%global _empty_manifest_terminate_build 0
Name:		python-cachetools
Version:	5.3.0
Release:	1
Summary:	Extensible memoizing collections and decorators
License:	MIT
URL:		https://github.com/tkem/cachetools/
Source0:	https://mirrors.nju.edu.cn/pypi/web/packages/4d/91/5837e9f9e77342bb4f3ffac19ba216eef2cd9b77d67456af420e7bafe51d/cachetools-5.3.0.tar.gz
BuildArch:	noarch


%description
This module provides various memoizing collections and decorators,
including variants of the Python Standard Library's `@lru_cache`_
function decorator.
   from cachetools import cached, LRUCache, TTLCache
   # speed up calculating Fibonacci numbers with dynamic programming
   @cached(cache={})
   def fib(n):
       return n if n < 2 else fib(n - 1) + fib(n - 2)
   # cache least recently used Python Enhancement Proposals
   @cached(cache=LRUCache(maxsize=32))
   def get_pep(num):
       url = 'http://www.python.org/dev/peps/pep-%04d/' % num
       with urllib.request.urlopen(url) as s:
           return s.read()
   # cache weather data for no longer than ten minutes
   @cached(cache=TTLCache(maxsize=1024, ttl=600))
   def get_weather(place):
       return owm.weather_at_place(place).get_weather()
For the purpose of this module, a *cache* is a mutable_ mapping_ of a
fixed maximum size.  When the cache is full, i.e. by adding another
item the cache would exceed its maximum size, the cache must choose
which item(s) to discard based on a suitable `cache algorithm`_.
This module provides multiple cache classes based on different cache
algorithms, as well as decorators for easily memoizing function and
method calls.

%package -n python3-cachetools
Summary:	Extensible memoizing collections and decorators
Provides:	python-cachetools
BuildRequires:	python3-devel
BuildRequires:	python3-setuptools
BuildRequires:	python3-pip
%description -n python3-cachetools
This module provides various memoizing collections and decorators,
including variants of the Python Standard Library's `@lru_cache`_
function decorator.
   from cachetools import cached, LRUCache, TTLCache
   # speed up calculating Fibonacci numbers with dynamic programming
   @cached(cache={})
   def fib(n):
       return n if n < 2 else fib(n - 1) + fib(n - 2)
   # cache least recently used Python Enhancement Proposals
   @cached(cache=LRUCache(maxsize=32))
   def get_pep(num):
       url = 'http://www.python.org/dev/peps/pep-%04d/' % num
       with urllib.request.urlopen(url) as s:
           return s.read()
   # cache weather data for no longer than ten minutes
   @cached(cache=TTLCache(maxsize=1024, ttl=600))
   def get_weather(place):
       return owm.weather_at_place(place).get_weather()
For the purpose of this module, a *cache* is a mutable_ mapping_ of a
fixed maximum size.  When the cache is full, i.e. by adding another
item the cache would exceed its maximum size, the cache must choose
which item(s) to discard based on a suitable `cache algorithm`_.
This module provides multiple cache classes based on different cache
algorithms, as well as decorators for easily memoizing function and
method calls.

%package help
Summary:	Development documents and examples for cachetools
Provides:	python3-cachetools-doc
%description help
This module provides various memoizing collections and decorators,
including variants of the Python Standard Library's `@lru_cache`_
function decorator.
   from cachetools import cached, LRUCache, TTLCache
   # speed up calculating Fibonacci numbers with dynamic programming
   @cached(cache={})
   def fib(n):
       return n if n < 2 else fib(n - 1) + fib(n - 2)
   # cache least recently used Python Enhancement Proposals
   @cached(cache=LRUCache(maxsize=32))
   def get_pep(num):
       url = 'http://www.python.org/dev/peps/pep-%04d/' % num
       with urllib.request.urlopen(url) as s:
           return s.read()
   # cache weather data for no longer than ten minutes
   @cached(cache=TTLCache(maxsize=1024, ttl=600))
   def get_weather(place):
       return owm.weather_at_place(place).get_weather()
For the purpose of this module, a *cache* is a mutable_ mapping_ of a
fixed maximum size.  When the cache is full, i.e. by adding another
item the cache would exceed its maximum size, the cache must choose
which item(s) to discard based on a suitable `cache algorithm`_.
This module provides multiple cache classes based on different cache
algorithms, as well as decorators for easily memoizing function and
method calls.

%prep
%autosetup -n cachetools-5.3.0

%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-cachetools -f filelist.lst
%dir %{python3_sitelib}/*

%files help -f doclist.lst
%{_docdir}/*

%changelog
* Mon Apr 10 2023 Python_Bot <Python_Bot@openeuler.org> - 5.3.0-1
- Package Spec generated