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authorRaymond Hettinger <python@rcn.com>2008-01-13 23:40:30 +0000
committerRaymond Hettinger <python@rcn.com>2008-01-13 23:40:30 +0000
commit6d7b11db0cfac96ba4d8bcfb13c4a0c5ce686603 (patch)
tree1a0374fa1b94647a7538f765a22f2982540fc59d /Doc/library/random.rst
parent8c98e554896d435114fccd1cb9011d063b60b00d (diff)
downloadcpython-6d7b11db0cfac96ba4d8bcfb13c4a0c5ce686603.tar.gz
Remove defunct parts of the random module
Diffstat (limited to 'Doc/library/random.rst')
-rw-r--r--Doc/library/random.rst46
1 files changed, 2 insertions, 44 deletions
diff --git a/Doc/library/random.rst b/Doc/library/random.rst
index 18c063ca7b..ff5fb77590 100644
--- a/Doc/library/random.rst
+++ b/Doc/library/random.rst
@@ -28,25 +28,14 @@ for cryptographic purposes.
The functions supplied by this module are actually bound methods of a hidden
instance of the :class:`random.Random` class. You can instantiate your own
-instances of :class:`Random` to get generators that don't share state. This is
-especially useful for multi-threaded programs, creating a different instance of
-:class:`Random` for each thread, and using the :meth:`jumpahead` method to make
-it likely that the generated sequences seen by each thread don't overlap.
+instances of :class:`Random` to get generators that don't share state.
Class :class:`Random` can also be subclassed if you want to use a different
basic generator of your own devising: in that case, override the :meth:`random`,
-:meth:`seed`, :meth:`getstate`, :meth:`setstate` and :meth:`jumpahead` methods.
+:meth:`seed`, :meth:`getstate`, and :meth:`setstate`.
Optionally, a new generator can supply a :meth:`getrandombits` method --- this
allows :meth:`randrange` to produce selections over an arbitrarily large range.
-As an example of subclassing, the :mod:`random` module provides the
-:class:`WichmannHill` class that implements an alternative generator in pure
-Python. The class provides a backward compatible way to reproduce results from
-earlier versions of Python, which used the Wichmann-Hill algorithm as the core
-generator. Note that this Wichmann-Hill generator can no longer be recommended:
-its period is too short by contemporary standards, and the sequence generated is
-known to fail some stringent randomness tests. See the references below for a
-recent variant that repairs these flaws.
Bookkeeping functions:
@@ -79,17 +68,6 @@ Bookkeeping functions:
the time :func:`setstate` was called.
-.. function:: jumpahead(n)
-
- Change the internal state to one different from and likely far away from the
- current state. *n* is a non-negative integer which is used to scramble the
- current state vector. This is most useful in multi-threaded programs, in
- conjuction with multiple instances of the :class:`Random` class:
- :meth:`setstate` or :meth:`seed` can be used to force all instances into the
- same internal state, and then :meth:`jumpahead` can be used to force the
- instances' states far apart.
-
-
.. function:: getrandbits(k)
Returns a python integer with *k* random bits. This method is supplied with
@@ -224,24 +202,6 @@ be found in any statistics text.
Alternative Generators:
-.. class:: WichmannHill([seed])
-
- Class that implements the Wichmann-Hill algorithm as the core generator. Has all
- of the same methods as :class:`Random` plus the :meth:`whseed` method described
- below. Because this class is implemented in pure Python, it is not threadsafe
- and may require locks between calls. The period of the generator is
- 6,953,607,871,644 which is small enough to require care that two independent
- random sequences do not overlap.
-
-
-.. function:: whseed([x])
-
- This is obsolete, supplied for bit-level compatibility with versions of Python
- prior to 2.1. See :func:`seed` for details. :func:`whseed` does not guarantee
- that distinct integer arguments yield distinct internal states, and can yield no
- more than about 2\*\*24 distinct internal states in all.
-
-
.. class:: SystemRandom([seed])
Class that uses the :func:`os.urandom` function for generating random numbers
@@ -281,6 +241,4 @@ Examples of basic usage::
equidistributed uniform pseudorandom number generator", ACM Transactions on
Modeling and Computer Simulation Vol. 8, No. 1, January pp.3-30 1998.
- Wichmann, B. A. & Hill, I. D., "Algorithm AS 183: An efficient and portable
- pseudo-random number generator", Applied Statistics 31 (1982) 188-190.