This is a pre-production deployment of Warehouse, however changes made here WILL affect the production instance of PyPI.
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Project Description

Purpose

Provide a Python API for accessing NHL game data including play by play, game summaries, player stats et c. The library hides the guts of the NHL website scraping process and encapsulates not only the data gathering, but data output. This project is inspired by the R package nhlscrapr, an all around must for NHL analytics geeks and R power users.

nhlscrapi is in the early/initial stages, but will be updated regularly. Currently, the package support most of the game summary reports, but all of the important and essential ones.

Related projects:

Installation

Getting started is as easy as:

pip install nhlscrapi

For more information on the setup, see the PyPi: nhlscrapi. The documentation for the package can be found at nhlscrapi: NHL Scraper API.

Usage Example

Scrape data for game 1226 of 2014, Ottawa vs Pittsburgh.

from nhlscrapi.games.game import Game, GameKey, GameType
from nhlscrapi.games.cumstats import Score, ShotCt, Corsi, Fenwick

season = 2014                                    # 2013-2014 season
game_num = 1226                                  #
game_type = GameType.Regular                     # regular season game
game_key = GameKey(season, game_type, game_num)

# define stat types that will be counted as the plays are parsed
cum_stats = {
  'Score': Score(),
  'Shots': ShotCt(),
  'Corsi': Corsi(),
  'Fenwick': Fenwick()
}
game = Game(game_key, cum_stats=cum_stats)

# also http requests and processing are lazy
# accumulators require play by play info so they parse the RTSS PBP
print('Final         : {}'.format(game.cum_stats['Score'].total))
print('Shootout      : {}'.format(game.cum_stats['Score'].shootout.total))
print('Shots         : {}'.format(game.cum_stats['Shots'].total))
print('EV Shot Atts  : {}'.format(game.cum_stats['Corsi'].total))
print('Corsi         : {}'.format(game.cum_stats['Corsi'].share()))
print('FW Shot Atts  : {}'.format(game.cum_stats['Fenwick'].total))
print('Fenwick       : {}'.format(game.cum_stats['Fenwick'].share()))

# http req for roster report
# only parses the sections related to officials and coaches
print('\nRefs          : {}'.format(game.refs))
print('Linesman      : {}'.format(game.linesman))
print('Coaches')
print('  Home        : {}'.format(game.home_coach))
print('  Away        : {}'.format(game.away_coach))

# scrape all remaining reports
game.load_all()

Current Release: v0.4.4

This is a pre-release and is not stable and fully fit for production. The first full stable release (v1.0.0) will be made available once the framework for all NHL game reports are completed. Currently, Play-by-Play, Home/Away TOI, Roster, Face-off Comparison and Event Summary reports are functional.

License

The NHL Scraper API is a free Python library provided under Apache License version 2.0.

Release History

Release History

0.4.4

This version

History Node

TODO: Figure out how to actually get changelog content.

Changelog content for this version goes here.

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0.4.3

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Changelog content for this version goes here.

Donec et mollis dolor. Praesent et diam eget libero egestas mattis sit amet vitae augue. Nam tincidunt congue enim, ut porta lorem lacinia consectetur. Donec ut libero sed arcu vehicula ultricies a non tortor. Lorem ipsum dolor sit amet, consectetur adipiscing elit.

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0.4.2

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TODO: Figure out how to actually get changelog content.

Changelog content for this version goes here.

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0.4.1

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Changelog content for this version goes here.

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0.4.0

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TODO: Figure out how to actually get changelog content.

Changelog content for this version goes here.

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0.3.7

History Node

TODO: Figure out how to actually get changelog content.

Changelog content for this version goes here.

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0.3.6

History Node

TODO: Figure out how to actually get changelog content.

Changelog content for this version goes here.

Donec et mollis dolor. Praesent et diam eget libero egestas mattis sit amet vitae augue. Nam tincidunt congue enim, ut porta lorem lacinia consectetur. Donec ut libero sed arcu vehicula ultricies a non tortor. Lorem ipsum dolor sit amet, consectetur adipiscing elit.

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0.3.5

History Node

TODO: Figure out how to actually get changelog content.

Changelog content for this version goes here.

Donec et mollis dolor. Praesent et diam eget libero egestas mattis sit amet vitae augue. Nam tincidunt congue enim, ut porta lorem lacinia consectetur. Donec ut libero sed arcu vehicula ultricies a non tortor. Lorem ipsum dolor sit amet, consectetur adipiscing elit.

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0.3.4

History Node

TODO: Figure out how to actually get changelog content.

Changelog content for this version goes here.

Donec et mollis dolor. Praesent et diam eget libero egestas mattis sit amet vitae augue. Nam tincidunt congue enim, ut porta lorem lacinia consectetur. Donec ut libero sed arcu vehicula ultricies a non tortor. Lorem ipsum dolor sit amet, consectetur adipiscing elit.

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0.3.3

History Node

TODO: Figure out how to actually get changelog content.

Changelog content for this version goes here.

Donec et mollis dolor. Praesent et diam eget libero egestas mattis sit amet vitae augue. Nam tincidunt congue enim, ut porta lorem lacinia consectetur. Donec ut libero sed arcu vehicula ultricies a non tortor. Lorem ipsum dolor sit amet, consectetur adipiscing elit.

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