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Python utility to easily scrape NBA stats

Project description

# nba_scrape

An easy-to-use Python utility to scrape professional basketball data off stats.nba.com using Selenium and BeautifulSoup.

## Installation:

pip install nba_scrape

## Usage:

from nba_scrape import NBA

#### Example:

>>> league = NBA()

>>> lebron = league.get_player(‘lebron james’)

>>> lebron.get_stat(‘pts’, ‘2016-17’, playoffs=True)

>>> 32.8

>>> lebron.get_stats([‘pts’, ‘reb’, ‘ast’, ‘ts%’], ‘2015-18’, mode=’playoffs’)

>>> {‘2015-16’: (26.3, 9.5, 7.6, 0.585), ‘2016-17’: (32.8, 9.1, 7.8, 0.649), ‘2017-18’: (34, 9.1, 9, 0.619)}

#### Get an instance of the NBA class:

league = NBA()

#### Get a player:

player = league.get_player(player_name)

OR

player = league.get_player_by_id(id_number)

#### Get a single stat:

player.get_stat(stat_name, season)

#### Get multiple stats (formatted as a dict with tuples as items):

player.get_stats([stat1, stat2, stat3], season_range, mode=mode)

(Possible modes are ‘season’, ‘playoffs’, or ‘both’; ‘season’ is the default.)

## Current functionality:

  1. Compile a list of all NBA players and their IDs when initializing the NBA class.
  2. Easily load all regular season and playoff stats off a player’s career page to a SQLite database. Only the player’s name is required as input.
  3. Retrieve all traditional stats and select advanced ones (such as True Shooting Percentage) via database queries; only the requested stats and seasons are required as input.
  4. Browser-agnostic; uses the best available browser or raises an error if no supported browser is available.
  5. Test suite to ensure correct statistics are returned.

Project details


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