refactor validators to be decorator

README.md

@@ -52,30 +52,26 @@ With your schemas defined in code, you can now take advantage of the additional
 1. Entity validation: Easily create custom validation rules for your Benchling entities.
 
     ```python
-    from liminal.validation import BenchlingValidator, BenchlingValidatorReport, BenchlingReportLevel
-    from liminal.orm.base_model import BaseModel
-
-    class CookTempValidator(BenchlingValidator):
-        """Validates that a field value is a valid enum value for a Benchling entity"""
-
-        def validate(self, entity: type[BaseModel]) -> BenchlingValidatorReport:
-            valid = True
-            message = None
-            if entity.cook_time is not None and entity.cook_temp is None:
-                valid = False
-                message = "Cook temp is required if cook time is set"
-            if entity.cook_time is None and entity.cook_temp is not None:
-                valid = False
-                message = "Cook time is required if cook temp is set"
-            return self.create_report(valid, BenchlingReportLevel.MED, entity, message)
+    from liminal.validation import ValidationSeverity, liminal_validator
+
+    class Pizza(BaseModel, CustomEntityMixin):
+        ...
+
+        @liminal_validator(ValidationSeverity.MEDIUM)
+        def cook_time_and_temp_validator(self) -> None:
+            if self.cook_time is not None and self.cook_temp is None:
+                raise ValueError("Cook temp is required if cook time is set")
+            if self.cook_time is None and self.cook_temp is not None:
+                raise ValueError("Cook time is required if cook temp is set")
+
+    validation_reports = Pizza.validate(session)
     ```
 
 2. Strongly typed queries: Write type-safe queries using SQLAlchemy to access your Benchling entities.
 
     ```python
     with BenchlingSession(benchling_connection, with_db=True) as session:
         pizza = session.query(Pizza).filter(Pizza.name == "Margherita").first()
-        print(pizza)
     ```
 
 3. CI/CD integration: Use Liminal to automatically generate and apply your revision files to your Benchling tenant(s) as part of your CI/CD pipeline.

docs/getting-started/tutorials.md

@@ -1 +1 @@
-🚧 Video tutorial coming soon! Come back 11.8.2024 🚧
+🚧 Video tutorial coming soon! 🚧

docs/reference/entity-schemas.md

@@ -178,44 +178,6 @@ multi_relationship(target_class_name: str, current_class_name: str, entity_link_
 
 The `query()` method must be implemented for the entity schema class to define a custom query. This is useful if you want to add additional filtering or joins to the query.
 
-## Validators: [class](https://github.com/dynotx/liminal-orm/blob/main/liminal/validation/__init__.py)
-
-As seen in the example above, the `get_validators` method is used to define a list of validators for the entity schema. These validators run on entities of the schema that are queried from Benchling's Postgres database. For example:
-
-```python
-pizza_entity = Pizza.query(session).first()
-
-# Validate a single entity from a query
-report = CookTempValidator().validate(pizza_entity)
-
-# Validate all entities for a schema
-reports = Pizza.validate(session)
-```
-
-The list of validators within `get_validators` are used to run on all entities of the schema.
-
-The `BenchlingValidator` object is used to define the validator classes, that can be defined with custom logic to validate entities of a schema. Refer to the [Validators](./validators.md) page to learn more about how to define validators.
-
-## Additional Functionality
-
-Below is additional functionality that is provided by the Liminal BaseModel class.
-
-```python
-connection = BenchlingConnection(...)
-benchling_service = BenchlingService(connection, use_db=True)
-
-with benchling_service as session:
-
-    # Get all entities for a schema and return a dataframe
-    df = Pizza.df(session)
-
-    # Validate all entities for a schema and return a list of ValidatorReports
-    reports = Pizza.validate(session)
-
-    # Validate all entities for a schema and return a dataframe
-    validated_df = Pizza.validate_to_df(session)
-```
-
 ## Notes
 
 - Note that the Entity Schema definition in Liminal does not cover 100% of the properties that can be set through the Benchling website. However, the goal is to have 100% parity! If you find any missing properties that are not covered in the definition or migration service, please open an issue on [Github](https://github.com/dynotx/liminal-orm/issues). In the meantime, you can manually set the properties through the Benchling website.

