From 007e7700f26ea37ca962dd73a51ebe83a279f982 Mon Sep 17 00:00:00 2001 From: CoprDistGit Date: Tue, 11 Apr 2023 22:00:05 +0000 Subject: automatic import of python-thread6 --- python-thread6.spec | 237 ++++++++++++++++++++++++++++++++++++++++++++++++++++ 1 file changed, 237 insertions(+) create mode 100644 python-thread6.spec (limited to 'python-thread6.spec') diff --git a/python-thread6.spec b/python-thread6.spec new file mode 100644 index 0000000..f150c66 --- /dev/null +++ b/python-thread6.spec @@ -0,0 +1,237 @@ +%global _empty_manifest_terminate_build 0 +Name: python-thread6 +Version: 0.2.0 +Release: 1 +Summary: A plug n play multithreading interface +License: MIT License +URL: https://github.com/Haizzz/thread6 +Source0: https://mirrors.nju.edu.cn/pypi/web/packages/39/f2/cd7b53367c00a0e4a37c53c5b18007a50fb66f19331699c894c918230b8b/thread6-0.2.0.tar.gz +BuildArch: noarch + + +%description +# thread6 +Simple parallel processing interface for python + +## Why? +Python's built in parallel processing and threading library is pretty simple to implement but sometimes you just want to chuck data at a function and make it run faster + +## Requirements +Python 3+ + +## Installation + +## Quickstart +Use the `threaded` decorator to turn a method into a threaded method. That's it! +```python +@thread6.threaded() +def threaded_print(): + print("") + return 1 +``` + +Alternatively, use `run_threaded` function +```python +thread6.run_threaded(threaded_print) +``` + +Both the `threaded` decorator and `run_threaded` method will return an instance of +`ResultThread`. This allow you to optionally wait for the function to finish executing +and get the return value. To get the return value, use `.await_output()` +```python +result = threaded_print() +result.await_output() # this will return 1 +``` + +If you have a function that needs to execute on a large list of data, use `run_chunked` +```python +def update_items(items): + ... + +items = [...] +thread6.run_chunked(update_items, items) +``` +`.await_output()` also work with `run_chunked` but will return a list of return values instead + +## Usage + + +## Todo +- [x] threaded function decorator +- [x] run something in a separate thread function +- [x] split data into chunk and run in separate threads +- [ ] add way for errors to fail loudly +- [ ] auto spawn to run fx on a set of data +- [ ] explore multi processing? + + + + +%package -n python3-thread6 +Summary: A plug n play multithreading interface +Provides: python-thread6 +BuildRequires: python3-devel +BuildRequires: python3-setuptools +BuildRequires: python3-pip +%description -n python3-thread6 +# thread6 +Simple parallel processing interface for python + +## Why? +Python's built in parallel processing and threading library is pretty simple to implement but sometimes you just want to chuck data at a function and make it run faster + +## Requirements +Python 3+ + +## Installation + +## Quickstart +Use the `threaded` decorator to turn a method into a threaded method. That's it! +```python +@thread6.threaded() +def threaded_print(): + print("") + return 1 +``` + +Alternatively, use `run_threaded` function +```python +thread6.run_threaded(threaded_print) +``` + +Both the `threaded` decorator and `run_threaded` method will return an instance of +`ResultThread`. This allow you to optionally wait for the function to finish executing +and get the return value. To get the return value, use `.await_output()` +```python +result = threaded_print() +result.await_output() # this will return 1 +``` + +If you have a function that needs to execute on a large list of data, use `run_chunked` +```python +def update_items(items): + ... + +items = [...] +thread6.run_chunked(update_items, items) +``` +`.await_output()` also work with `run_chunked` but will return a list of return values instead + +## Usage + + +## Todo +- [x] threaded function decorator +- [x] run something in a separate thread function +- [x] split data into chunk and run in separate threads +- [ ] add way for errors to fail loudly +- [ ] auto spawn to run fx on a set of data +- [ ] explore multi processing? + + + + +%package help +Summary: Development documents and examples for thread6 +Provides: python3-thread6-doc +%description help +# thread6 +Simple parallel processing interface for python + +## Why? +Python's built in parallel processing and threading library is pretty simple to implement but sometimes you just want to chuck data at a function and make it run faster + +## Requirements +Python 3+ + +## Installation + +## Quickstart +Use the `threaded` decorator to turn a method into a threaded method. That's it! +```python +@thread6.threaded() +def threaded_print(): + print("") + return 1 +``` + +Alternatively, use `run_threaded` function +```python +thread6.run_threaded(threaded_print) +``` + +Both the `threaded` decorator and `run_threaded` method will return an instance of +`ResultThread`. This allow you to optionally wait for the function to finish executing +and get the return value. To get the return value, use `.await_output()` +```python +result = threaded_print() +result.await_output() # this will return 1 +``` + +If you have a function that needs to execute on a large list of data, use `run_chunked` +```python +def update_items(items): + ... + +items = [...] +thread6.run_chunked(update_items, items) +``` +`.await_output()` also work with `run_chunked` but will return a list of return values instead + +## Usage + + +## Todo +- [x] threaded function decorator +- [x] run something in a separate thread function +- [x] split data into chunk and run in separate threads +- [ ] add way for errors to fail loudly +- [ ] auto spawn to run fx on a set of data +- [ ] explore multi processing? + + + + +%prep +%autosetup -n thread6-0.2.0 + +%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-thread6 -f filelist.lst +%dir %{python3_sitelib}/* + +%files help -f doclist.lst +%{_docdir}/* + +%changelog +* Tue Apr 11 2023 Python_Bot - 0.2.0-1 +- Package Spec generated -- cgit v1.2.3