%global _empty_manifest_terminate_build 0 Name: python-basketball-reference-scraper Version: 1.0.31 Release: 1 Summary: A Python client for scraping stats and data from Basketball Reference License: MIT URL: https://github.com/vishaalagartha/basketball_reference_scraper Source0: https://mirrors.nju.edu.cn/pypi/web/packages/b7/d9/d305b624569f7fdda759a20bd3387a7f837f3fc7eb6b381db33fb412529b/basketball_reference_scraper-1.0.31.tar.gz BuildArch: noarch Requires: python3-beautifulsoup4 Requires: python3-bs4 Requires: python3-lxml Requires: python3-numpy Requires: python3-pandas Requires: python3-dateutil Requires: python3-pytz Requires: python3-requests Requires: python3-six Requires: python3-soupsieve Requires: python3-unidecode Requires: python3-unittest %description # basketball_reference_scraper [Basketball Reference](https://www.basketball-reference.com/) is a great 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. ## 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). ### 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). %package -n python3-basketball-reference-scraper Summary: A Python client for scraping stats and data from Basketball Reference Provides: python-basketball-reference-scraper BuildRequires: python3-devel BuildRequires: python3-setuptools BuildRequires: python3-pip %description -n python3-basketball-reference-scraper # basketball_reference_scraper [Basketball Reference](https://www.basketball-reference.com/) is a great 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. ## 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). ### 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). %package help Summary: Development documents and examples for basketball-reference-scraper Provides: python3-basketball-reference-scraper-doc %description help # basketball_reference_scraper [Basketball Reference](https://www.basketball-reference.com/) is a great 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. ## 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). ### 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). %prep %autosetup -n basketball_reference_scraper-1.0.31 %build %py3_build %install %py3_install install -d -m755 %{buildroot}/%{_pkgdocdir} if [ -d doc ]; then cp -arf doc %{buildroot}/%{_pkgdocdir}; fi if [ -d docs ]; then cp -arf docs %{buildroot}/%{_pkgdocdir}; fi if [ -d example ]; then cp -arf example %{buildroot}/%{_pkgdocdir}; fi if [ -d examples ]; then cp -arf examples %{buildroot}/%{_pkgdocdir}; fi pushd %{buildroot} if [ -d usr/lib ]; then find usr/lib -type f -printf "\"/%h/%f\"\n" >> filelist.lst fi if [ -d usr/lib64 ]; then find usr/lib64 -type f -printf "\"/%h/%f\"\n" >> filelist.lst fi if [ -d usr/bin ]; then find usr/bin -type f -printf "\"/%h/%f\"\n" >> filelist.lst fi if [ -d usr/sbin ]; then find usr/sbin -type f -printf "\"/%h/%f\"\n" >> filelist.lst fi touch doclist.lst if [ -d usr/share/man ]; then find usr/share/man -type f -printf "\"/%h/%f.gz\"\n" >> doclist.lst fi popd mv %{buildroot}/filelist.lst . mv %{buildroot}/doclist.lst . %files -n python3-basketball-reference-scraper -f filelist.lst %dir %{python3_sitelib}/* %files help -f doclist.lst %{_docdir}/* %changelog * Thu Jun 08 2023 Python_Bot - 1.0.31-1 - Package Spec generated