Simple, fast implementation of Fisher's exact test. For example, for the following table:

Perhaps we are interested in whether there is any difference of property in selected vs. non-selected groups, then we can do the Fisher's exact test.

Within this folder :

git clone git://github.com/brentp/fishers_exact_test.git
pip install .

From PyPI :

pip install fisher

Or install the development version :

pip install git+git://github.com/brentp/fishers_exact_test.git

fisher.pvalue() accepts 4 values corresponding to the 2-by-2 contingency table, returns an object with attributes for left_tail, right_tail, and two_tail p-values :

>>> from fisher import pvalue
>>> mat = [[12, 5], [29, 2]]
>>> p = pvalue(12, 5, 29, 2)
>>> p.left_tail, p.right_tail, p.two_tail  # doctest: +NORMALIZE_WHITESPACE, +ELLIPSIS
(0.04455473783507..., 0.994525206021..., 0.0802685520741...)

A simple benchmark that calls the Fisher's exact test 1000 times (in scripts/rfisher.py):

calling python fisher...
iterations/sec: 3000.62526381
calling rpy fisher...
iterations/sec: 289.225902364
calling R directly...
iterations/sec: 244.36542276

So the cython fisher is up to 10 times faster than rpy or R version.