Metadata-Version: 2.3
Name: akimbo
Version: 2024.12.0
Summary: Awkward Array Extension for Dataframes
Project-URL: Homepage, https://github.com/intake/akimbo
Project-URL: Bug Tracker, https://github.com/intake/akimbo/issues
Author-email: Martin Durant <mdurant@anaconda.com>
Maintainer-email: Martin Durant <mdurant@anaconda.com>
License: BSD-3-Clause
Classifier: Development Status :: 3 - Alpha
Classifier: License :: OSI Approved :: BSD License
Classifier: Programming Language :: Python :: 3
Classifier: Programming Language :: Python :: 3 :: Only
Classifier: Programming Language :: Python :: 3.9
Classifier: Programming Language :: Python :: 3.10
Classifier: Programming Language :: Python :: 3.11
Classifier: Programming Language :: Python :: 3.12
Classifier: Topic :: Scientific/Engineering
Requires-Python: >=3.9
Requires-Dist: awkward>=2.6.5
Requires-Dist: pyarrow
Provides-Extra: docs
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Requires-Dist: pandoc; extra == 'docs'
Requires-Dist: polars; extra == 'docs'
Requires-Dist: pyarrow; extra == 'docs'
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Provides-Extra: test
Requires-Dist: dask; extra == 'test'
Requires-Dist: dask-awkward; extra == 'test'
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Description-Content-Type: text/markdown

# akimbo

**For when your data won't fit in your dataframe**

[![Tests](https://github.com/intake/akimbo/actions/workflows/pypi.yml/badge.svg)](https://github.com/intake/akimbo/actions/workflows/pypi.yml)
[![Documentation Status](https://readthedocs.org/projects/akimbo/badge/?version=latest)](https://akimbo.readthedocs.io/en/latest/?badge=latest)

Akimbo provides fast vectorized processing of nested, ragged data
in dataframes, using the ``.ak`` accessor.

### Features

- numpy-like API for slicing and accessing data deep in nested structures
- apply any function, ufunc or aggregation at any level
- use with different backends: pandas, polars, dask-dataframe and cuDF
  exactly the same way (more backends may come in the future)
- CPU and GPU processing and support for ``numba``-jit
- attach object-like behaviours to your record (sub)structures

See the [quick
start](https://akimbo.readthedocs.io/en/latest/quickstart.html)
in the documentation for an introduction to akimbo.

Acknowledgements
----------------

Support for this work was provided by NSF grant [OAC-2103945](https://www.nsf.gov/awardsearch/showAward?AWD_ID=2103945).