docs/reference/validation.md

@@ -0,0 +1,141 @@
+When using Benchling to store essential data, it is important to validate the data to ensure it is accurate and consistent. Liminal provides a way to validate entities that follow key business logic by defining validators. Below is an example of a Liminal Validator that validates the cook temp of a pizza. Validators must be defined within the entity schema, and run on data queried from the warehouse.
+
+## Defining a Liminal Validator [decorator](https://github.com/dynotx/liminal-orm/blob/main/liminal/validation/__init__.py#L61)
+
+Any function decorated with `liminal_validator` are detected as validators for the entity schema.
+Each validator returns a `BenchlingValidatorReport` object per entity it is run on, with either `valid=True` or `valid=False`.
+
+```python
+from liminal.validation import ValidationSeverity, liminal_validator
+
+class Pizza(BaseModel, CustomEntityMixin):
+    ...
+
+    @liminal_validator(ValidationSeverity.MEDIUM)
+    def cook_time_and_temp_validator(self) -> None:
+        if self.cook_time is not None and self.cook_temp is None:
+            raise ValueError("Cook temp is required if cook time is set")
+        if self.cook_time is None and self.cook_temp is not None:
+            raise ValueError("Cook time is required if cook temp is set")
+```
+
+### Parameters
+
+**validator_level: ValidationSeverity**
+
+> The severity of the validator. Defaults to `ValidationSeverity.LOW`.
+
+**validator_name: str | None**
+
+> The name of the validator. Defaults to the pascalized name of the function.
+
+## BenchlingValidatorReport: [class](https://github.com/dynotx/liminal-orm/blob/main/liminal/validation/__init__.py#L13)
+
+### Parameters
+
+**valid : bool**
+
+> Indicates whether the validation passed or failed.
+
+**model : str**
+
+> The name of the model being validated. (eg: Pizza)
+
+**level : ValidationSeverity**
+
+> The severity level of the validation report.
+
+**validator_name : str | None**
+
+> The name of the validator that generated this report. (eg: CookTimeAndTempValidator)
+
+**entity_id : str | None**
+
+> The entity ID of the entity being validated.
+
+**registry_id : str | None**
+
+> The registry ID of the entity being validated.
+
+**entity_name : str | None**
+
+> The name of the entity being validated.
+
+**message : str | None**
+
+> A message describing the result of the validation.
+
+**creator_name : str | None**
+
+> The name of the creator of the entity being validated.
+
+**creator_email : str | None**
+
+> The email of the creator of the entity being validated.
+
+**updated_date : datetime | None**
+
+> The date the entity was last updated.
+
+## Running Validation
+
+To run validation using Liminal, you can call the `validate()` method on the entity schema.
+
+```python
+with BenchlingSession(benchling_connection, with_db=True) as session:
+    reports = Pizza.validate(session)
+```
+
+### Parameters
+
+**session : Session**
+
+> The Benchling database session.
+
+**base_filters: BaseValidatorFilters | None**
+
+> Filters to apply to the query.
+
+**only_invalid: bool**
+
+> If True, only returns reports for entities that failed validation.
+
+### Returns
+
+**list[BenchlingValidatorReport]**
+
+> List of reports from running all validators on all entities returned from the query.
+
+!!! note
+    The `validate_to_df` method returns a pandas dataframe with all the reports.
+
+## BaseValidatorFilters: [class](https://github.com/dynotx/liminal-orm/blob/main/liminal/base/base_validation_filters.py)
+
+This class is used to pass base filters to benchling warehouse database queries.
+These columns are found on all tables in the benchling warehouse database.
+
+### Parameters
+
+**created_date_start: date | None**
+
+> Start date for created date filter.
+
+**created_date_end: date | None**
+
+> End date for created date filter.
+
+**updated_date_start: date | None**
+
+> Start date for updated date filter.
+
+**updated_date_end: date | None**
+
+> End date for updated date filter.
+
+**entity_ids: list[str] | None**
+
+> List of entity IDs to filter by.
+
+**creator_full_names: list[str] | None**
+
+> List of creator full names to filter by.

liminal/base/base_validation_filters.py

@@ -7,6 +7,21 @@ class BaseValidatorFilters(BaseModel):
     """
     This class is used to pass base filters to benchling warehouse database queries.
     These columns are found on all tables in the benchling warehouse database.
+
+    Parameters
+    ----------
+    created_date_start: date | None
+        Start date for created date filter.
+    created_date_end: date | None
+        End date for created date filter.
+    updated_date_start: date | None
+        Start date for updated date filter.
+    updated_date_end: date | None
+        End date for updated date filter.
+    entity_ids: list[str] | None
+        List of entity IDs to filter by.
+    creator_full_names: list[str] | None
+        List of creator full names to filter by.
     """
 
     created_date_start: date | None = None

liminal/enums/__init__.py

@@ -4,5 +4,4 @@
 from liminal.enums.benchling_field_type import BenchlingFieldType
 from liminal.enums.benchling_folder_item_type import BenchlingFolderItemType
 from liminal.enums.benchling_naming_strategy import BenchlingNamingStrategy
-from liminal.enums.benchling_report_level import BenchlingReportLevel
 from liminal.enums.benchling_sequence_type import BenchlingSequenceType

liminal/external/__init__.py

@@ -29,6 +29,5 @@
     BenchlingFieldType,
     BenchlingFolderItemType,
     BenchlingNamingStrategy,
-    BenchlingReportLevel,
     BenchlingSequenceType,
 )