Data Persistence¶
The modules described in this chapter support storing Python data in a
persistent form on disk. The pickle
and marshal
modules can turn
many Python data types into a stream of bytes and then recreate the objects from
the bytes. The various DBM-related modules support a family of hash-based file
formats that store a mapping of strings to other strings.
The list of modules described in this chapter is:
pickle
— Python object serialization- Relationship to other Python modules
- Data stream format
- Module Interface
- What can be pickled and unpickled?
- Pickling Class Instances
- Custom Reduction for Types, Functions, and Other Objects
- Out-of-band Buffers
- Restricting Globals
- Performance
- Examples
copyreg
— Registerpickle
support functionsshelve
— Python object persistencemarshal
— Internal Python object serializationdbm
— Interfaces to Unix “databases”sqlite3
— DB-API 2.0 interface for SQLite databases- Module functions and constants
- Connection Objects
Connection
Connection.isolation_level
Connection.in_transaction
Connection.cursor()
Connection.commit()
Connection.rollback()
Connection.close()
Connection.execute()
Connection.executemany()
Connection.executescript()
Connection.create_function()
Connection.create_aggregate()
Connection.create_collation()
Connection.interrupt()
Connection.set_authorizer()
Connection.set_progress_handler()
Connection.set_trace_callback()
Connection.enable_load_extension()
Connection.load_extension()
Connection.row_factory
Connection.text_factory
Connection.total_changes
Connection.iterdump()
Connection.backup()
- Cursor Objects
- Row Objects
- Exceptions
- SQLite and Python types
- Controlling Transactions
- Using
sqlite3
efficiently