Skip to main content

Coroutine-based network library

Project description

gevent is a coroutine-based Python networking library.

Features include:

  • Fast event loop based on libev or libuv.

  • Lightweight execution units based on greenlet.

  • Familiar API that re-uses concepts from the Python standard library.

  • Cooperative sockets with SSL support.

  • DNS queries performed through c-ares or a threadpool.

  • Ability to use standard library and 3rd party modules written for standard blocking sockets

gevent is inspired by eventlet but features more consistent API, simpler implementation and better performance. Read why others use gevent and check out the list of the open source projects based on gevent.

gevent was written by Denis Bilenko.

Since version 1.1, gevent is maintained by NextThought with help from the contributors and is licensed under the MIT license.

See what’s new in the latest major release.

Check out the detailed changelog for this version.

Get gevent

gevent runs on Python >= 2.7, Python >= 3.4, or PyPy >= 5.5 (including PyPy2 and PyPy3). On all platforms, installing setuptools is required (this is done automatically if working in a virtual environment).

You can use pip to install gevent:

pip install gevent

Download the latest release from Python Package Index or clone the repository.

Read the documentation online at http://www.gevent.org. Additional installation information can be found here.

Post feedback and issues on the bug tracker, mailing list, blog and twitter (@gevent).

Development

To install the latest development version:

pip install setuptools cffi 'cython>=0.27' git+git://github.com/gevent/gevent.git#egg=gevent

To hack on gevent (using a virtualenv):

$ git clone https://github.com/gevent/gevent.git
$ cd gevent
$ virtualenv env
$ source env/bin/activate
(env) $ pip install -r dev-requirements.txt

Running Tests

There are a few different ways to run the tests. To simply run the tests on one version of Python during development, try this:

(env) $ pip install -e .
(env) $ cd src/greentest
(env) $ python ./testrunner.py

Before submitting a pull request, it’s a good idea to run the tests across all supported versions of Python, and to check the code quality using prospector. This is what is done on Travis CI. Locally it can be done using tox:

pip install tox
tox

The testrunner accepts a --coverage argument to enable code coverage metrics through the coverage.py package. That would go something like this:

cd src/greentest
python testrunner.py --coverage
coverage combine
coverage html -i
<open htmlcov/index.html>

Builds on Travis CI automatically submit updates to coveralls.io to monitor test coverage.

https://coveralls.io/repos/gevent/gevent/badge.svg?branch=master&service=github

Continuous integration

A test suite is run for every push and pull request submitted. Travis CI is used to test on Linux, and AppVeyor runs the builds on Windows.

https://travis-ci.org/gevent/gevent.svg?branch=master https://ci.appveyor.com/api/projects/status/q4kl21ng2yo2ixur?svg=true

Project details


Release history Release notifications | RSS feed

Download files

Download the file for your platform. If you're not sure which to choose, learn more about installing packages.

Source Distribution

gevent-1.3b1.tar.gz (4.5 MB view details)

Uploaded Source

Built Distributions

If you're not sure about the file name format, learn more about wheel file names.

gevent-1.3b1-pp259-pypy_41-win32.whl (656.4 kB view details)

Uploaded PyPyWindows x86

gevent-1.3b1-cp37-cp37m-macosx_10_9_x86_64.whl (2.1 MB view details)

Uploaded CPython 3.7mmacOS 10.9+ x86-64

gevent-1.3b1-cp36-cp36m-win_amd64.whl (2.0 MB view details)

Uploaded CPython 3.6mWindows x86-64

gevent-1.3b1-cp36-cp36m-win32.whl (1.8 MB view details)

Uploaded CPython 3.6mWindows x86

gevent-1.3b1-cp36-cp36m-manylinux1_x86_64.whl (4.3 MB view details)

Uploaded CPython 3.6m

gevent-1.3b1-cp36-cp36m-macosx_10_6_intel.whl (3.0 MB view details)

Uploaded CPython 3.6mmacOS 10.6+ Intel (x86-64, i386)

gevent-1.3b1-cp35-cp35m-win_amd64.whl (2.0 MB view details)

Uploaded CPython 3.5mWindows x86-64

gevent-1.3b1-cp35-cp35m-win32.whl (1.8 MB view details)

Uploaded CPython 3.5mWindows x86

gevent-1.3b1-cp35-cp35m-manylinux1_x86_64.whl (4.2 MB view details)

Uploaded CPython 3.5m

gevent-1.3b1-cp35-cp35m-macosx_10_6_intel.whl (3.0 MB view details)

Uploaded CPython 3.5mmacOS 10.6+ Intel (x86-64, i386)

gevent-1.3b1-cp34-cp34m-win_amd64.whl (2.0 MB view details)

Uploaded CPython 3.4mWindows x86-64

gevent-1.3b1-cp34-cp34m-win32.whl (1.9 MB view details)

Uploaded CPython 3.4mWindows x86

gevent-1.3b1-cp34-cp34m-manylinux1_x86_64.whl (4.3 MB view details)

Uploaded CPython 3.4m

gevent-1.3b1-cp34-cp34m-macosx_10_6_intel.whl (3.0 MB view details)

