9.6. random — Generate pseudo-random numbers¶
This module implements pseudo-random number generators for various distributions.
For integers, uniform selection from a range. For sequences, uniform selection of a random element, a function to generate a random permutation of a list in-place, and a function for random sampling without replacement.
On the real line, there are functions to compute uniform, normal (Gaussian), lognormal, negative exponential, gamma, and beta distributions. For generating distributions of angles, the von Mises distribution is available.
Almost all module functions depend on the basic function random(), which
generates a random float uniformly in the semi-open range [0.0, 1.0). Python
uses the Mersenne Twister as the core generator. It produces 53-bit precision
floats and has a period of 2**19937-1. The underlying implementation in C is
both fast and threadsafe. The Mersenne Twister is one of the most extensively
tested random number generators in existence. However, being completely
deterministic, it is not suitable for all purposes, and is completely unsuitable
for cryptographic purposes.
The functions supplied by this module are actually bound methods of a hidden
instance of the random.Random class. You can instantiate your own
instances of Random to get generators that don’t share state. This is
especially useful for multi-threaded programs, creating a different instance of
Random for each thread, and using the jumpahead() method to make
it likely that the generated sequences seen by each thread don’t overlap.
Class Random can also be subclassed if you want to use a different
basic generator of your own devising: in that case, override the random(),
seed(), getstate(), setstate() and jumpahead() methods.
Optionally, a new generator can supply a getrandbits() method — this
allows randrange() to produce selections over an arbitrarily large range.
New in version 2.4:
New in version 2.4: the getrandbits() method.
As an example of subclassing, the random module provides the
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.
Changed in version 2.3:
Changed in version 2.3: MersenneTwister replaced Wichmann-Hill as the default generator.