sportsipy 0.6.0

Description:

sportsipy 0.6.0

Contents

Installation
Examples

Get instances of all NHL teams for the 2018 season
Print every NBA team’s name and abbreviation
Get a specific NFL team’s season information
Print the date of every game for a NCAA Men’s Basketball team
Print the number of interceptions by the away team in a NCAA Football game
Get a Pandas DataFrame of all stats for a MLB game
Find the number of goals a football team has scored


Documentation
Testing


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.

Installation
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 for detailed steps on
installing the package manager for your local environment.
Next, run:
pip install sportsipy
to 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.txt
Once complete, create a Python wheel for your default version of Python by
running the following command:
python setup.py sdist bdist_wheel
This will create a .whl file in the dist directory which can be installed
with the following command:
pip install dist/*.whl


Examples
The 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 for a
complete list of all information exposed by the API.

Get instances of all NHL teams for the 2018 season
from sportsipy.nhl.teams import Teams

teams = Teams(2018)


Print every NBA team’s name and abbreviation
from sportsipy.nba.teams import Teams

teams = Teams()
for team in teams:
print(team.name, team.abbreviation)


Get a specific NFL team’s season information
from sportsipy.nfl.teams import Teams

teams = Teams()
lions = teams('DET')


Print the date of every game for a NCAA Men’s Basketball team
from sportsipy.ncaab.schedule import Schedule

purdue_schedule = Schedule('purdue')
for game in purdue_schedule:
print(game.date)


Print the number of interceptions by the away team in a NCAA Football game
from sportsipy.ncaaf.boxscore import Boxscore

championship_game = Boxscore('2018-01-08-georgia')
print(championship_game.away_interceptions)


Get a Pandas DataFrame of all stats for a MLB game
from sportsipy.mlb.boxscore import Boxscore

game = Boxscore('BOS201806070')
df = game.dataframe


Find the number of goals a football team has scored
from sportsipy.fb.team import Team

tottenham = Team('Tottenham Hotspur')
print(tottenham.goals_scored)



Documentation
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
Part 2: Pull any sports metric in 10 lines of Python

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. 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.


Testing
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.txt
Next, 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.