Reflection

The reflection module contains helpers for introspecting existing databases. This module is used internally by several other modules in the playhouse, including DataSet and pwiz, a model generator.

class Introspector(metadata[, schema=None])

Metadata can be extracted from a database by instantiating an Introspector. Rather than instantiating this class directly, it is recommended to use the factory method from_database().

• classmethod from_database(database[, schema=None])

  Parameters:	database – a Database instance. schema (str) – an optional schema (supported by some databases).

  Creates an Introspector instance suitable for use with the given database.

  Usage:

  db = SqliteDatabase('my_app.db')
  introspector = Introspector.from_database(db)
  models = introspector.generate_models()
  # User and Tweet (assumed to exist in the database) are
  # peewee Model classes generated from the database schema.
  User = models['user']
  Tweet = models['tweet']

• generate_models([skip_invalid=False[, table_names=None[, literal_column_names=False[, bare_fields=False[, include_views=False]]]]])

  Parameters:

  skip_invalid (bool) – Skip tables whose names are invalid python identifiers. table_names (list) – List of table names to generate. If unspecified, models are generated for all tables. literal_column_names (bool) – Use column-names as-is. By default, column names are “python-ized”, i.e. mixed-case becomes lower-case. bare_fields – SQLite-only. Do not specify data-types for introspected columns. include_views – generate models for VIEWs as well.

  Returns:

  A dictionary mapping table-names to model classes.

  Introspect the database, reading in the tables, columns, and foreign key constraints, then generate a dictionary mapping each database table to a dynamically-generated Model class.