Column Metadata

Sometimes it can be useful to attach user-provided metadata to columns of tables. The metadata parameter is available for all column types and accepts a dictionary of arbitrary objects. For instance, one may use the metadata parameter to mark a column as pseudonymized or provide other context-specific information.

class UserSchema(dy.Schema):
    id = dy.String(primary_key=True)
    # Mark last name column as pseudonymized and (non-docstring) comment on it.
    last_name = dy.String(metadata={
        "pseudonymized": True,
        "comment": "Pseudonymized using cryptographic hash function"
    })
    # Add information about database column type.
    address = dy.String(metadata={"database-type": "VARCHAR(MAX)"})

>>> print(UserSchema.last_name.metadata)
{'pseudonymized': True, 'comment': 'Pseudonymized using cryptographic hash function'}

Metadata are never read by dataframely and merely enable users to provide custom information in a structured way.

Note

User-provided metadata can be useful for code generation. For instance, one could specify metadata for columns, such as database column types or constraints, and override the built-in SQLAlchemy generation for more tailored SQL output.