Sportsipy: A free sports API written for python ############################################### Development Status: This project is no longer undergoing active development. Please consider opening a pull request for any new features or bug fixes to be reviewed and merged.
.. image:: https://github.com/roclark/sportsipy/workflows/Sportsipy%20push%20tests/badge.svg :target: https://github.com/roclark/sportsipy/actions .. image:: https://readthedocs.org/projects/sportsipy/badge/?version=latest :target: https://sportsipy.readthedocs.io/en/latest/?badge=latest :alt: Documentation Status .. image:: https://img.shields.io/pypi/v/sportsipy.svg :target: https://pypi.org/project/sportsipy
.. contents::
Sportsipy is a free python API that pulls the stats from www.sports-reference.com and allows them to be easily be used in python-based applications, especially ones involving data analytics and machine learning.
Sportsipy exposes a plethora of sports information from major sports leagues in North America, such as the MLB, NBA, College Football and Basketball, NFL, and NHL. Sportsipy also now supports Professional Football (or Soccer) for thousands of teams from leagues around the world. Every sport has its own set of valid API queries ranging from the list of teams in a league, to the date and time of a game, to the total number of wins a team has secured during the season, and many, many more metrics that paint a more detailed picture of how a team has performed during a game or throughout a season.
The easiest way to install sportsipy is by downloading the latest
released binary from PyPI using PIP. For instructions on installing PIP, visit
PyPA.io <https://pip.pypa.io/en/stable/installing/>_ for detailed steps on
installing the package manager for your local environment.
Next, run::
pip install sportsipyto download and install the latest official release of sportsipy on
your machine. You now have the latest stable version of sportsipy
installed and can begin using it following the examples below!
If the bleeding-edge version of sportsipy is desired, clone this
repository using git and install all of the package requirements with PIP::
git clone https://github.com/roclark/sportsipy
cd sportsipy
pip install -r requirements.txtOnce complete, create a Python wheel for your default version of Python by running the following command::
python setup.py sdist bdist_wheelThis will create a .whl file in the dist directory which can be installed
with the following command::
pip install dist/*.whlThe following are a few examples showcasing how easy it can be to collect
an abundance of metrics and information from all of the tracked leagues. The
examples below are only a miniscule subset of the total number of statistics
that can be pulled using sportsipy. Visit the documentation on
Read The Docs <http://sportsipy.readthedocs.io/en/latest/>_ for a
complete list of all information exposed by the API.
.. code-block:: python
from sportsipy.nhl.teams import Teams
teams = Teams(2018).. code-block:: python
from sportsipy.nba.teams import Teams
teams = Teams()
for team in teams:
print(team.name, team.abbreviation).. code-block:: python
from sportsipy.nfl.teams import Teams
teams = Teams()
lions = teams('DET').. code-block:: python
from sportsipy.ncaab.schedule import Schedule
purdue_schedule = Schedule('purdue')
for game in purdue_schedule:
print(game.date).. code-block:: python
from sportsipy.ncaaf.boxscore import Boxscore
championship_game = Boxscore('2018-01-08-georgia')
print(championship_game.away_interceptions).. code-block:: python
from sportsipy.mlb.boxscore import Boxscore
game = Boxscore('BOS201806070')
df = game.dataframe.. code-block:: python
from sportsipy.fb.team import Team
tottenham = Team('Tottenham Hotspur')
print(tottenham.goals_scored)Two blog posts detailing the creation and basic usage of sportsipy can
be found on The Medium at the following links:
Part 1: Creating a public sports API <https://medium.com/clarktech-sports/python-sports-analytics-made-simple-part-1-14569d6e9a86>_Part 2: Pull any sports metric in 10 lines of Python <https://medium.com/clarktech-sports/python-sports-analytics-made-simple-part-2-40e591a7f3db>_The second post in particular is a great guide for getting started with
sportsipy and is highly recommended for anyone who is new to the
package.
Complete documentation is hosted on
readthedocs.org <http://sportsipy.readthedocs.io/en/latest>_. Refer to
the documentation for a full list of all metrics and information exposed by
sportsipy. The documentation is auto-generated using Sphinx based on the
docstrings in the sportsipy package.
Sportsipy contains a testing suite which aims to test all major portions of code for proper functionality. To run the test suite against your environment, ensure all of the requirements are installed by running::
pip install -r requirements.txtNext, start the tests by running py.test while optionally including coverage flags which identify the amount of production code covered by the testing framework::
py.test --cov=sportsipy --cov-report term-missing tests/If the tests were successful, it will return a green line will show a message at the end of the output similar to the following::
======================= 380 passed in 245.56 seconds =======================If a test failed, it will show the number of failed and what went wrong within the test output. If that's the case, ensure you have the latest version of code and are in a supported environment. Otherwise, create an issue on GitHub to attempt to get the issue resolved.