How do I program using threads?
-------------------------------
-.. XXX it's _thread in py3k
-
-Be sure to use the :mod:`threading` module and not the :mod:`thread` module.
+Be sure to use the :mod:`threading` module and not the :mod:`_thread` module.
The :mod:`threading` module builds convenient abstractions on top of the
-low-level primitives provided by the :mod:`thread` module.
+low-level primitives provided by the :mod:`_thread` module.
Aahz has a set of slides from his threading tutorial that are helpful; see
http://starship.python.net/crew/aahz/OSCON2001/.
Instead of trying to guess how long a :func:`time.sleep` delay will be enough,
it's better to use some kind of semaphore mechanism. One idea is to use the
-:mod:`Queue` module to create a queue object, let each thread append a token to
+:mod:`queue` module to create a queue object, let each thread append a token to
the queue when it finishes, and let the main thread read as many tokens from the
queue as there are threads.
How do I parcel out work among a bunch of worker threads?
---------------------------------------------------------
-Use the :mod:`Queue` module to create a queue containing a list of jobs. The
-:class:`~Queue.Queue` class maintains a list of objects with ``.put(obj)`` to
+Use the :mod:`queue` module to create a queue containing a list of jobs. The
+:class:`~queue.Queue` class maintains a list of objects with ``.put(obj)`` to
add an item to the queue and ``.get()`` to return an item. The class will take
care of the locking necessary to ensure that each job is handed out exactly
once.
Yes.
-.. XXX remove bsddb in py3k, fix other module names
-
-Python 2.3 includes the :mod:`bsddb` package which provides an interface to the
-BerkeleyDB library. Interfaces to disk-based hashes such as :mod:`DBM <dbm>`
-and :mod:`GDBM <gdbm>` are also included with standard Python.
+Interfaces to disk-based hashes such as :mod:`DBM <dbm.ndbm>` and :mod:`GDBM
+<dbm.gnu>` are also included with standard Python. There is also the
+:mod:`sqlite3` module, which provides a lightweight disk-based relational
+database.
Support for most relational databases is available. See the
`DatabaseProgramming wiki page
The :mod:`pickle` library module solves this in a very general way (though you
still can't store things like open files, sockets or windows), and the
:mod:`shelve` library module uses pickle and (g)dbm to create persistent
-mappings containing arbitrary Python objects. For better performance, you can
-use the :mod:`cPickle` module.
+mappings containing arbitrary Python objects.
A more awkward way of doing things is to use pickle's little sister, marshal.
The :mod:`marshal` module provides very fast ways to store noncircular basic
In general, don't use ``from modulename import *``. Doing so clutters the
importer's namespace. Some people avoid this idiom even with the few modules
that were designed to be imported in this manner. Modules designed in this
-manner include :mod:`Tkinter`, and :mod:`threading`.
+manner include :mod:`tkinter`, and :mod:`threading`.
Import modules at the top of a file. Doing so makes it clear what other modules
your code requires and avoids questions of whether the module name is in scope.
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