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basketball_reference_scraper

(★ 290)

A python module for scraping static and dynamic content from Basketball Reference.

파일 탐색기

최종 버전 다운로드 (.zip)

- - main.yml
- __init__.py
- box_scores.py
- br_names.txt
- constants.py
- drafts.py
- injury_report.py
- lookup.py
- pbp.py
- players.py
- request_utils.py
- seasons.py
- shot_charts.py
- teams.py
- utils.py
- __init__.py
- test_box_scores.py
- test_drafts.py
- test_injury_report.py
- test_pbp.py
- test_players.py
- test_seasons.py
- test_shot_charts.py
- test_teams.py
.gitignore
__init__.py
API.md
examples.py
LICENSE
README.md
requirements.txt
setup.py

# 설치 가이드

1. 코드 내려받기

git clone https://github.com/vishaalagartha/basketball_reference_scraper

깃허브에서 프로젝트 코드 전체를 내 컴퓨터로 내려받습니다.

cd basketball_reference_scraper

방금 내려받은 프로젝트 폴더 안으로 이동합니다.

2. 공식 설치 스크립트

쉬움 추천

사전 준비물

Python 3 pip 명령어를 쓰려면 Python이 필요합니다.

pip install basketball-reference-scraper

PyPI에 배포된 패키지를 바로 설치합니다. 소스 클론이 필요 없습니다.

✅ 설치 후 새 터미널을 열고, 프로그램의 버전 확인 명령(예: --version)으로 정상 설치됐는지 확인하세요.

이 레포의 README에 적힌 실제 명령어를 그대로 가져왔습니다.

3. Python

쉬움

사전 준비물

Git GitHub에서 프로젝트 코드를 내려받으려면 필요합니다.
Python 3 설치 시 'Add Python to PATH' 옵션을 꼭 체크하세요 (Windows).

pip install basketball-reference-scraper

PyPI에 배포된 패키지를 바로 설치합니다. 소스 클론이 필요 없습니다.

✅ 에러 메시지 없이 실행되고 터미널에 안내 문구가 출력되면 정상입니다.

이 레포의 README에 적힌 실제 명령어를 그대로 가져왔습니다.

// repository documentation

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# basketball_reference_scraper

[Basketball Reference](https://www.basketball-reference.com/) is a resource to aggregate statistics on NBA teams, seasons, players, and games. This package provides methods to acquire data for all these categories in pre-parsed and simplified formats.

## Installing
### Via `pip`
I wrote this library as an exercise for creating my first PyPi package. Hopefully, you find it easy to use.
Install using the following command:

```
pip install basketball-reference-scraper
```

### Via GitHub
Alternatively, you can just clone this repo and import the libraries at your own discretion.

### Selenium

This package can also capture dynamically rendered content that is being added to the page via JavaScript, rather than baked into the HTML. To achieve this, it uses [Python Selenium](https://selenium-python.readthedocs.io/). Please refer to their [installation instructions](https://selenium-python.readthedocs.io/installation.html) and ensure you have [Chrome webdriver](https://selenium-python.readthedocs.io/installation.html#drivers) installed in and in your `PATH` variable.

## Wait, don't scrapers like this already exist?

Yes, scrapers and APIs do exist. The primary API used currently is for [stats.nba.com](https://stats.nba.com/), but the website blocks too many requests, hindering those who want to acquire a lot of data. Additionally, scrapers for [Basketball Reference](https://www.basketball-reference.com/) do exist, but none of them load dynamically rendered content. These scrapers can only acquire statically loaded content, preventing those who want statistics in certain formats (for example, Player Advanced Stats Per Game).

Most of the scrapers use outdated methodologies of scraping from `'https://widgets.sports-reference.com/'`. This is outdated and Basketball Reference no longer acquires their data from there. Additionally, [Sports Reference recently instituted a rate limiter](https://www.sports-reference.com/bot-traffic.html) preventing users from making an excess of 20 requests/minute. This package abstracts the waiting logic to ensure you never hit this threshold.

### API
Currently, the package contains 5 modules: `teams`, `players`, `seasons`, `box_scores`, `pbp`, `shot_charts`, and `injury_report`. 
The package will be expanding to include other content as well, but this is a start.

For full details on the API please refer to the [documentation](https://github.com/vishaalagartha/basketball_reference_scraper/blob/master/API.md).