Metadata-Version: 2.1
Name: awkward
Version: 1.10.2
Summary: Manipulate JSON-like data with NumPy-like idioms.
Home-page: https://github.com/scikit-hep/awkward-1.0
Author: Jim Pivarski
Author-email: pivarski@princeton.edu
Maintainer: Scikit-HEP
Maintainer-email: scikit-hep-admins@googlegroups.com
License: BSD-3-Clause
Project-URL: Documentation, https://awkward-array.org
Project-URL: Source Code, https://github.com/scikit-hep/awkward-1.0
Project-URL: Bug Tracker, https://github.com/scikit-hep/awkward-1.0/issues
Project-URL: Discussions, https://github.com/scikit-hep/awkward-1.0/discussions
Project-URL: Chat, https://gitter.im/Scikit-HEP/awkward-array
Project-URL: Releases, https://github.com/scikit-hep/awkward-1.0/releases
Classifier: Development Status :: 5 - Production/Stable
Classifier: Intended Audience :: Developers
Classifier: Intended Audience :: Information Technology
Classifier: Intended Audience :: Science/Research
Classifier: License :: OSI Approved :: BSD License
Classifier: Operating System :: MacOS :: MacOS X
Classifier: Operating System :: Microsoft :: Windows
Classifier: Operating System :: POSIX :: Linux
Classifier: Operating System :: Unix
Classifier: Programming Language :: Python
Classifier: Programming Language :: Python :: 3
Classifier: Programming Language :: Python :: 3 :: Only
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: 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-Python: >=3.7
Description-Content-Type: text/markdown
Provides-Extra: cuda
Provides-Extra: test
Provides-Extra: dev
Provides-Extra: all
License-File: LICENSE

<a href="https://github.com/scikit-hep/awkward-1.0"><img src="https://github.com/scikit-hep/awkward-1.0/raw/main/docs-img/logo/logo-300px.png"></a>

[![PyPI version](https://badge.fury.io/py/awkward.svg)](https://pypi.org/project/awkward)
[![Conda-Forge](https://img.shields.io/conda/vn/conda-forge/awkward)](https://github.com/conda-forge/awkward-feedstock)
[![Python 3.7‒3.11](https://img.shields.io/badge/python-3.7%E2%80%923.11-blue)](https://www.python.org)
[![BSD-3 Clause License](https://img.shields.io/badge/license-BSD%203--Clause-blue.svg)](https://opensource.org/licenses/BSD-3-Clause)
[![Continuous integration tests](https://img.shields.io/azure-devops/build/jpivarski/Scikit-HEP/3/main?label=tests)](https://dev.azure.com/jpivarski/Scikit-HEP/_build)

[![Scikit-HEP](https://scikit-hep.org/assets/images/Scikit--HEP-Project-blue.svg)](https://scikit-hep.org/)
[![NSF-1836650](https://img.shields.io/badge/NSF-1836650-blue.svg)](https://nsf.gov/awardsearch/showAward?AWD_ID=1836650)
[![DOI](https://zenodo.org/badge/DOI/10.5281/zenodo.4341376.svg)](https://doi.org/10.5281/zenodo.4341376)
[![Documentation](https://img.shields.io/badge/docs-online-success)](https://awkward-array.org)
[![Gitter](https://img.shields.io/badge/chat-online-success)](https://gitter.im/Scikit-HEP/awkward-array)

Awkward Array is a library for **nested, variable-sized data**, including arbitrary-length lists, records, mixed types, and missing data, using **NumPy-like idioms**.

Arrays are **dynamically typed**, but operations on them are **compiled and fast**. Their behavior coincides with NumPy when array dimensions are regular and generalizes when they're not.

