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%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 <Python_Bot@openeuler.org> - 1.0.31-1
- Package Spec generated
|
