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@@ -0,0 +1 @@ +/atasker-0.7.9.tar.gz diff --git a/python-atasker.spec b/python-atasker.spec new file mode 100644 index 0000000..4db3444 --- /dev/null +++ b/python-atasker.spec @@ -0,0 +1,639 @@ +%global _empty_manifest_terminate_build 0 +Name: python-atasker +Version: 0.7.9 +Release: 1 +Summary: Thread and multiprocessing pooling, task processing via asyncio +License: Apache License 2.0 +URL: https://github.com/alttch/atasker +Source0: https://mirrors.nju.edu.cn/pypi/web/packages/c6/e5/c82778e0774af33a6dd476f03988c6317017f599320805217bce9d2514ec/atasker-0.7.9.tar.gz +BuildArch: noarch + + +%description +# atasker +Python library for modern thread / multiprocessing pooling and task processing +via asyncio. + +<img src="https://img.shields.io/pypi/v/atasker.svg" /> +<img src="https://img.shields.io/badge/license-Apache%202-blue.svg" /> +<img src="https://img.shields.io/badge/python-3.5%20%7C%203.6%20%7C%203.7-blue.svg" /> +<img src="https://img.shields.io/badge/-alpha-red.svg" /> + +Warning: **atasker** is not suitable for the lightweight tasks in high-load +environments. For such projects it's highly recommended to use lightweight +version: [neotasker](https://github.com/alttch/neotasker) + +No matter how your code is written, atasker automatically detects blocking +functions and coroutines and launches them in a proper way, in a thread, +asynchronous loop or in multiprocessing pool. + +Tasks are grouped into pools. If there's no space in pool, task is being placed +into waiting queue according to their priority. Pool also has "reserve" for the +tasks with priorities "normal" and higher. Tasks with "critical" priority are +always executed instantly. + +This library is useful if you have a project with many similar tasks which +produce approximately equal CPU/memory load, e.g. API responses, scheduled +resource state updates etc. + +## Install + +```bash +pip3 install atasker +``` + +Sources: https://github.com/alttch/atasker + +Documentation: https://atasker.readthedocs.io/ + +## Why + +* asynchronous programming is a perfect way to make your code fast and reliable + +* multithreading programming is a perfect way to run blocking code in the + background + +**atasker** combines advantages of both ways: atasker tasks run in separate +threads however task supervisor and workers are completely asynchronous. But +all their public methods are thread-safe. + +## Why not standard Python thread pool? + +* threads in a standard pool don't have priorities +* workers + +## Why not standard asyncio loops? + +* compatibility with blocking functions +* async workers + +## Why not concurrent.futures? + +**concurrent.futures** is a great standard Python library which allows you to +execute specified tasks in a pool of workers. + +For thread-based tasks, **atasker** extends +*concurrent.futures.ThreadPoolExecutor* functionality. + +**atasker** method *background_task* solves the same problem but in slightly +different way, adding priorities to the tasks, while *atasker* workers do +absolutely different job: + +* in *concurrent.futures* worker is a pool member which executes the single + specified task. + +* in *atasker* worker is an object, which continuously *generates* new tasks + with the specified interval or on external event, and executes them in thread + or multiprocessing pool. + + +## Code examples + +### Start/stop + +```python + +from atasker import task_supervisor + +# set pool size +task_supervisor.set_thread_pool(pool_size=20, reserve_normal=5, reserve_high=5) +task_supervisor.start() +# ... +# start workers, other threads etc. +# ... +# optionally block current thread +task_supervisor.block() + +# stop from any thread +task_supervisor.stop() +``` + +### Background task + +```python +from atasker import background_task, TASK_LOW, TASK_HIGH, wait_completed + +# with annotation +@background_task +def mytask(): + print('I am working in the background!') + return 777 + +task = mytask() + +# optional +result = wait_completed(task) + +print(task.result) # 777 +print(result) # 