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You can now add additional fields, and compose more queries together!

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The server starts with the schema provided and prints out a load of meta information. We will cover those in detail in a bit. For now, open the playground URL in a new tab in your browser and try it out for yourself!

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This command prompts for additional file creation and configuration, creating a .tailcallrc.graphql file by default.

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In summary, the key to maximizing HTTP client performance lies in understanding the underlying protocols and thoughtful configuration of client settings through test. By doing so, developers can ensure efficient, robust, and high-performing client-server communication, essential for the smooth operation of modern web applications.

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Here, headers.userId refers to a header called userId that should be present in the context. The server can use this userId to fetch comments for the specified user.

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By following these practices, you can effectively manage and secure your environment variables.

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info

Log levels are flexible and can be provided in either uppercase or lowercase. For instance, setting TAILCALL_LOG_LEVEL=DEBUG or TAILCALL_LOG_LEVEL=debug will yield the same result.

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By using this approach, you can reduce the number of requests from 101 (for 100 posts plus one initial request for the post list) to just 2. This significant optimization effectively handles the N+1 problem, thereby enhancing your application's efficiency and user experience.

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This is a powerful mechanism that allows you to make your GraphQL schema more precise, easier to understand, and more suitable for the specific needs of your application.

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By following these best practices and using entr effectively, you can significantly improve your development workflow. Experiment with entr, adapt it to your project's specific requirements, and enjoy a smoother and more efficient development process. Happy coding!

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Further enhancing its capabilities, Tailcall's DSL supports sophisticated API Orchestration, going beyond mere request routing. It enables you to define the expected API structure and provides guidance on resolving each component within the entity type. For instance, consider a transaction API containing a userId. Traditionally, expanding this userId to retrieve the corresponding user details would require additional micro-services. However, with Tailcall, expressing this requirement through its DSL prompts the Tailcall runtime to automatically resolve and populate these details for you. This approach eliminates the need for any manual coding, streamlining the API management process significantly.

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In conclusion, the @addField operator helps tidy up your schema and streamline data fetching by reducing query depth, promoting better performance and simplicity.

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If @cache is set for a query or a field, the resolver for it will run once and the result will be stored in memory for maxAge milliseconds, and will expire after this duration. After the cache expires, the resolver will be run again to fetch the latest value and that value will then be cached.

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@const

The @const operators allows us to embed a constant response for the schema. For eg:

schema {
  query: Query
}

type Query {
  user: User @const(data: {name: "John", age: 12})
}

type User {
  name: String
  age: Int
}
-

The const operator will also validate the provided value at compile time to make sure that it matches the of the field. If the schema of the provided value doesn't match the type of the field, a descriptive error message is show on the console.

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The const operator will also validate the provided value at compile time to make sure that it matches the of the field. If the schema of the provided value doesn't match the type of the field, a descriptive error message is show on the console.

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Make sure you have also specified batch settings to the @upstream and to the @graphQL operator.

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The @grpc operator is a powerful tool for GraphQL developers, allowing for seamless integration with gRPC services. By understanding and utilizing its various fields, developers can create efficient, streamlined APIs that leverage the strengths of both GraphQL and gRPC.

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Operators

Tailcall DSL builds on your existing GraphQL knowledge by allowing the addition of some custom operators. These operators provide powerful compile time guarantees to make sure your API composition is tight and robust. The operator information is used to automatically generate highly optimized resolver logic for your types.

Here is a list of all the custom operators supported by Tailcall:

Certainly! Here's the table with hyperlinks added back to the operator names:

-
OperatorDescription
@addFieldSimplifies data structures and queries by adding, inlining, or flattening fields or nodes within the schema.
@cacheEnables caching for the query, field or type it is applied to.
@constAllows embedding of a constant response within the schema.
@graphQLResolves a field or node by a GraphQL API.
@grpcResolves a field or node by a gRPC API.
@httpResolves a field or node by a REST API.
@modifyEnables changes to attributes of fields or nodes in the schema.
@serverProvides server configurations for behavior tuning and tailcall optimization in various use-cases.
@upstreamControls aspects of the upstream server connection, including timeouts and keep-alive settings.
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OperatorDescription
@addFieldSimplifies data structures and queries by adding, inlining, or flattening fields or nodes within the schema.
@cacheEnables caching for the query, field or type it is applied to.
@constAllows embedding of a constant response within the schema.
@graphQLResolves a field or node by a GraphQL API.
@grpcResolves a field or node by a gRPC API.
@httpResolves a field or node by a REST API.
@modifyEnables changes to attributes of fields or nodes in the schema.
@serverProvides server configurations for behavior tuning and tailcall optimization in various use-cases.
@upstreamControls aspects of the upstream server connection, including timeouts and keep-alive settings.
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@modify(omit: true) tells GraphQL that the id field should not be included in the schema, thus it won't be accessible to the client.

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Batching can improve performance but may introduce latency if one request in the batch takes longer. It also makes network traffic debugging harder.

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schema @upstream(batch: {maxSize: 1000, delay: 10, headers: ["X-Server", "Authorization"]}) {
  query: Query
  mutation: Mutation
}
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