\n display: none !important;\n }\n\n .gleap-admin-frame-container {\n position: fixed;\n bottom: 0px;\n left: 0px;\n right: 0px;\n width: 100vw;\n z-index: ").concat(2147483640,";\n }\n\n .gleap-admin-frame {\n width: 100%;\n height: 100%;\n border: none;\n outline: none;\n display: block;\n }\n \n .gleap-tour-message .linktype-link {\n display: inline-block !important;\n background-color: transparent !important;\n color: ").concat(n," !important;\n }\n\n .gleap-tooltip .linktype-button,\n .gleap-tour-message .linktype-button {\n display: inline-block !important;\n border-radius: 5px;\n box-sizing: border-box;\n padding: 10px 20px !important;\n text-decoration: none !important;\n background-color: ").concat(n," !important;\n color: ").concat(p," !important;\n }\n\n .gleap-tour-message img {\n width: 100%;\n max-width: 100%;\n min-height: 260px;\n height: auto;\n margin-top: 10px;\n margin-bottom: 10px;\n object-fit: cover;\n }\n\n .gleap-tour-active .gleap-tour-overlay {\n pointer-events: none;\n }\n \n .gleap-tour-active * {\n pointer-events: none;\n }\n \n .gleap-tour-active .gleap-tour-active-element,\n .gleap-tour-active .gleap-tour-active-element *,\n .gleap-tour-popover,\n .gleap-tour-popover * {\n pointer-events: auto;\n }\n \n @keyframes animate-fade-in {\n 0% {\n opacity: 0;\n }\n \n to {\n opacity: 1;\n }\n }\n \n .gleap-tour-fade .gleap-tour-overlay {\n animation: animate-fade-in 200ms ease-in-out;\n }\n \n .gleap-tour-fade .gleap-tour-popover {\n animation: animate-fade-in 200ms;\n }\n\n .gleap-tour-video-playpause {\n position: absolute;\n top: 0px;\n left: 0px;\n right: 0px;\n width: 100%;\n height: 100%;\n background-color: rgba(0,0,0,0.5);\n display: flex;\n align-items: center;\n justify-content: center;\n cursor: pointer;\n border-radius: 8px;\n transition: opacity 200ms ease-in-out;\n }\n\n .gleap-tour-popover-video-pointer .gleap-tour-popover-arrow {\n display: none !important;\n }\n\n .gleap-tour-video-playpause svg {\n width: 34px;\n height: auto;\n fill: #fff;\n }\n \n /* Popover styles */\n .gleap-tour-popover {\n all: unset;\n box-sizing: border-box;\n color: #2d2d2d;\n margin: 0;\n padding: 15px;\n border-radius: ").concat(S,'px;\n min-width: 250px;\n max-width: 300px;\n box-shadow: 0 1px 10px #0006;\n z-index: 1000000000;\n position: fixed;\n top: 0;\n right: 0;\n background-color: #fff;\n }\n \n .gleap-tour-popover * {\n font-family: "Helvetica Neue", Inter, ui-sans-serif, "Apple Color Emoji", Helvetica, Arial, sans-serif;\n }\n \n .gleap-tour-popover-title {\n font: 19px / normal sans-serif;\n font-weight: 700;\n display: block;\n position: relative;\n line-height: 1.5;\n zoom: 1;\n margin: 0;\n }\n \n .gleap-tour-popover-close-btn {\n all: unset;\n position: absolute;\n top: 5px;\n right: 5px;\n width: 32px;\n height: 32px;\n cursor: pointer;\n font-size: 30px;\n font-weight: 500;\n line-height: 32px;\n color: #d2d2d2;\n z-index: 1;\n text-align: center;\n transition: color;\n transition-duration: 200ms;\n }\n \n .gleap-tour-popover-close-btn:hover,\n .gleap-tour-popover-close-btn:focus {\n color: #2d2d2d;\n }\n \n .gleap-tour-popover-title[style*="block"] + .gleap-tour-popover-description {\n margin-top: 5px;\n }\n \n .gleap-tour-popover-description {\n margin-bottom: 0;\n font: 15px / normal sans-serif;\n line-height: 1.5;\n font-weight: 400;\n zoom: 1;\n }\n \n .gleap-tour-popover-footer {\n margin-top: 15px;\n text-align: right;\n zoom: 1;\n display: flex;\n align-items: center;\n justify-content: space-between;\n }\n \n .gleap-tour-popover-progress-text {\n font-size: 13px;\n font-weight: 400;\n color: #727272;\n zoom: 1;\n }\n \n .gleap-tour-popover-footer button {\n background-color: ').concat(e,";\n color: ").concat(d,";\n border-radius: ").concat(C,"px;\n box-sizing: border-box;\n padding: 10px 20px;\n font-size: 14px;\n font-weight: bold;\n line-height: 21px;\n border: none;\n text-align: center;\n cursor: pointer;\n -webkit-tap-highlight-color: transparent;\n display: