Metadata-Version: 2.1
Name: EDS-Scikit
Version: 0.1.0
Summary: OMOP data analysis in Python
Author-email: Thomas Petitjean <thomas.petitjean@aphp.fr>, Adam Remaki <adam.remaki@aphp.fr>, Vincent Maladière <vincent.maladiere-ext@aphp.fr>, Romain Bey <romain.bey@aphp.fr>, Gaël Varoquaux <gael.varoquaux@inria.fr>
License: 
        BSD License
        
        Copyright (c) 2021, Assistance Publique - Hôpitaux de Paris, Inria
        All rights reserved.
        
        Redistribution and use in source and binary forms, with or without modification,
        are permitted provided that the following conditions are met:
        
        * Redistributions of source code must retain the above copyright notice, this
          list of conditions and the following disclaimer.
        
        * Redistributions in binary form must reproduce the above copyright notice, this
          list of conditions and the following disclaimer in the documentation and/or
          other materials provided with the distribution.
        
        * Neither the name of the copyright holder nor the names of its
          contributors may be used to endorse or promote products derived from this
          software without specific prior written permission.
        
        THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS "AS IS" AND
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Project-URL: source, https://github.com/aphp/EDS-Scikit
Classifier: Intended Audience :: Developers
Classifier: Intended Audience :: Science/Research
Classifier: Programming Language :: Python :: 3.7
Classifier: Topic :: Software Development :: Libraries
Classifier: Topic :: Scientific/Engineering
Classifier: License :: OSI Approved :: BSD License
Classifier: Operating System :: Unix
Requires-Python: <3.8,>=3.7.1
Description-Content-Type: text/markdown
Provides-Extra: dev
Provides-Extra: doc
Provides-Extra: aphp
License-File: LICENSE

<div align="center">

<p align="center">
  <a href="https://aphp.github.io/EDS-Scikit/"><img src="docs/_static/scikit_logo_text.png" width="30%"></a>
</p>

#

<p align="center">
<a href="https://aphp.github.io/EDS-Scikit/" target="_blank">
    <img src="https://img.shields.io/badge/docs-passed-brightgreen" alt="Documentation">
</a>
<a href="https://github.com/aphp/EDS-Scikit/commits/main" target="_blank">
    <img src="https://github.com/aphp/EDS-Scikit/actions/workflows/testing.yml/badge.svg" alt="Pipeline Status">
</a>
<a href="https://codecov.io/github/aphp/EDS-Scikit?branch=main">
    <img src="https://codecov.io/github/aphp/EDS-Scikit/coverage.svg?branch=main" alt="Coverage" >
</a>
<a href="https://github.com/psf/black" target="_blank">
    <img src="https://img.shields.io/badge/code%20style-black-000000.svg" alt="Black">
</a>

<a href="https://www.python.org/" target="_blank">
    <img src="https://img.shields.io/badge/python-%3E%3D%203.7.1%20%7C%20%3C%203.8-brightgreen" alt="Supported Python versions">
</a>
</p>
</div>


EDS-Scikit is a tool to assist data scientists working on the AP-HP's Clinical Data Warehouse. It is specifically targeted for OMOP-standardized data. It main goals are to:

- Ease access and analysis of data
- Allow a better transfer of knowledge between projects
- Improve research reproduciblity

## Development

This library is developed and maintained by the core team of AP-HP’s Clinical Data Warehouse (EDS) with the strong support of [Inria's SODA team](https://team.inria.fr/soda/).

## How to use

Please check the [online documentation](https://datasciencetools-pages.eds.aphp.fr/eds-scikit/documentation/) for more informations. You will find
- Detailed explanation of the project goal and working principles
- A complete API documentation
- Various Jupyter Notebooks describing how to use various functionnalities of SciKit-EDS
- And more !
## Requirements
EDS-Scikit stands on the shoulders of [Spark 2.4](https://spark.apache.org/docs/2.4.8/index.html) which requires:

- Python ~3.7.1
- Java 8
## Installation

You can install EDS-Scikit via `pip`:

```bash
pip install eds-scikit
```

:warning: If you work in AP-HP's ecosystem (EDS), please install additionnal features via:

```bash
pip install "eds-scikit[aphp]"
```

You can now import the library via

```python
import eds_scikit
```
### Contributing

- You want to help on the project ?
- You developped an interesting feature and you think it could benefit other by being integrated in the library ?
- You found a bug ?
- You have a question about the library ?
- ...

Please check our [contributing guidelines](https://datasciencetools-pages.eds.aphp.fr/eds-scikit/documentation/contributing.html).

For AP-HP users, also feel free to use the dedicated [Zulip channel](https://chat.eds.aphp.fr/#narrow/stream/154-SciKit-EDS). (If you need a permission to join the channel, simply [message one of the developper](https://chat.eds.aphp.fr/#narrow/pm-with/351-thomas.petitjean-ext))

### Acknowledgment

We would like to thank the following funders:
- Assistance Publique – Hôpitaux de Paris
- AP-HP Foundation
