Applying predictive analytics to horse racing via Python
Project description
This project aims to apply predictive analytics to horse racing via Python.
Installation
Prior to using predictive_punter, the package must be installed in your current Python environment. In most cases, an automated installation via PyPI and pip will suffice, as follows:
pip install predictive_punter
If you would prefer to gain access to new (unstable) features via a pre-release version of the package, specify the ‘pre’ option when calling pip, as follows:
pip install --pre predictive_punter
To gain access to bleeding edge developments, the package can be installed from a source distribution. To do so, you will need to clone the git repository and execute the setup.py script from the root directory of the source tree, as follows:
git clone https://github.com/justjasongreen/predictive_punter.git cd predictive_punter python setup.py install
If you would prefer to install the package as a symlink to the source distribution (for development purposes), execute the setup.py script with the ‘develop’ option instead, as follows:
python setup.py develop
Basic Usage
To access the functionality described below, you must first import the predictive_punter package into your Python interpreter, as follows:
>>> import predictive_punter
Development and Testing
The source distribution includes a test suite based on pytest. To ensure compatibility with all supported versions of Python, it is recommended that the test suite be run via tox.
To install all development and test requirements into your current Python environment, execute the following command from the root directory of the source tree:
pip install -e .[dev,test]
To run the test suite included in the source distribution, execute the tox command from the root directory of the source tree as follows:
tox
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