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mlbgame

mlbgame demo

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mlbgame is a Python API to retrieve and read MLB GameDay XML data. mlbgame works with real time data, getting information as games are being played.

mlbgame uses the same data that MLB GameDay uses, and therefore is updated as soon as something happens in a game.

mlbgame currently comes pre-loaded with scoreboard information for every game from 2012 to the end of the 2016 season. Therefore, accessing this data does not actually make a request to mlb.com.

If you try to get data from a game that is not cached, mlbgame will download the data from mlb.com.

There are a lot of extra data for individual games that do not come pre-installed with mlbgame, but can be installed by running update scripts shown below. This data is not included because it takes up too much space, and therefore a request to mlb.com every time is a better option because not everyone will want to access this data.

mlbgame documentation

mlbgame on Github (Source Code)

If you have a question or need help, the quickest way to get a response is to file an issue on the Github issue tracker

mlbgame's submodules (except for statmap) should not really be used other than as used by the main functions of the package (in __init__.py).

Installation

mlbgame is in the Python Package Index (PyPI). Installing with pip is recommended for all systems.

mlbgame can be installed by running:

pip install mlbgame

Alternatively, the latest release of mlbgame can be downloaded as a zip or tarball. If you do not install with pip, you must also install the dependencies as specified in setup.py.

If you want to help develop mlbgame, you must also install the dev dependencies, which can be done by running pip install -e .[dev] from within the directory.

Updating the Game Database

Since games happen every day, new game data exists that is not stored on disk from the original install. The database can be updated by running the following command:

mlbgame-update

There are some optional arguments that will cache extra data that is not included with the original install. This extra data may take up a lot of disk space, so only cache if you really need it (it will make processes much faster). If this data is not cached, mlbgame will make a request to mlb.com every time you try to access the data.

usage: mlbgame-update <arguments>

Arguments:
--help (-h): display this help menu
--clear: delete all cached data
--hide: hides output from update script
--stats: saves the box scores and individual game stats from every game
--events: saves the game events from every game
--overview: saves the game overview from every game
--start (-s) <MM-DD-YYYY>: date to start updating from (default: 01-01-2012)
--end (-e) <MM-DD-YYYY>: date to update until (default: current day)

Use of mlbgame must follow the terms stated in the license and on mlb.com.

Examples

Here is a quick teaser to find the scores of all home Mets games for the month of June, 2015:

from __future__ import print_function
import mlbgame

month = mlbgame.games(2015, 6, home="Mets")
games = mlbgame.combine_games(month)
for game in games:
    print(game)

And the output is:

Giants (5) at Mets (0)
Giants (8) at Mets (5)
Giants (4) at Mets (5)
Braves (3) at Mets (5)
Braves (5) at Mets (3)
Braves (8) at Mets (10)
Blue Jays (3) at Mets (4)
Blue Jays (2) at Mets (3)
Reds (1) at Mets (2)
Reds (1) at Mets (2)
Reds (1) at Mets (2)
Reds (2) at Mets (7)
Cubs (1) at Mets (0)

Maybe you want to know the pitchers for the Royals game on April 30th, 2015:

from __future__ import print_function
import mlbgame

day = mlbgame.day(2015, 4, 12, home="Royals", away="Royals")
game = day[0]
output = "Winning pitcher: %s (%s) - Losing Pitcher: %s (%s)"
print(output % (game.w_pitcher, game.w_team, game.l_pitcher, game.l_team))

And the output is:

Winning pitcher: Y. Ventura (Royals) - Losing Pitcher: C. Wilson (Angels)

You can easily find stats for the Mets batters in the final game of the 2015 World Series:

from __future__ import print_function
import mlbgame

game = mlbgame.day(2015, 11, 1, home="Mets")[0]
stats = mlbgame.player_stats(game.game_id)
for player in stats['home_batting']:
    print(player)

And the output is:

Curtis Granderson - 1 for 4 with 1 RBI and 1 Home Runs
David Wright - 1 for 5
Daniel Murphy - 0 for 3
Yoenis Cespedes - 0 for 3
Juan Lagares - 0 for 2
Lucas Duda - 0 for 2 with 1 RBI
Travis d'Arnaud - 0 for 5
Michael Conforto - 2 for 5
Wilmer Flores - 0 for 4
Matt Harvey - 0 for 3
Jeurys Familia - 0 for 0
Kelly Johnson - 0 for 1
Jon Niese - 0 for 0
Addison Reed - 0 for 0
Bartolo Colon - 0 for 0

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A Python API to retrieve and read MLB GameDay XML data

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