Metadata-Version: 2.1
Name: awkwardql
Version: 0.0.1.dev0
Summary: SQL-like language for awkward arrays
Home-page: https://github.com/lgray/AwkwardQL
Author: Lindsey Gray (Fermilab), Jim Pivarski (Princeton)
Author-email: lagray@fnal.gov
Maintainer: Lindsey Gray (Fermilab)
Maintainer-email: lagray@fnal.gov
License: BSD 3-clause
Download-URL: https://github.com/lgray/AwkwardQL/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 :: 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: awkward1 (>=0.1.36)
Requires-Dist: numba (>=0.43.1)
Requires-Dist: numpy (>=1.16.0)

.. inclusion-marker-1-5-do-not-remove

This is derived from and inspired by the demo by Jim Pivarski (PartiQL) and targets awkward 1.0.

We will start out focusing on particle physics uses cases and see how far it goes from there. :-)

.. inclusion-marker-2-do-not-remove

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

Install coffea like any other Python package:

.. code-block:: bash

    pip install awkwardql

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/>`__ (3.6+)

The following are installed automatically when you install coffea with pip:

- `awkward1 <https://github.com/scikit-hep/awkward-array>`__ to manipulate complex-structured columnar data, such as jagged arrays;
- `numba <https://numba.pydata.org/>`__ just-in-time compilation of python functions;