flex;\n justify-content: center;\n align-items: center;\n box-shadow: none !important;\n outline: none !important;\n }\n\n .gleap-tour-popover-prev-btn {\n color: ").concat(f," !important;\n background-color: ").concat(y," !important;\n margin-right: 3px;\n }\n\n .gleap-tour-popover-prev-btn:hover {\n background-color: ").concat(e,"22 !important;\n color: ").concat(e,' !important;\n }\n \n .gleap-tour-popover-footer .gleap-tour-popover-btn-disabled {\n opacity: 0.5;\n pointer-events: none;\n }\n \n /* Disable the scrolling of parent element if it has an active element*/\n :not(body):has(> .gleap-tour-active-element) {\n overflow: hidden !important;\n }\n \n .gleap-tour-no-interaction, .gleap-tour-no-interaction * {\n pointer-events: none !important;\n }\n \n .gleap-tour-popover-navigation-btns {\n display: flex;\n flex-grow: 1;\n justify-content: flex-end;\n }\n \n .gleap-tour-popover-navigation-btns button + button {\n margin-left: 4px;\n }\n \n .gleap-tour-popover-arrow {\n content: "";\n position: absolute;\n border: 5px solid #fff;\n }\n \n .gleap-tour-popover-arrow-side-over {\n display: none;\n }\n \n /** Popover Arrow Sides **/\n .gleap-tour-popover-arrow-side-left {\n left: 100%;\n border-right-color: transparent;\n border-bottom-color: transparent;\n border-top-color: transparent;\n }\n \n .gleap-tour-popover-arrow-side-right {\n right: 100%;\n border-left-color: transparent;\n border-bottom-color: transparent;\n border-top-color: transparent;\n }\n \n .gleap-tour-popover-arrow-side-top {\n top: 100%;\n border-right-color: transparent;\n border-bottom-color: transparent;\n border-left-color: transparent;\n }\n \n .gleap-tour-popover-arrow-side-bottom {\n bottom: 100%;\n border-left-color: transparent;\n border-top-color: transparent;\n border-right-color: transparent;\n }\n \n .gleap-tour-popover-arrow-side-center {\n display: none;\n }\n \n /* Left/Start + Right/Start */\n .gleap-tour-popover-arrow-side-left.gleap-tour-popover-arrow-align-start,\n .gleap-tour-popover-arrow-side-right.gleap-tour-popover-arrow-align-start {\n top: 15px;\n }\n \n /* Top/Start + Bottom/Start */\n .gleap-tour-popover-arrow-side-top.gleap-tour-popover-arrow-align-start,\n .gleap-tour-popover-arrow-side-bottom.gleap-tour-popover-arrow-align-start {\n left: 15px;\n }\n \n /* End/Left + End/Right */\n .gleap-tour-popover-arrow-align-end.gleap-tour-popover-arrow-side-left,\n .gleap-tour-popover-arrow-align-end.gleap-tour-popover-arrow-side-right {\n bottom: 15px;\n }\n \n /* Top/End + Bottom/End */\n .gleap-tour-popover-arrow-side-top.gleap-tour-popover-arrow-align-end,\n .gleap-tour-popover-arrow-side-bottom.gleap-tour-popover-arrow-align-end {\n right: 15px;\n }\n \n /* Left/Center + Right/Center */\n .gleap-tour-popover-arrow-side-left.gleap-tour-popover-arrow-align-center,\n .gleap-tour-popover-arrow-side-right.gleap-tour-popover-arrow-align-center {\n top: 50%;\n margin-top: -5px;\n }\n \n /* Top/Center + Bottom/Center */\n .gleap-tour-popover-arrow-side-top.gleap-tour-popover-arrow-align-center,\n .gleap-tour-popover-arrow-side-bottom.gleap-tour-popover-arrow-align-center {\n left: 50%;\n margin-left: -5px;\n }\n \n /* No arrow */\n .gleap-tour-popover-arrow-none {\n display: none;\n } \n '),L=document.querySelector(".gleap-styles");L&&L.remove();var I=document.createElement("style");I.innerHTML=T,I.className="gleap-styles",document.body.appendChild(I)}(e,t,n,a,r,i,s,u)}))}},{key:"sendSilentCrashReport",value:function(){var t=arguments.length>0&&void 0!==arguments[0]?arguments[0]:"",n=arguments.length>1&&void 0!==arguments[1]?arguments[1]:"MEDIUM",r=arguments.length>2&&void 0!==arguments[2]?arguments[2]:{screenshot:!0,replays:!0,attachments:!0};return e.sendSilentCrashReportWithFormData({description:t},n,r)}},{key:"sendSilentCrashReportWithFormData",value:function(e){var t=this,n=arguments.length>1&&void 0!==arguments[1]?arguments[1]:"MEDIUM",r=arguments.length>2&&void 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