Metadata-Version: 2.2
Name: bitepy
Version: 0.6.8
Summary: A Python wrapper for my C++ battery CID arbitrage simulation engine.
Author-Email: David Schaurecker <dschaurecker@gmail.com>
License: MIT License
         
         Copyright (c) 2025 ETH Zurich
         
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Classifier: Programming Language :: Python :: 3
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: Programming Language :: Python :: 3.12
Classifier: Programming Language :: Python :: 3.13
Classifier: License :: OSI Approved :: MIT License
Classifier: Operating System :: OS Independent
Classifier: Development Status :: 4 - Beta
Project-URL: Homepage, https://github.com/dschaurecker/bitepy
Project-URL: Issues, https://github.com/dschaurecker/bitepy/issues
Project-URL: Documentation, https://dschaurecker.github.io/bitepy/
Requires-Python: >=3.8
Requires-Dist: numpy>=1.16.0
Requires-Dist: pandas>=0.24.0
Requires-Dist: matplotlib>=3.0.0
Requires-Dist: tqdm>=4.0.0
Description-Content-Type: text/markdown

<p align="center" width="100%">
<img src="https://raw.githubusercontent.com/dschaurecker/bitepy/main/docs/assets/bitepy_logo_text.png" width="300">
</p>

## _A Battery Intraday Trading Engine_

[![Version](https://img.shields.io/github/v/tag/dschaurecker/bitepy?label=version&style=flat)](https://github.com/dschaurecker/bitepy/releases)
[![License: MIT](https://img.shields.io/badge/License-MIT-red.svg)](https://opensource.org/licenses/MIT)
[![PyPI - Downloads](https://img.shields.io/pypi/dm/bitepy)](https://pypi.org/project/bitepy/)
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A Python high-frequency intraday trading engine for simulating the rolling intrinsic strategy on the European market, solved as a dynamic program. See our paper (tbd, Schaurecker & Wozabal et al. (2025)) for details on the method and visualizations of the results.


## Features

- Process your own raw EPEX Spot Market Data to a suitable format
- Define battery and simulation settings
- Adapt the parameters of the dynamic programming optimization
- React to every single LOB update on the exchange
- Run yearly high-frequency trading simulations in minutes/hours
- Return and visualize results and statistics

## Installation

BitePy requires Python 3.8+ to run.
The package is hosted on [PyPI](https://pypi.org/project/bitepy/) and can be easily installed via

```sh
pip install bitepy
```

## Documentation and Tutorial

Our [Documentation](https://dschaurecker.github.io/bitepy/) gives a detailed overview on our package's features and will be updated continuously. We also provide a simple [Tutorial](https://github.com/dschaurecker/bitepy/blob/main/notebooks/package_tutorial.ipynb) in form of a Jupyter Notebook, guiding users through our simulation process.

## Contribution

We are happy about all forms of feedback and would like to hear from you, if you would like to contribute as well, or are interested in the underlying C++ source code of your simulation engine.
If you want to clone and contribute to the repository, first `pip install bitepy` and then clone the repository to have access to the compiled binaries while being able to edit the Python source code.

## License

Licensed under MIT License.
See [License](https://github.com/dschaurecker/bitepy/blob/main/LICENSE) for the full license text.

## Author

[@dschaurecker](https://github.com/dschaurecker)

with pythonic support by [@simon-hirsch](https://github.com/simon-hirsch)
