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    "info": {
        "author": "Jae Bradley",
        "author_email": "jae.b.bradley@gmail.com",
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        "classifiers": [
            "License :: OSI Approved :: MIT License",
            "Operating System :: OS Independent",
            "Programming Language :: Python :: 3"
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        "description": "# Basketball Reference Web Scraper\n\n[![Build Status](https://travis-ci.org/jaebradley/basketball_reference_web_scraper.svg?branch=master)](https://travis-ci.org/jaebradley/basketball_reference_web_scraper)\n[![PyPI version](https://badge.fury.io/py/basketball_reference_web_scraper.svg)](https://badge.fury.io/py/basketball_reference_web_scraper)\n[![codecov](https://codecov.io/gh/jaebradley/basketball_reference_web_scraper/branch/master/graph/badge.svg)](https://codecov.io/gh/jaebradley/basketball_reference_web_scraper)\n\n[Basketball Reference](http://www.basketball-reference.com) is a great site (especially for a basketball stats nut like me), and hopefully they don't get too pissed off at me for creating this.\n\nBasically, I created this repository as a utility for another project where I'm trying to estimate an NBA player's productivity as it relates to daily fantasy sports.  For that project, I need box score and scheduling information, which is provided by this utility. \n\nHere's the [PyPi package](https://pypi.python.org/pypi/basketball_reference_web_scraper/3.0).\n\n## Installing via pip\n\nI wrote this library as an exercise for creating my first `PyPi` package.  \n\nHopefully this means that if you'd like to use this library, you can by simply downloading the package via [pip](https://pypi.python.org/pypi/pip) like so\n\n```bash\npip install basketball_reference_web_scraper\n```\n\nThis library requires `Python 3.4+` and only supports seasons after the `1999-2000` season\n\n## Client\n\nYou can import the `client` like this\n\n```python\n# This imports the client\nfrom basketball_reference_web_scraper import client\n```\n\nThere are also a couple useful `enum`s that are defined in the `data` module which can be `import`ed like\n\n```python\n# This imports the Team enum\nfrom basketball_reference_web_scraper.data import Team\n```\n\n## API\n\nThis client has five methods\n* Getting player box scores by a date (`client.player_box_scores`)\n* Getting team box scores by a date (`client.team_box_scores`)\n* Getting the schedule for a season (`client.season_schedule`)\n* Getting players totals for a season (`client.players_season_totals`)\n* Getting players advanced season statistics for a season (`client.players_advanced_season_totals`)\n\nYou can see all methods used in [this `repl`]()https://repl.it/@jaebradley/v300api-examples).\n\n### Data output\n\nThis client also supports three output types:\n* Python data types (i.e. a `list` or results)\n* `JSON`\n* `CSV`\n\nVersions `>=3` of this client outputs `CSV` to a specified file path and returns `JSON` output or writes it to a specified file path.\n* Specify an output type by setting the `output_type` value to `OutputType.JSON` or `OutputType.CSV`\n  * The default return value of client methods are `Python` data structures (the `box_scores` method returns a `list` of `dict`s)\n* If you'd like the output to be outputted to a specific file, set the `output_file_path` variable - for `CSV` output, this variable must be defined\n* Specifying an `output_write_option` specifies how the output will be written to the specified file (`OutputWriteOption.WRITE` corresponds to `w`)\n  * The default write option is `OutputWriteOption.WRITE`\n\n### Data parsing\n\n* Some pieces of data, like a player's team or the outcome of a game are parsed into enums (for example, the `Team` and `Outcome` enums, respectively, for the previous two examples)\n* These enums are serialized to strings when outputting to `JSON` or `CSV`, but when dealing with `Python` data structures, you'll see these enum values.\n  * Hopefully, these enums make it easier for the `client `user to implement team-specific logic, for example.  \n\n\n### Get player box scores by date\n\n```python\nfrom basketball_reference_web_scraper import client\nfrom basketball_reference_web_scraper.data import OutputType\n\n# Get all player box scores for January 1st, 2017 \nclient.player_box_scores(day=1, month=1, year=2017)\n\n# Get all player box scores for January 1st, 2017 in JSON format\nclient.player_box_scores(day=1, month=1, year=2017, output_type=OutputType.JSON)\n\n# Output all player box scores for January 1st, 2017 in JSON format to 1_1_2017_box_scores.json\nclient.player_box_scores(day=1, month=1, year=2017, output_type=OutputType.JSON, output_file_path=\"./1_1_2017_box_scores.json\")\n\n# Output all player box scores for January 1st, 2017 in JSON format to 1_1_2017_box_scores.csv\nclient.player_box_scores(day=1, month=1, year=2017, output_type=OutputType.CSV, output_file_path=\"./1_1_2017_box_scores.csv\")\n```\n\n### Get team box scores by date\n\n```python\nfrom basketball_reference_web_scraper import client\n\n# Get all team totals for January 1st, 2018\nclient.team_box_scores(day=1, month=1, year=2018)\n\n# The team_box_scores method also supports all output behavior previously described\n```\n\n### Get season schedule\n\n```python\nfrom basketball_reference_web_scraper import client\n\n# Get all games for the 2017-2018 season\nclient.season_schedule(season_end_year=2018)\n\n# The schedule method also supports all output behavior previously described\n``` \n\n### Get season totals for all players\n\n```python\nfrom basketball_reference_web_scraper import client\n\n# Get 2017-2018 season totals for all players\nclient.players_season_totals(season_end_year=2018)\n\n# The players_season_totals method also supports all output behavior previously described\n```\n\n### Get advanced season statistics for all players\n\n```python\nfrom basketball_reference_web_scraper import client\n\n# Get 2017-2018 advanced season statistics for all players\nclient.players_advanced_season_totals(season_end_year=2018)\n\n# The players_advanced_season_totals method also supports all output behavior previously described\n```\n\n### Get play-by-play data for a game\n\nThe structure of the API is due to the unique URL pattern that Basketball Reference has for getting play-by-play data, \nwhich depends on the date of the game and the home team.\n\nExample: `https://www.basketball-reference.com/boxscores/pbp/201810160BOS.html`\n\n```python\nfrom basketball_reference_web_scraper import client\nfrom basketball_reference_web_scraper.data import Team\n\n# Get play-by-play data for 2018-10-16 game played at the Boston Celtics\nplay_by_play = client.play_by_play(\n    home_team=Team.BOSTON_CELTICS,\n    year=2018,\n    month=10,\n    day=16,\n)\n```\n\n## Development\n\nThere are currently two supported major versions - `V3` and `V4`.\n\nThere are two branches, `v3` and `v4` for both of these major versions - these are the defacto \"master\" branches to use\nwhen making changes.\n\n`master` will reflect the latest major version branch.\n\n## Contributors\n\nThanks to [@DaiJunyan](https://github.com/DaiJunyan) for their contributions!\n\n\n\n",
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