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|
%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 <Python_Bot@openeuler.org> - 0.2.0-1
- Package Spec generated
|
