Decorators for running functions in Thread/ThreadPool/IOLoop
Project description
threaded
threaded is a set of decorators, which wrap functions in:
concurrent.futures.ThreadPool
threading.Thread
asyncio.Task in Python 3.
gevent.threadpool.ThreadPool if gevent is installed.
Why? Because copy-paste of loop.create_task, threading.Thread and thread_pool.submit is boring, especially if target functions is used by this way only.
Pros:
Free software: Apache license
Open Source: https://github.com/penguinolog/threaded
PyPI packaged: https://pypi-hypernode.com/pypi/threaded
Tested: see bages on top
Support multiple Python versions:
Python 2.7 Python 3.4 Python 3.5 Python 3.6 PyPy PyPy3 3.5+ Jyton 2.7
Decorators:
ThreadPooled - native concurrent.futures.ThreadPool usage on Python 3 and it’s backport on Python 2.7.
threadpooled is alias for ThreadPooled.
Threaded - wrap in threading.Thread.
threaded is alias for Threaded.
AsyncIOTask - wrap in asyncio.Task. Uses the same API, as Python 3 ThreadPooled.
asynciotask is alias for AsyncIOTask.
GThreadPooled - wrap function in gevent.threadpool.ThreadPool.
gthreadpooled is alias for GThreadPooled.
Usage
ThreadPooled
Mostly it is required decorator: submit function to ThreadPoolExecutor on call.
threaded.ThreadPooled.configure(max_workers=3)Python 2.7 usage:
@threaded.ThreadPooled
def func():
pass
concurrent.futures.wait([func()])Python 3.3+ usage:
@threaded.ThreadPooled
def func():
pass
concurrent.futures.wait([func()])Python 3.3+ usage with asyncio:
loop = asyncio.get_event_loop()
@threaded.ThreadPooled(loop_getter=loop, loop_getter_need_context=False)
def func():
pass
loop.run_until_complete(asyncio.wait_for(func(), timeout))Python 3.3+ usage with asyncio and loop extraction from call arguments:
loop_getter = lambda tgt_loop: tgt_loop
@threaded.ThreadPooled(loop_getter=loop_getter, loop_getter_need_context=True) # loop_getter_need_context is required
def func(*args, **kwargs):
pass
loop = asyncio.get_event_loop()
loop.run_until_complete(asyncio.wait_for(func(loop), timeout))During application shutdown, pool can be stopped (while it will be recreated automatically, if some component will request).
threaded.ThreadPooled.shutdown()Threaded
Classic threading.Thread. Useful for running until close and self-closing threads without return.
Usage example:
@threaded.Threaded
def func(*args, **kwargs):
pass
thread = func()
thread.start()
thread.join()Without arguments, thread name will use pattern: 'Threaded: ' + func.__name__
Override name can be don via corresponding argument:
@threaded.Threaded(name='Function in thread')
def func(*args, **kwargs):
passThread can be daemonized automatically:
@threaded.Threaded(daemon=True)
def func(*args, **kwargs):
passAlso, if no any addition manipulations expected before thread start, it can be started automatically before return:
@threaded.Threaded(started=True)
def func(*args, **kwargs):
passAsyncIOTask
Wrap in asyncio.Task.
usage with asyncio:
@threaded.AsyncIOTask
def func():
pass
loop = asyncio.get_event_loop()
loop.run_until_complete(asyncio.wait_for(func(), timeout))Provide event loop directly:
loop = asyncio.get_event_loop()
@threaded.AsyncIOTask(loop_getter=loop)
def func():
pass
loop.run_until_complete(asyncio.wait_for(func(), timeout))Usage with loop extraction from call arguments:
loop_getter = lambda tgt_loop: tgt_loop
@threaded.AsyncIOTask(loop_getter=loop_getter, loop_getter_need_context=True)
def func(*args, **kwargs):
pass
loop = asyncio.get_event_loop()
loop.run_until_complete(asyncio.wait_for(func(loop), timeout))GThreadPooled
Post function to gevent.threadpool.ThreadPool.
threaded.GThreadPooled.configure(max_workers=3)Basic usage example:
@threaded.GThreadPooled
def func():
pass
func().wait()Testing
The main test mechanism for the package threaded is using tox. Test environments available:
pep8 py27 py34 py35 py36 pypy pypy3 pylint
CI systems
For code checking several CI systems is used in parallel:
Travis CI: is used for checking: PEP8, pylint, bandit, installation possibility and unit tests. Also it’s publishes coverage on coveralls.
coveralls: is used for coverage display.
CD system
Travis CI: is used for package delivery on PyPI.
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