|PyVersion| |Status| |License|
The pyqstrat
package is designed for backtesting quantitative strategies. It was originally built for my own use after I could not find a python based framework that was fast, extensible and transparent enough for use in my work.
The goals are:
Using this framework, you can:
I would strongly recommend installing mamba and creating a mamba environment. See https://github.com/conda-forge/miniforge for installation instructions.
pyqstrat relies on numpy, scipy and pandas which in turn use Fortran and C code that needs to be compiled. pyqstrat also includes C++ code that will need to be compiled
::
mamba install pyqstrat
Requirements:
The best way to get started is to go through the getting started Jupyter notebook: Getting Started <https://github.com/abbass2/pyqstrat/tree/master/pyqstrat/notebooks/getting_started.ipynb>
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Jupyter Notebooks <https://github.com/abbass2/pyqstrat/tree/master/pyqstrat/notebooks>
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API docs <https://abbass2.github.io/pyqstrat>
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The pyqstrat user group <https://groups.io/g/pyqstrat>
_ is the group used for pyqstrat discussions. You can also add code issues via github
The software is provided on the conditions of the simplified BSD license.
.. _Python: http://www.python.org
.. |PyVersion| image:: https://img.shields.io/badge/python-3.10+-blue.svg :alt:
.. |Status| image:: https://img.shields.io/badge/status-beta-green.svg :alt:
.. |License| image:: https://img.shields.io/badge/license-BSD-blue.svg :alt: