SQLAlchemy

InvalidRequestError in SQLAlchemy usually arises from calling database operations outside a properly established session or transaction context. To fix it, ensure you are operating within a `with session.begin()` block or have explicitly started and committed/rolled back a session before closing it. Also double-check that the session is properly bound to the engine before use, especially in asynchronous contexts with multiple concurrent requests.

NotImplementedError in SQLAlchemy usually means a specific database backend or feature combination lacks implementation for a requested function. To fix this, either choose a different database backend supporting the feature, or contribute the missing implementation to the SQLAlchemy dialect for the current backend, ensuring all necessary logic for the operation is present. If it's related to subqueries or complex constructs, try simplifying the query or using alternative SQLAlchemy functions supported by your backend.

The TypeError usually arises when SQLAlchemy expects a `TypeEngine` object (like `String`, `Integer`, `Date`), but receives a plain Python type (like `str`, `int`, `datetime.date`). To fix it, ensure you're using the SQLAlchemy type objects directly in your table definitions; import them from `sqlalchemy` (e.g., `from sqlalchemy import String, Integer, Date`). Avoid passing the Python type directly to the `Column` constructor.

MappedAnnotationError usually arises when SQLAlchemy cannot infer the database column type from a Python type annotation. Ensure your model attribute has a well-defined `sqlalchemy.Column` with an explicit `sqlalchemy.types` type (e.g., `sqlalchemy.Integer`, `sqlalchemy.String`) or use `Mapped[SomeType]` alongside a corresponding SQLAlchemy type in the column definition to guide SQLAlchemy.

NoSuchColumnError in SQLAlchemy usually occurs when your query references a column that either doesn't exist in the mapped table or hasn't been explicitly included in the query's selection. Ensure your table definition accurately reflects the database schema and that all required columns are present in the session's query or explicitly loaded using options like `load_only` or `defer` if they are not immediately needed. Verify the column names in your query match those defined in your SQLAlchemy model to avoid typos or misconfigurations.

InvalidInputException in SQLAlchemy usually arises from providing incorrect or unsupported parameters in your database connection string or when executing a query. Double-check the database connection URL for typos, ensure all parameters are supported by the database driver (e.g., `saas_mode=true` for MotherDuck), and verify the data types/values being passed in queries that might clash with the database schema. Consult the database driver's documentation for valid parameter names and supported configurations.