777 + +# with manual decoration +def mytask2(): + print('I am working in the background too!') + +task = background_task(mytask2, priority=TASK_HIGH)() +``` +### Async tasks + +```python +# new asyncio loop is automatically created in own thread +a1 = task_supervisor.create_aloop('myaloop', default=True) + +async def calc(a): + print(a) + await asyncio.sleep(1) + print(a * 2) + return a * 3 + +# call from sync code + +# put coroutine +task = background_task(calc)(1) + +wait_completed(task) + +# run coroutine and wait for result +result = a1.run(calc(1)) +``` + +### Worker examples + +```python +from atasker import background_worker, TASK_HIGH + +@background_worker +def worker1(**kwargs): + print('I am a simple background worker') + +@background_worker +async def worker_async(**kwargs): + print('I am async background worker') + +@background_worker(interval=1) +def worker2(**kwargs): + print('I run every second!') + +@background_worker(queue=True) +def worker3(task, **kwargs): + print('I run when there is a task in my queue') + +@background_worker(event=True, priority=TASK_HIGH) +def worker4(**kwargs): + print('I run when triggered with high priority') + +worker1.start() +worker_async.start() +worker2.start() +worker3.start() +worker4.start() + +worker3.put_threadsafe('todo1') +worker4.trigger_threadsafe() + +from atasker import BackgroundIntervalWorker + +class MyWorker(BackgroundIntervalWorker): + + def run(self, **kwargs): + print('I am custom worker class') + +worker5 = MyWorker(interval=0.1, name='worker5') +worker5.start() +``` + +%package -n python3-atasker +Summary: Thread and multiprocessing pooling, task processing via asyncio +Provides: python-atasker +BuildRequires: python3-devel +BuildRequires: python3-setuptools +BuildRequires: python3-pip +%description -n python3-atasker +# atasker +Python library for modern thread / multiprocessing pooling and task processing +via asyncio. + +<img src="https://img.shields.io/pypi/v/atasker.svg" /> +<img src="https://img.shields.io/badge/license-Apache%202-blue.svg" /> +<img src="https://img.shields.io/badge/python-3.5%20%7C%203.6%20%7C%203.7-blue.svg" /> +<img src="https://img.shields.io/badge/-alpha-red.svg" /> + +Warning: **atasker** is not suitable for the lightweight tasks in high-load +environments. For such projects it's highly recommended to use lightweight +version: [neotasker](https://github.com/alttch/neotasker) + +No matter how your code is written, atasker automatically detects blocking +functions and coroutines and launches them in a proper way, in a thread, +asynchronous loop or in multiprocessing pool. + +Tasks are grouped into pools. If there's no space in pool, task is being placed +into waiting queue according to their priority. Pool also has "reserve" for the +tasks with priorities "normal" and higher. Tasks with "critical" priority are +always executed instantly. + +This library is useful if you have a project with many similar tasks which +produce approximately equal CPU/memory load, e.g. API responses, scheduled +resource state updates etc. + +## Install + +```bash +pip3 install atasker +``` + +Sources: https://github.com/alttch/atasker + +Documentation: https://atasker.readthedocs.io/ + +## Why + +* asynchronous programming is a perfect way to make your code fast and reliable + +* multithreading programming is a perfect way to run blocking code in the + background + +**atasker** combines advantages of both ways: atasker tasks run in separate +threads however task supervisor and workers are completely asynchronous. But +all their public methods are thread-safe. + +## Why not standard Python thread pool? + +* threads in a standard pool don't have priorities +* workers + +## Why not standard asyncio loops? + +* compatibility with blocking functions +* async workers + +## Why not concurrent.futures? + +**concurrent.futures** is a great standard Python library which allows you to +execute specified tasks in a pool of workers. + +For thread-based tasks, **atasker** extends +*concurrent.futures.ThreadPoolExecutor* functionality. + +**atasker** method *background_task* solves the same problem but in slightly +different way, adding priorities to the tasks, while *atasker* workers do +absolutely different job: + +* in *concurrent.futures* worker is a pool member which executes the single + specified task. + +* in *atasker* worker is an object, which continuously *generates* new tasks + with the specified interval or on external event, and executes them in thread + or multiprocessing pool. + + +## Code examples + +### Start/stop + +```python + +from atasker import task_supervisor + +# set pool size +task_supervisor.set_thread_pool(pool_size=20, reserve_normal=5, reserve_high=5) +task_supervisor.start() +# ... +# start workers, other threads etc. +# ... +# optionally block current thread +task_supervisor.block() + +# stop from any thread +task_supervisor.stop() +``` + +### Background task + +```python +from atasker import background_task, TASK_LOW, TASK_HIGH, wait_completed + +# with annotation +@background_task +def mytask(): + print('I am working in the background!') + return 777 + +task = mytask() + +# optional +result = wait_completed(task) + +print(task.result) # 777 +print(result) # 777 + +# with manual decoration +def mytask2(): + print('I am working in the background too!') + +task = background_task(mytask2, priority=TASK_HIGH)() +``` +### Async tasks + +```python +# new asyncio loop is automatically created in own thread +a1 = task_supervisor.create_aloop('myaloop', default=True) + +async def calc(a): + print(a) + await asyncio.sleep(1) + print(a * 2) + return a * 3 + +# call from sync code + +# put coroutine +task = background_task(calc)(1) + +wait_completed(task) + +# run coroutine and wait for result +result = a1.run(calc(1)) +``` + +### Worker examples + +```python +from atasker import background_worker, TASK_HIGH + +@background_worker +def worker1(**kwargs): + print('I am a simple background worker') + +@background_worker +async def worker_async(**kwargs): + print('I am async background worker') + +@background_worker(interval=1) +def worker2(**kwargs): + print('I run every second!') + +@background_worker(queue=True) +def worker3(task, **kwargs): + print('I run when there is a task in my queue') + +@background_worker(event=True, priority=TASK_HIGH) +def worker4(**kwargs): + print('I run when triggered with high priority') + +worker1.start() +worker_async.start() +worker2.start() +worker3.start() +worker4.start() + +worker3.put_threadsafe('todo1') +worker4.trigger_threadsafe() + +from atasker import BackgroundIntervalWorker + +class MyWorker(BackgroundIntervalWorker): + + def run(self, **kwargs): + print('I am custom worker class') + +worker5 = MyWorker(interval=0.1, name='worker5') +worker5.start() +``` + +%package help +Summary: Development documents and examples for atasker +Provides: python3-atasker-doc +%description help +# atasker +Python library for modern thread / multiprocessing pooling and task processing +via asyncio. + +<img src="https://img.shields.io/pypi/v/atasker.svg" /> +<img src="https://img.shields.io/badge/license-Apache%202-blue.svg" /> +<img src="https://img.shields.io/badge/python-3.5%20%7C%203.6%20%7C%203.7-blue.svg" /> +<img src="https://img.shields.io/badge/-alpha-red.svg" /> + +Warning: **atasker** is not suitable for the lightweight tasks in high-load +environments. For such projects it's highly recommended to use lightweight +version: [neotasker](https://github.com/alttch/neotasker) + +No matter how your code is written, atasker automatically detects blocking +functions and coroutines and launches them in a proper way, in a thread, +asynchronous loop or in multiprocessing pool. + +Tasks are grouped into pools. If there's no space in pool, task is being placed +into waiting queue according to their priority. Pool also has "reserve" for the +tasks with priorities "normal" and higher. Tasks with "critical" priority are +always executed instantly. + +This library is useful if you have a project with many similar tasks which +produce approximately equal CPU/memory load, e.g. API responses, scheduled +resource state updates etc. + +## Install + +```bash +pip3 install atasker +``` + +Sources: https://github.com/alttch/atasker + +Documentation: https://atasker.readthedocs.io/ + +## Why + +* asynchronous programming is a perfect way to make your code fast and reliable + +* multithreading programming is a perfect way to run blocking code in the + background + +**atasker** combines advantages of both ways: atasker tasks run in separate +threads however task supervisor and workers are completely asynchronous. But +all their public methods are thread-safe. + +## Why not standard Python thread pool? + +* threads in a standard pool don't have priorities +* workers + +## Why not standard asyncio loops? + +* compatibility with blocking functions +* async workers + +## Why not concurrent.futures? + +**concurrent.futures** is a great standard Python library which allows you to +execute specified tasks in a pool of workers. + +For thread-based tasks, **atasker** extends +*concurrent.futures.ThreadPoolExecutor* functionality. + +**atasker** method *background_task* solves the same problem but in slightly +different way, adding priorities to the tasks, while *atasker* workers do +absolutely different job: + +* in *concurrent.futures* worker is a pool member which executes the single + specified task. + +* in *atasker* worker is an object, which continuously *generates* new tasks + with the specified interval or on external event, and executes them in thread + or multiprocessing pool. + + +## Code examples + +### Start/stop + +```python + +from atasker import task_supervisor + +# set pool size +task_supervisor.set_thread_pool(pool_size=20, reserve_normal=5, reserve_high=5) +task_supervisor.start() +# ... +# start workers, other threads etc. +# ... +# optionally block current thread +task_supervisor.block() + +# stop from any thread +task_supervisor.stop() +``` + +### Background task + +```python +from atasker import background_task, TASK_LOW, TASK_HIGH, wait_completed + +# with annotation +@background_task +def mytask(): + print('I am working in the background!') + return 777 + +task = mytask() + +# optional +result = wait_completed(task) + +print(task.result) # 777 +print(result) # 777 + +# with manual decoration +def mytask2(): + print('I am working in the background too!') + +task = background_task(mytask2, priority=TASK_HIGH)() +``` +### Async tasks + +```python +# new asyncio loop is automatically created in own thread +a1 = task_supervisor.create_aloop('myaloop', default=True) + +async def calc(a): + print(a) + await asyncio.sleep(1) + print(a * 2) + return a * 3 + +# call from sync code + +# put coroutine +task = background_task(calc)(1) + +wait_completed(task) + +# run coroutine and wait for result +result = a1.run(calc(1)) +``` + +### Worker examples + +```python +from atasker import background_worker, TASK_HIGH + +@background_worker +def worker1(**kwargs): + print('I am a simple background worker') + +@background_worker +async def worker_async(**kwargs): + print('I am async background worker') + +@background_worker(interval=1) +def worker2(**kwargs): + print('I run every second!') + +@background_worker(queue=True) +def worker3(task, **kwargs): + print('I run when there is a task in my queue') + +@background_worker(event=True, priority=TASK_HIGH) +def worker4(**kwargs): + print('I run when triggered with high priority') + +worker1.start() +worker_async.start() +worker2.start() +worker3.start() +worker4.start() + +worker3.put_threadsafe('todo1') +worker4.trigger_threadsafe() + +from atasker import BackgroundIntervalWorker + +class MyWorker(BackgroundIntervalWorker): + + def run(self, **kwargs): + print('I am custom worker class') + +worker5 = MyWorker(interval=0.1, name='worker5') +worker5.start() +``` + +%prep +%autosetup -n atasker-0.7.9 + +%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-atasker -f filelist.lst +%dir %{python3_sitelib}/* + +%files help -f doclist.lst +%{_docdir}/* + +%changelog +* Mon May 15 2023 Python_Bot <Python_Bot@openeuler.org> - 0.7.9-1 +- Package Spec generated @@ -0,0 +1 @@ +f340e89a189487eb3df27e6d2678a720 atasker-0.7.9.tar.gz |