Metadata-Version: 2.1
Name: awkward0
Version: 0.15.5
Summary: Manipulate arrays of complex data structures as easily as Numpy.
Home-page: https://github.com/scikit-hep/awkward-0.x
Author: Jim Pivarski (IRIS-HEP)
Author-email: pivarski@princeton.edu
Maintainer: Jim Pivarski (IRIS-HEP)
Maintainer-email: pivarski@princeton.edu
License: BSD 3-clause
Download-URL: https://github.com/scikit-hep/awkward-0.x/releases
Platform: Any
Classifier: Development Status :: 7 - Inactive
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: Programming Language :: Python :: 3.8
Classifier: Programming Language :: Python :: 3.9
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
License-File: LICENSE

.. image:: https://raw.githubusercontent.com/scikit-hep/awkward-0.x/master/docs/source/logo-300px.png
   :alt: awkward-array
   :target: https://github.com/scikit-hep/awkward-0.x

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

Calculations with rectangular, numerical data are simpler and faster in Numpy than traditional for loops. Consider, for instance,

.. code-block:: python

    all_r = []
    for x, y in zip(all_x, all_y):
        all_r.append(sqrt(x**2 + y**2))

versus

.. code-block:: python

    all_r = sqrt(all_x**2 + all_y**2)

Not only is the latter easier to read, it's hundreds of times faster than the for loop (and provides opportunities for hidden vectorization and parallelization). However, the Numpy abstraction stops at rectangular arrays of numbers or character strings. While it's possible to put arbitrary Python data in a Numpy array, Numpy's ``dtype=object`` is essentially a fixed-length list: data are not contiguous in memory and operations are not vectorized.

Awkward Array is a pure Python+Numpy library for manipulating complex data structures as you would Numpy arrays. Even if your data structures

* contain variable-length lists (jagged/ragged),
* are deeply nested (record structure),
* have different data types in the same list (heterogeneous),
* are masked, bit-masked, or index-mapped (nullable),
* contain cross-references or even cyclic references,
* need to be Python class instances on demand,
* are not defined at every point (sparse),
* are not contiguous in memory,
* should not be loaded into memory all at once (lazy),

this library can access them as `columnar data structures <https://towardsdatascience.com/the-beauty-of-column-oriented-data-2945c0c9f560>`__, with the efficiency of Numpy arrays. They may be converted from JSON or Python data, loaded from "awkd" files, `HDF5 <https://www.hdfgroup.org>`__, `Parquet <https://parquet.apache.org>`__, or `ROOT <https://root.cern>`__ files, or they may be views into memory buffers like `Arrow <https://arrow.apache.org>`__.

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

Install Awkward Array like any other Python package:

.. code-block:: bash

    pip install awkward0                      # maybe with sudo or --user, or in virtualenv

The base ``awkward0`` package requires only `Numpy <https://scipy.org/install.html>`__  (1.13.1+).

Recommended packages:
---------------------

- `pyarrow <https://arrow.apache.org/docs/python/install.html>`__ to view Arrow and Parquet data as Awkward Arrays
- `h5py <https://www.h5py.org>`__ to read and write Awkward Arrays in HDF5 files
- `Pandas <https://pandas.pydata.org>`__ as an alternative view

