numexpr-mod 2.8.5.dev1

Fast numerical expression evaluator for NumPy

Author:

Alexander K.

URL:

https://github.com/MrCheatak/numexpr_mod

What is NumExpr?

Please refer to the original Numexpr repo.

Installation

From wheels

NumExpr is available for install via pip for a wide range of platforms and Python versions (which may be browsed at: https://pypi.org/project/numexpr/#files). Installation can be performed as:

pip install numexpr

If you are using the Anaconda or Miniconda distribution of Python you may prefer to use the conda package manager in this case:

conda install numexpr

From Source

On most *nix systems your compilers will already be present. However if you are using a virtual environment with a substantially newer version of Python than your system Python you may be prompted to install a new version of gcc or clang.

For Windows, you will need to install the Microsoft Visual C++ Build Tools (which are free) first. The version depends on which version of Python you have installed:

https://wiki.python.org/moin/WindowsCompilers

For Python 3.6+ simply installing the latest version of MSVC build tools should be sufficient. Note that wheels found via pip do not include MKL support. Wheels available via conda will have MKL, if the MKL backend is used for NumPy.

See requirements.txt for the required version of NumPy.

NumExpr is built in the standard Python way:

python setup.py build install

You can test numexpr with:

python -c "import numexpr; numexpr.test()"

Do not test NumExpr in the source directory or you will generate import errors.

Usage

>>> import numexpr_mod as ne
>>> import numpy as np

>>> a = np.array([1,2,3,4,5])
>>> b = np.array([6,7,8,9,0])

>>> ne.cache_expression('a + b', 'sum_ab')
{'ex': <numexpr_mod.NumExpr object at 0x1090e36b0>, 'argnames': ['a', 'b'], 'kwargs': {'out': None, 'order': 'K', 'casting': 'safe', 'ex_uses_vml': False}}
>>> ne.re_evaluate('sum_ab')
array([ 7,  9, 11, 13,  5], dtype=int64)
>>> ne.evaluate('a + b')
array([ 7,  9, 11, 13,  5], dtype=int64)

Documentation

Please see the official documentation at numexpr.readthedocs.io. Included is a user guide, benchmark results, and the reference API.

Authors

Please see AUTHORS.txt.

License

NumExpr is distributed under the MIT license.