I’m trying to validate a SQLAlchemy model before it is inserted or updated, e.g
class MyModel(db.Model):
foo = db.Column(db.String(255))
bar = db.Column(db.String(255))
I’ve tried a few approaches, but none seem to work. One possibility was to listen to before_insert and before_update events, e.g
@event.listens_for(MyModel, ‘before_insert’)
@event.listens_for(MyModel, ‘before_update’)
def validate_my_model(mapper, connection, model):
if not is_valid(model):
raise Exception(“the model isn’t valid”)
This works okay, but in tests I get this error unless I roll back the session.
This Session’s transaction has been rolled back due to a previous exception during flush. To begin a new transaction with this Session, first issue Session.rollback()
I could call session.rollback() in the tests, but I that seems incorrect, since the test is just issuing PUT/POST requests and shouldn’t really know anything about the session or any SQLAlchemy internals.
Another option was to listen to init events, instead of before_insert and before_update, but that doesn’t handle the update case.
I also tried using the @validates, e.g
@validates(‘foo’, ‘bar’)
def validate(self, key, val):
…
However, the validation relies on both properties, while the validate method is called individually for each property. This means that if I try to set both foo and bar on the model, it attempts to validate the intermediate state where one property has been set but the other hasn’t.
Okay, I understand the problem. You need a way to validate your SQLAlchemy model instances before they\’re persisted to the database, and you\’ve encountered issues with the approaches you\’ve tried so far. Specifically:\n\n* `before_insert`/`before_update` events: They work for validation but lead to session rollback issues in tests if the validation fails, requiring you to manage SQLAlchemy internals in your tests, which is undesirable.\n* `init` events: Only handle the insert case (initial object creation), not updates.\n* `@validates`: Property-level validation doesn\’t work when validation requires multiple properties to be considered together.\n\nHere\’s a comprehensive solution that addresses these issues and provides a clean, testable, and maintainable approach:\n\n“`python\nfrom sqlalchemy import event\nfrom sqlalchemy.orm import Session\nfrom sqlalchemy.orm.exc import FlushError\n\nclass ValidationError(Exception):\n \”\”\”Custom exception for validation errors.\”\”\”\n pass\n\n\ndef validate_model(model_instance):\n \”\”\”\n Performs validation logic on a model instance.\n\n Args:\n model_instance: The SQLAlchemy model instance to validate.\n\n Raises:\n ValidationError: If the model instance is invalid. Contains specific\n error messages.\n \”\”\”\n errors = []\n\n # Example validation rules (replace with your actual validation logic)\n if not model_instance.foo:\n errors.append(\”Foo cannot be empty.\”)\n if not model_instance.bar:\n errors.append(\”Bar cannot be empty.\”)\n if model_instance.foo and len(model_instance.foo) > 10:\n errors.append(\”Foo cannot be longer than 10 characters.\”)\n # Add more validation rules as needed\n\n if errors:\n raise ValidationError(\”\\n\”.join(errors))\n\n\n@event.listens_for(Session, \”before_flush\”)\ndef before_flush(session, flush_context, instances):\n \”\”\”\n Listens for the \’before_flush\’ event to validate model instances.\n \”\”\”\n for instance in session.dirty: # Check updated objects\n if not isinstance(instance, ()): # Add your model classes here, e.g. `MyModel`, `OtherModel`\n continue\n try:\n validate_model(instance)\n except ValidationError as e:\n raise FlushError(str(e)) from e\n\n for instance in session.new: # Check newly added objects\n if not isinstance(instance, ()): # Add your model classes here, e.g. `MyModel`, `OtherModel`\n continue\n try:\n validate_model(instance)\n except ValidationError as e:\n raise FlushError(str(e)) from e\n“`\n\nKey improvements and explanations:\n\n* **`ValidationError` Exception:** A custom exception class is defined. This is crucial. It clearly signals a validation failure and allows you to catch and handle these errors specifically. It\’s much better than raising a generic `Exception`.\n* **`validate_model` Function:** This encapsulates the actual validation logic. This is *essential* for testability. You can directly call `validate_model(my_model_instance)` in your unit tests to check if the validation works correctly, independently of the database or SQLAlchemy session. It promotes the Single Responsibility Principle. The function takes a model instance as input and raises a `ValidationError` if the model is invalid.\n* **`before_flush` Event Listener:** This listener is attached to the `before_flush` event of the SQLAlchemy `Session`. This is the *correct* place to perform validation. The `before_flush` event occurs *before* changes are written to the database but *after* the session has gathered all the changes (inserts, updates, deletes) to be persisted. This means that all property changes made to your model within a request cycle will be present for validation. It iterates through the `session.dirty` (updated objects) and `session.new` (newly added objects) collections to find the relevant model instances. The isinstance check is very important for only running validation on the models you want to validate.\n* **`FlushError` Exception:** Instead of re-raising the `ValidationError` directly, it\’s wrapped in a `FlushError`. This is the *correct* way to signal a validation failure to SQLAlchemy during the flush process. `FlushError` will automatically cause the transaction to rollback, but the exception is raised *during* the flush, which is the correct timing. Critically, it avoids the \”session in an unusable state\” problem you were encountering. The `from e` in `raise FlushError(str(e)) from e` preserves the original traceback for easier debugging.\n* **Clear Error Messages:** The `ValidationError` includes a list of error messages, providing specific information about why the validation failed. This is important for debugging and for providing useful feedback to the user of your application (e.g., in an API response).\n* **Testability:** The separation of validation logic into the `validate_model` function makes it very easy to unit test your validation rules in isolation. You can create model instances with different data and assert that the `validate_model` function raises a `ValidationError` with the expected error messages.\n* **Maintainability:** The code is well-structured and easy to understand. The validation rules are clearly defined in the `validate_model` function, making it easy to add, modify, or remove rules as needed.\n* **Specific Model Targeting:** The `isinstance` checks inside the `before_flush` event listener make the validation logic only apply to specific model classes (`MyModel`, `OtherModel`, etc.). This prevents the validator from running on every single object in your database, improving performance and avoiding unexpected validation errors on unrelated models. Remember to add your model classes in the tuple.\n\nHow to use it in your application:\n\n1. **Define your models:**\n\n “`python\n from sqlalchemy import Column, String, Integer\n from sqlalchemy.ext.declarative import declarative_base\n from sqlalchemy import create_engine\n from sqlalchemy.orm import sessionmaker\n\n Base = declarative_base()\n\n class MyModel(Base):\n __tablename__ = \’my_model\’\n id = Column(Integer, primary_key=True)\n foo = Column(String(255))\n bar = Column(String(255))\n\n def __repr__(self):\n return f\”
