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This library is intended for use with the
concurrent.futures
module. It includes a collection of Executor
implementations in order to
extend the behavior of Future
objects.
concurrent.futures
with asyncio
See the API documentation for detailed information on usage.
This example combines the map and retry executors to create futures for HTTP requests running concurrently, decoding JSON responses within the future and retrying on error.
import requests
from concurrent.futures import as_completed
from more_executors import Executors
def get_json(response):
response.raise_for_status()
return (response.url, response.json())
def fetch_urls(urls):
# Configure an executor:
# - run up to 4 requests concurrently, in separate threads
# - run get_json on each response
# - retry up to several minutes on any errors
executor = Executors.\
thread_pool(max_workers=4).\
with_map(get_json).\
with_retry()
# Submit requests for each given URL
futures = [executor.submit(requests.get, url)
for url in urls]
# Futures API works as normal; we can block on the completed
# futures and map/retry happens implicitly
for future in as_completed(futures):
(url, data) = future.result()
do_something(url, data)
virtualenv
and pip
may be used to locally install this project from
source:
virtualenv ~/dev/python
. ~/dev/python/bin/activate
git clone https://github.com/rohanpm/more-executors
cd more-executors
pip install --editable .
Autotests may be run with pytest:
pip install -r test-requirements.txt
py.test
Submit pull requests against https://github.com/rohanpm/more-executors.
This program is free software: you can redistribute it and/or modify it under the terms of the GNU General Public License as published by the Free Software Foundation, either version 3 of the License, or (at your option) any later version.
FAQs
A library of composable Python executors and futures
We found that more-executors demonstrated a healthy version release cadence and project activity because the last version was released less than a year ago. It has 1 open source maintainer collaborating on the project.
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