
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
    * Persistence of External Objects
    * Handling Stateful Objects
  * Restricting Globals
  * Examples
* ``copyreg`` --- Register ``pickle`` support functions
  * Example
* ``shelve`` --- Python object persistence
  * Restrictions
  * Example
* ``marshal`` --- Internal Python object serialization
* ``dbm`` --- Interfaces to Unix "databases"
  * ``dbm.gnu`` --- GNU's reinterpretation of dbm
  * ``dbm.ndbm`` --- Interface based on ndbm
  * ``dbm.dumb`` --- Portable DBM implementation
* ``sqlite3`` --- DB-API 2.0 interface for SQLite databases
  * Module functions and constants
  * Connection Objects
  * Cursor Objects
  * Row Objects
  * SQLite and Python types
    * Introduction
    * Using adapters to store additional Python types in SQLite
      databases
      * Letting your object adapt itself
      * Registering an adapter callable
    * Converting SQLite values to custom Python types
    * Default adapters and converters
  * Controlling Transactions
  * Using ``sqlite3`` efficiently
    * Using shortcut methods
    * Accessing columns by name instead of by index
    * Using the connection as a context manager
  * Common issues
    * Multithreading