The CollapsingThreadPoolExecutor is inspired by and compatible with the ThreadPoolExecutor from the "futures" module, it operates differently in that worker threads are handled with a stack which results in the same worker or workers doing all the work (and idle workers being destroyed).
$ pip install collapsing-thread-pool-executor
Prerequisites
- python3 w/ pip
- python2 w/ pip
- virtualenvwrapper
- entr
Set up the environments
$ mkvirtualenv -p `which python2.7` collapsing-thread-pool-executor-py2
$ pip install .
$ pip install -r requirements.txt
$ mkvirtualenv -p `which python3` collapsing-thread-pool-executor-py3
$ pip install .
$ pip install -r requirements.txt
Watch the tests
# watch python2 tests in one window
$ workon collapsing-thread-pool-executor-py2
$ find ./ -name '*.py' | entr -c py.test -v --log-level=DEBUG collapsing_thread_pool_executor
# watch python3 tests in one window
$ workon collapsing-thread-pool-executor-py3
$ find ./ -name '*.py' | entr -c py.test -v --log-level=DEBUG collapsing_thread_pool_executor
The example below will execute some_task() 100 times; as some_task() should take a second to execute and as we've allocated 10 workers, the whole thing should take about 10 seconds.
import time
from collapsing_thread_pool_executor import CollapsingThreadPoolExecutor
def some_task():
time.sleep(1)
# all arguments are optional
pool = CollapsingThreadPoolExecutor(
workers=10,
thread_name_prefix='SomePool',
permitted_thread_age_in_seconds=60,
)
for i in range(0, 100):
pool.submit(some_task)
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