Metadata-Version: 2.1
Name: numexpr-mod
Version: 2.8.5.dev1
Summary: Fast numerical expression evaluator for NumPy
Home-page: https://github.com/pydata/numexpr
Author: David M. Cooke, Francesc Alted, and others
Maintainer: Robert A. McLeod
Maintainer-email: robbmcleod@gmail.com
License: MIT
Classifier: Development Status :: 6 - Mature
Classifier: Intended Audience :: Financial and Insurance Industry
Classifier: Intended Audience :: Science/Research
Classifier: License :: OSI Approved :: MIT License
Classifier: Programming Language :: Python :: 3
Classifier: Programming Language :: Python :: 3.7
Classifier: Programming Language :: Python :: 3.8
Classifier: Programming Language :: Python :: 3.9
Classifier: Programming Language :: Python :: 3.10
Classifier: Programming Language :: Python :: 3.11
Classifier: Operating System :: Microsoft :: Windows
Classifier: Operating System :: POSIX
Classifier: Operating System :: MacOS
Requires-Python: >=3.7
Description-Content-Type: text/x-rst
License-File: LICENSE.txt
License-File: AUTHORS.txt

============================================================
NumExpr_mod: 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 <https://github.com/pydata/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 <https://numexpr.readthedocs.io>`_.
Included is a user guide, benchmark results, and the reference API.


Authors
-------

Please see `AUTHORS.txt <https://github.com/pydata/numexpr/blob/master/AUTHORS.txt>`_.


License
-------

NumExpr is distributed under the `MIT <http://www.opensource.org/licenses/mit-license.php>`_ license.


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