From d7d565b1a9ea2ef4332a81842d213301f5ef7f31 Mon Sep 17 00:00:00 2001 From: CoprDistGit Date: Tue, 11 Apr 2023 14:04:12 +0000 Subject: automatic import of python-cachey --- .gitignore | 1 + python-cachey.spec | 130 +++++++++++++++++++++++++++++++++++++++++++++++++++++ sources | 1 + 3 files changed, 132 insertions(+) create mode 100644 python-cachey.spec create mode 100644 sources diff --git a/.gitignore b/.gitignore index e69de29..27ac5cb 100644 --- a/.gitignore +++ b/.gitignore @@ -0,0 +1 @@ +/cachey-0.2.1.tar.gz diff --git a/python-cachey.spec b/python-cachey.spec new file mode 100644 index 0000000..40c63eb --- /dev/null +++ b/python-cachey.spec @@ -0,0 +1,130 @@ +%global _empty_manifest_terminate_build 0 +Name: python-cachey +Version: 0.2.1 +Release: 1 +Summary: Caching mindful of computation/storage costs +License: BSD +URL: http://github.com/dask/cachey/ +Source0: https://mirrors.nju.edu.cn/pypi/web/packages/c6/9c/e3c959c1601013bf8a72e8bf91ea1ebc6fe8a2305bd2324b039ee0403277/cachey-0.2.1.tar.gz +BuildArch: noarch + +Requires: python3-heapdict + +%description +Humans repeat stuff. Caching helps. +Normal caching policies like LRU aren't well suited for analytic computations +where both the cost of recomputation and the cost of storage routinely vary by +one million or more. Consider the following computations +```python +# Want this +np.std(x) # tiny result, costly to recompute +# Don't want this +np.transpose(x) # huge result, cheap to recompute +``` +Cachey tries to hold on to values that have the following characteristics +1. Expensive to recompute (in seconds) +2. Cheap to store (in bytes) +3. Frequently used +4. Recenty used +It accomplishes this by adding the following to each items score on each access + score += compute_time / num_bytes * (1 + eps) ** tick_time +For some small value of epsilon (which determines the memory halflife.) This +has units of inverse bandwidth, has exponential decay of old results and +roughly linear amplification of repeated results. + +%package -n python3-cachey +Summary: Caching mindful of computation/storage costs +Provides: python-cachey +BuildRequires: python3-devel +BuildRequires: python3-setuptools +BuildRequires: python3-pip +%description -n python3-cachey +Humans repeat stuff. Caching helps. +Normal caching policies like LRU aren't well suited for analytic computations +where both the cost of recomputation and the cost of storage routinely vary by +one million or more. Consider the following computations +```python +# Want this +np.std(x) # tiny result, costly to recompute +# Don't want this +np.transpose(x) # huge result, cheap to recompute +``` +Cachey tries to hold on to values that have the following characteristics +1. Expensive to recompute (in seconds) +2. Cheap to store (in bytes) +3. Frequently used +4. Recenty used +It accomplishes this by adding the following to each items score on each access + score += compute_time / num_bytes * (1 + eps) ** tick_time +For some small value of epsilon (which determines the memory halflife.) This +has units of inverse bandwidth, has exponential decay of old results and +roughly linear amplification of repeated results. + +%package help +Summary: Development documents and examples for cachey +Provides: python3-cachey-doc +%description help +Humans repeat stuff. Caching helps. +Normal caching policies like LRU aren't well suited for analytic computations +where both the cost of recomputation and the cost of storage routinely vary by +one million or more. Consider the following computations +```python +# Want this +np.std(x) # tiny result, costly to recompute +# Don't want this +np.transpose(x) # huge result, cheap to recompute +``` +Cachey tries to hold on to values that have the following characteristics +1. Expensive to recompute (in seconds) +2. Cheap to store (in bytes) +3. Frequently used +4. Recenty used +It accomplishes this by adding the following to each items score on each access + score += compute_time / num_bytes * (1 + eps) ** tick_time +For some small value of epsilon (which determines the memory halflife.) This +has units of inverse bandwidth, has exponential decay of old results and +roughly linear amplification of repeated results. + +%prep +%autosetup -n cachey-0.2.1 + +%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-cachey -f filelist.lst +%dir %{python3_sitelib}/* + +%files help -f doclist.lst +%{_docdir}/* + +%changelog +* Tue Apr 11 2023 Python_Bot - 0.2.1-1 +- Package Spec generated diff --git a/sources b/sources new file mode 100644 index 0000000..53e6a2a --- /dev/null +++ b/sources @@ -0,0 +1 @@ +25f1e2038b319badf1ba0469b8f6d27e cachey-0.2.1.tar.gz -- cgit v1.2.3