Metadata-Version: 2.1
Name: awkward
Version: 0.4.5
Summary: Manipulate jagged, chunky, and/or bitmasked arrays as easily as Numpy.
Home-page: https://github.com/scikit-hep/awkward-array
Author: Jim Pivarski (DIANA-HEP)
Author-email: pivarski@fnal.gov
Maintainer: Jim Pivarski (DIANA-HEP)
Maintainer-email: pivarski@fnal.gov
License: BSD 3-clause
Download-URL: https://github.com/scikit-hep/awkward-array/releases
Platform: Any
Classifier: Development Status :: 4 - Beta
Classifier: Intended Audience :: Developers
Classifier: Intended Audience :: Information Technology
Classifier: Intended Audience :: Science/Research
Classifier: License :: OSI Approved :: BSD License
Classifier: Operating System :: MacOS
Classifier: Operating System :: POSIX
Classifier: Operating System :: Unix
Classifier: Programming Language :: Python
Classifier: Programming Language :: Python :: 2.7
Classifier: Programming Language :: Python :: 3.4
Classifier: Programming Language :: Python :: 3.5
Classifier: Programming Language :: Python :: 3.6
Classifier: Programming Language :: Python :: 3.7
Classifier: Topic :: Scientific/Engineering
Classifier: Topic :: Scientific/Engineering :: Information Analysis
Classifier: Topic :: Scientific/Engineering :: Mathematics
Classifier: Topic :: Scientific/Engineering :: Physics
Classifier: Topic :: Software Development
Classifier: Topic :: Utilities
Requires-Dist: numpy (>=1.13.1)

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Installation
============

Install awkward-array like any other Python package:

.. code-block:: bash

    pip install awkward

or similar (use ``sudo``, ``--user``, ``virtualenv``, or pip-in-conda if you wish).

Strict dependencies:
====================

- `Python <http://docs.python-guide.org/en/latest/starting/installation/>`__ (2.7+, 3.4+)
- `Numpy <https://scipy.org/install.html>`__

Recommended dependencies:
=========================

- `Numba and LLVM <http://numba.pydata.org/numba-doc/latest/user/installing.html>`__ to JIT-compile functions (requires a particular version of LLVM, follow instructions)
- `Dask <http://dask.pydata.org/en/latest/install.html>`__ to distribute work on arrays
- `bcolz <http://bcolz.blosc.org/en/latest/install.html>`__ for on-the-fly compression
- `pyarrow and Arrow-C++ <https://arrow.apache.org/docs/python/install.html>`__ for interoperability with other applications and fast Parquet reading/writing

