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%global _empty_manifest_terminate_build 0
Name: python-sortedcontainers
Version: 2.4.0
Release: 1
Summary: Sorted Containers -- Sorted List, Sorted Dict, Sorted Set
License: Apache 2.0
URL: http://www.grantjenks.com/docs/sortedcontainers/
Source0: https://mirrors.nju.edu.cn/pypi/web/packages/e8/c4/ba2f8066cceb6f23394729afe52f3bf7adec04bf9ed2c820b39e19299111/sortedcontainers-2.4.0.tar.gz
BuildArch: noarch
%description
`Sorted Containers`_ is an Apache2 licensed `sorted collections library`_,
written in pure-Python, and fast as C-extensions.
Python's standard library is great until you need a sorted collections
type. Many will attest that you can get really far without one, but the moment
you **really need** a sorted list, sorted dict, or sorted set, you're faced
with a dozen different implementations, most using C-extensions without great
documentation and benchmarking.
In Python, we can do better. And we can do it in pure-Python!
>>> from sortedcontainers import SortedList
>>> sl = SortedList(['e', 'a', 'c', 'd', 'b'])
>>> sl
SortedList(['a', 'b', 'c', 'd', 'e'])
>>> sl *= 10_000_000
>>> sl.count('c')
10000000
>>> sl[-3:]
['e', 'e', 'e']
>>> from sortedcontainers import SortedDict
>>> sd = SortedDict({'c': 3, 'a': 1, 'b': 2})
>>> sd
SortedDict({'a': 1, 'b': 2, 'c': 3})
>>> sd.popitem(index=-1)
('c', 3)
>>> from sortedcontainers import SortedSet
>>> ss = SortedSet('abracadabra')
>>> ss
SortedSet(['a', 'b', 'c', 'd', 'r'])
>>> ss.bisect_left('c')
2
All of the operations shown above run in faster than linear time. The above
demo also takes nearly a gigabyte of memory to run. When the sorted list is
multiplied by ten million, it stores ten million references to each of "a"
through "e". Each reference requires eight bytes in the sorted
container. That's pretty hard to beat as it's the cost of a pointer to each
object. It's also 66% less overhead than a typical binary tree implementation
(e.g. Red-Black Tree, AVL-Tree, AA-Tree, Splay-Tree, Treap, etc.) for which
every node must also store two pointers to children nodes.
`Sorted Containers`_ takes all of the work out of Python sorted collections -
making your deployment and use of Python easy. There's no need to install a C
compiler or pre-build and distribute custom extensions. Performance is a
feature and testing has 100% coverage with unit tests and hours of stress.
%package -n python3-sortedcontainers
Summary: Sorted Containers -- Sorted List, Sorted Dict, Sorted Set
Provides: python-sortedcontainers
BuildRequires: python3-devel
BuildRequires: python3-setuptools
BuildRequires: python3-pip
%description -n python3-sortedcontainers
`Sorted Containers`_ is an Apache2 licensed `sorted collections library`_,
written in pure-Python, and fast as C-extensions.
Python's standard library is great until you need a sorted collections
type. Many will attest that you can get really far without one, but the moment
you **really need** a sorted list, sorted dict, or sorted set, you're faced
with a dozen different implementations, most using C-extensions without great
documentation and benchmarking.
In Python, we can do better. And we can do it in pure-Python!
>>> from sortedcontainers import SortedList
>>> sl = SortedList(['e', 'a', 'c', 'd', 'b'])
>>> sl
SortedList(['a', 'b', 'c', 'd', 'e'])
>>> sl *= 10_000_000
>>> sl.count('c')
10000000
>>> sl[-3:]
['e', 'e', 'e']
>>> from sortedcontainers import SortedDict
>>> sd = SortedDict({'c': 3, 'a': 1, 'b': 2})
>>> sd
SortedDict({'a': 1, 'b': 2, 'c': 3})
>>> sd.popitem(index=-1)
('c', 3)
>>> from sortedcontainers import SortedSet
>>> ss = SortedSet('abracadabra')
>>> ss
SortedSet(['a', 'b', 'c', 'd', 'r'])
>>> ss.bisect_left('c')
2
All of the operations shown above run in faster than linear time. The above
demo also takes nearly a gigabyte of memory to run. When the sorted list is
multiplied by ten million, it stores ten million references to each of "a"
through "e". Each reference requires eight bytes in the sorted
container. That's pretty hard to beat as it's the cost of a pointer to each
object. It's also 66% less overhead than a typical binary tree implementation
(e.g. Red-Black Tree, AVL-Tree, AA-Tree, Splay-Tree, Treap, etc.) for which
every node must also store two pointers to children nodes.
`Sorted Containers`_ takes all of the work out of Python sorted collections -
making your deployment and use of Python easy. There's no need to install a C
compiler or pre-build and distribute custom extensions. Performance is a
feature and testing has 100% coverage with unit tests and hours of stress.
%package help
Summary: Development documents and examples for sortedcontainers
Provides: python3-sortedcontainers-doc
%description help
`Sorted Containers`_ is an Apache2 licensed `sorted collections library`_,
written in pure-Python, and fast as C-extensions.
Python's standard library is great until you need a sorted collections
type. Many will attest that you can get really far without one, but the moment
you **really need** a sorted list, sorted dict, or sorted set, you're faced
with a dozen different implementations, most using C-extensions without great
documentation and benchmarking.
In Python, we can do better. And we can do it in pure-Python!
>>> from sortedcontainers import SortedList
>>> sl = SortedList(['e', 'a', 'c', 'd', 'b'])
>>> sl
SortedList(['a', 'b', 'c', 'd', 'e'])
>>> sl *= 10_000_000
>>> sl.count('c')
10000000
>>> sl[-3:]
['e', 'e', 'e']
>>> from sortedcontainers import SortedDict
>>> sd = SortedDict({'c': 3, 'a': 1, 'b': 2})
>>> sd
SortedDict({'a': 1, 'b': 2, 'c': 3})
>>> sd.popitem(index=-1)
('c', 3)
>>> from sortedcontainers import SortedSet
>>> ss = SortedSet('abracadabra')
>>> ss
SortedSet(['a', 'b', 'c', 'd', 'r'])
>>> ss.bisect_left('c')
2
All of the operations shown above run in faster than linear time. The above
demo also takes nearly a gigabyte of memory to run. When the sorted list is
multiplied by ten million, it stores ten million references to each of "a"
through "e". Each reference requires eight bytes in the sorted
container. That's pretty hard to beat as it's the cost of a pointer to each
object. It's also 66% less overhead than a typical binary tree implementation
(e.g. Red-Black Tree, AVL-Tree, AA-Tree, Splay-Tree, Treap, etc.) for which
every node must also store two pointers to children nodes.
`Sorted Containers`_ takes all of the work out of Python sorted collections -
making your deployment and use of Python easy. There's no need to install a C
compiler or pre-build and distribute custom extensions. Performance is a
feature and testing has 100% coverage with unit tests and hours of stress.
%prep
%autosetup -n sortedcontainers-2.4.0
%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-sortedcontainers -f filelist.lst
%dir %{python3_sitelib}/*
%files help -f doclist.lst
%{_docdir}/*
%changelog
* Fri Apr 21 2023 Python_Bot <Python_Bot@openeuler.org> - 2.4.0-1
- Package Spec generated
|