# Motivating example

Given an array of objects with `x`, `y` fields and variable-length nested lists like

```python
array = ak.Array([
    [{"x": 1.1, "y": [1]}, {"x": 2.2, "y": [1, 2]}, {"x": 3.3, "y": [1, 2, 3]}],
    [],
    [{"x": 4.4, "y": {1, 2, 3, 4]}, {"x": 5.5, "y": [1, 2, 3, 4, 5]}]
])
```

the following slices out the `y` values, drops the first element from each inner list, and runs NumPy's `np.square` function on everything that is left:

```python
output = np.square(array["y", ..., 1:])
```

The result is

```python
[
    [[], [4], [4, 9]],
    [],
    [[4, 9, 16], [4, 9, 16, 25]]
]
```

The equivalent using only Python is

```python
output = []
for sublist in array:
    tmp1 = []
    for record in sublist:
        tmp2 = []
        for number in record["y"][1:]:
            tmp2.append(np.square(number))
        tmp1.append(tmp2)
    output.append(tmp1)
```

Not only is the expression using Awkward Arrays more concise, using idioms familiar from NumPy, but it's much faster and uses less memory.

For a similar problem 10 million times larger than the one above (on a single-threaded 2.2 GHz processor),

   * the Awkward Array one-liner takes **4.6 seconds** to run and uses **2.1 GB** of memory,
   * the equivalent using Python lists and dicts takes **138 seconds** to run and uses **22 GB** of memory.

Speed and memory factors in the double digits are common because we're replacing Python's dynamically typed, pointer-chasing virtual machine with type-specialized, precompiled routines on contiguous data. (In other words, for the same reasons as NumPy.) Even higher speedups are possible when Awkward Array is paired with [Numba](https://numba.pydata.org/).

Our [presentation at SciPy 2020](https://youtu.be/WlnUF3LRBj4) provides a good introduction, showing how to use these arrays in a real analysis.

# Installation

Awkward Array can be installed [from PyPI](https://pypi.org/project/awkward) using pip:

```bash
pip install awkward
```

You will likely get a precompiled binary (wheel), depending on your operating system and Python version. If not, pip attempts to compile from source (which requires a C++ compiler, make, and CMake).

Awkward Array is also available using [conda](https://anaconda.org/conda-forge/awkward), which always installs a binary:
```bash
conda install -c conda-forge awkward
```

If you have already added `conda-forge` as a channel, the `-c conda-forge` is unnecessary. Adding the channel is recommended because it ensures that all of your packages use compatible versions:

```bash
conda config --add channels conda-forge
conda update --all
```

## Getting help

<table>
  <tr>
    <td width="66%" valign="top">
      <a href="https://awkward-array.org">
        <img src="https://github.com/scikit-hep/awkward-1.0/raw/main/docs-img/panel-tutorials.png" width="570">
      </a>
      <p align="center"><b>
        <a href="https://awkward-array.org">
        How-to tutorials
        </a>
      </b></p>
    </td>
    <td width="33%" valign="top">
      <a href="https://awkward-array.readthedocs.io/en/latest/index.html">
        <img src="https://github.com/scikit-hep/awkward-1.0/raw/main/docs-img/panel-sphinx.png" width="268">
      </a>
      <p align="center"><b>
        <a href="https://awkward-array.readthedocs.io/en/latest/index.html">
        Python API reference
        </a>
      </b></p>
      <a href="https://awkward-array.readthedocs.io/en/latest/_static/index.html">
        <img src="https://github.com/scikit-hep/awkward-1.0/raw/main/docs-img/panel-doxygen.png" width="268">
      </a>
      <p align="center"><b>
        <a href="https://awkward-array.readthedocs.io/en/latest/_static/index.html">
        C++ API reference
        </a>
      </b></p>
    </td>
  </tr>
</table>

   * Report bugs, request features, and ask for additional documentation on [GitHub Issues](https://github.com/scikit-hep/awkward-1.0/issues).
   * You can vote for issues by adding a "thumbs up" (👍) using the "smile/pick your reaction" menu on the top-right of the issue. See the [prioritized list of open issues](https://github.com/scikit-hep/awkward-1.0/issues?q=is%3Aissue+is%3Aopen+sort%3Areactions-%2B1-desc+reactions%3A%3E0+).
   * If you have a "How do I...?" question, start a [GitHub Discussion](https://github.com/scikit-hep/awkward-1.0/discussions) with category "Q&A".
   * Alternatively, ask about it on [StackOverflow with the [awkward-array] tag](https://stackoverflow.com/questions/tagged/awkward-array). Be sure to include tags for any other libraries that you use, such as Pandas or PyTorch.
   * To ask questions in real time, try the Gitter [Scikit-HEP/awkward-array](https://gitter.im/Scikit-HEP/awkward-array) chat room.
