Metadata-Version: 2.4
Name: wheely-mammoth
Version: 0.16.7
Summary: Utility for reading and handling extreme-scale proteomics datasets with PySpark
Home-page: https://github.com/seerbio/wheely-mammoth
Author: Seth Just
Author-email: sjust@seer.bio
Project-URL: Bug Tracker, https://github.com/seerbio/wheely-mammoth/issues
Classifier: Programming Language :: Python :: 3
Classifier: Operating System :: OS Independent
Classifier: Topic :: Scientific/Engineering :: Bio-Informatics
Requires-Python: >=3.7
Description-Content-Type: text/markdown
License-File: LICENSE.md
Requires-Dist: pyspark<4,>=3.4.0
Provides-Extra: docs
Requires-Dist: numpydoc>=1.0.0; extra == "docs"
Requires-Dist: sphinx-argparse>=0.2.5; extra == "docs"
Requires-Dist: sphinx-rtd-theme>=0.5.0; extra == "docs"
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Requires-Dist: ipykernel>=5.3.0; extra == "docs"
Requires-Dist: recommonmark>=0.5.0; extra == "docs"
Provides-Extra: dev
Requires-Dist: pre-commit>=2.7.1; extra == "dev"
Requires-Dist: black>=20.8b1; extra == "dev"
Requires-Dist: pandas>=1.3.0; extra == "dev"
Requires-Dist: numpy<1.24.0; extra == "dev"
Requires-Dist: pytest; extra == "dev"
Requires-Dist: pyspark[sql]; extra == "dev"
Dynamic: license-file

<img alt="wheely-mammoth logo" src="./static/wheely-mammoth-logo.png" height="128" align="left" style="margin: 8px">

**wheely-mammoth** is a Python library for reading and handling extremely large
proteomics datasets with PySpark. It provides a simple way to find and describe
datasets for use with other tools.

## Installation  

wheely-mammoth requires Python 3.8+ and can be installed with pip  

```shell
pip install wheely-mammoth
```

## Basic Usage  

Example usage:
```pycon
>>> from wheely.mammoth.parsers import read_encyclopedia_features
>>> ds = read_encyclopedia_features("data/*.features.txt")
>>> type(ds)
<class 'wheely.mammoth.dataset.PsmDataset'>
>>> ds.scores.select(ds.score_columns[0]).describe().toPandas()
  summary             primary
0   count                1770
1    mean  12.408585019887022
2  stddev   3.727298477605115
3     min           6.9876947
4     max            43.78316
```
