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https://github.com/noxdafox/pebble

Multi threading and processing eye-candy.
https://github.com/noxdafox/pebble

asyncio decorators multiprocessing pool python threading

Last synced: 26 days ago
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Multi threading and processing eye-candy.

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Pebble
======

Pebble provides a neat API to manage threads and processes within an application.

:Source: https://github.com/noxdafox/pebble
:Documentation: https://pebble.readthedocs.io
:Download: https://pypi.org/project/Pebble/

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Examples
--------

Run a job in a separate thread and wait for its results.

.. code:: python

from pebble import concurrent

@concurrent.thread
def function(foo, bar=0):
return foo + bar

future = function(1, bar=2)

result = future.result() # blocks until results are ready

Same code with AsyncIO support.

.. code:: python

import asyncio

from pebble import asynchronous

@asynchronous.thread
def function(foo, bar=0):
return foo + bar

async def asynchronous_function():
result = await function(1, bar=2) # blocks until results are ready
print(result)

asyncio.run(asynchronous_function())

Run a function with a timeout of ten seconds and deal with errors.

.. code:: python

from pebble import concurrent
from concurrent.futures import TimeoutError

@concurrent.process(timeout=10)
def function(foo, bar=0):
return foo + bar

future = function(1, bar=2)

try:
result = future.result() # blocks until results are ready
except TimeoutError as error:
print("Function took longer than %d seconds" % error.args[1])
except Exception as error:
print("Function raised %s" % error)
print(error.traceback) # traceback of the function

Pools support workers restart, timeout for long running tasks and more.

.. code:: python

from pebble import ProcessPool
from concurrent.futures import TimeoutError

TIMEOUT_SECONDS = 3

def function(foo, bar=0):
return foo + bar

def task_done(future):
try:
result = future.result() # blocks until results are ready
except TimeoutError as error:
print("Function took longer than %d seconds" % error.args[1])
except Exception as error:
print("Function raised %s" % error)
print(error.traceback) # traceback of the function

with ProcessPool(max_workers=5, max_tasks=10) as pool:
for index in range(0, 10):
future = pool.schedule(function, index, bar=1, timeout=TIMEOUT_SECONDS)
future.add_done_callback(task_done)