Uploaded CPython 3.4mmacOS 10.6+ Intel (x86-64, i386)

gevent-1.3b1-cp27-cp27mu-manylinux1_x86_64.whl (4.0 MB view details)

Uploaded CPython 2.7mu

gevent-1.3b1-cp27-cp27m-win_amd64.whl (2.0 MB view details)

Uploaded CPython 2.7mWindows x86-64

gevent-1.3b1-cp27-cp27m-win32.whl (1.9 MB view details)

Uploaded CPython 2.7mWindows x86

gevent-1.3b1-cp27-cp27m-manylinux1_x86_64.whl (4.0 MB view details)

Uploaded CPython 2.7m

gevent-1.3b1-cp27-cp27m-macosx_10_6_intel.whl (3.0 MB view details)

Uploaded CPython 2.7mmacOS 10.6+ Intel (x86-64, i386)

File details

Details for the file gevent-1.3b1.tar.gz.

File metadata

  • Download URL: gevent-1.3b1.tar.gz
  • Upload date:
  • Size: 4.5 MB
  • Tags: Source
  • Uploaded using Trusted Publishing? No

File hashes

Hashes for gevent-1.3b1.tar.gz
Algorithm Hash digest
SHA256 e2808a40a5747c13e634edbdd42032dfe5f930a39eddd6f235703886cdf486bc
MD5 3b009d082500150007514567a241276c
BLAKE2b-256 6acedfa807a393fbb2b19f2dbb88558de94a7bf13236254136ead762a1e14fc1

See more details on using hashes here.

File details

Details for the file gevent-1.3b1-pp259-pypy_41-win32.whl.

File metadata

File hashes

Hashes for gevent-1.3b1-pp259-pypy_41-win32.whl
Algorithm Hash digest
SHA256 66574654c43c655beed59825b00e3a5c006c4d9a0b767e3a34ba256246e7df9d
MD5 46f261ffab550f045594dd37d863f700
BLAKE2b-256 2a0cd57bfcf4675b59b1f673f6533170e40f88b44d65c1bfbb2c439ef9af4448

See more details on using hashes here.

File details

Details for the file gevent-1.3b1-cp37-cp37m-macosx_10_9_x86_64.whl.

File metadata

File hashes

Hashes for gevent-1.3b1-cp37-cp37m-macosx_10_9_x86_64.whl
Algorithm Hash digest
SHA256 ebeb962bd19c4297067e50c8786115900022564b90a91a13adc77296c6698df3
MD5 6fbe84858f95718ed10b6b3fe876176e
BLAKE2b-256 df0f41e53c47c10531b87261e9e03475132418ca2ec96eff56a15b7e124a433a

See more details on using hashes here.

File details

Details for the file gevent-1.3b1-cp36-cp36m-win_amd64.whl.

File metadata

File hashes

Hashes for gevent-1.3b1-cp36-cp36m-win_amd64.whl
Algorithm Hash digest
SHA256 0141b44a1eea5c3d2dec9e75da3bf0a51153bc6f9ef6e631a1e18460541d2ac1
MD5 026afc2061b363d11e506856420dffc3
BLAKE2b-256 bb5065f6bf44ceda7fb9e01512f2d3c8f5bc785b55ed0bbe6e39fa3a1a66012f

See more details on using hashes here.

File details

Details for the file gevent-1.3b1-cp36-cp36m-win32.whl.

File metadata

File hashes

Hashes for gevent-1.3b1-cp36-cp36m-win32.whl
Algorithm Hash digest
SHA256 135c4cac0e3b35ba2497acb38ed739606cb2ca1acbec4c052fb4b7f527abfbfb
MD5 8aebba08d8927314a7ded88115882ae2
BLAKE2b-256 affd381b2e1a8419cd3a1b720b3c680f2b87e4695043c5f61fc0721232db4a47

See more details on using hashes here.

File details

Details for the file gevent-1.3b1-cp36-cp36m-manylinux1_x86_64.whl.

File metadata

File hashes

Hashes for gevent-1.3b1-cp36-cp36m-manylinux1_x86_64.whl
Algorithm Hash digest
SHA256 b3f41829ff9c2d2fde2c71a646b53b9c7f2b62908ee3601ad2d17eaa6c8b89b9
MD5 617c806a42890898c26276c7a676fa6d
BLAKE2b-256 b1c75cd56248e327bb6bd32a492e4dd65e58d6ee579259f48373eff3e04cb27b

See more details on using hashes here.

File details

Details for the file gevent-1.3b1-cp36-cp36m-macosx_10_6_intel.whl.

File metadata

File hashes

Hashes for gevent-1.3b1-cp36-cp36m-macosx_10_6_intel.whl
Algorithm Hash digest
SHA256 967c8df8192ab388e985e964f7c7608dc4a967c081c7b042228c56aeac276e78
MD5 f5fb46aa1a165b2cb58c8c0bddfc3518
BLAKE2b-256 38a7b43a77a78dea16e4e68570c8df9d6884610fff1865324eaad166d6908fe6

See more details on using hashes here.

File details

Details for the file gevent-1.3b1-cp35-cp35m-win_amd64.whl.

File metadata

File hashes

Hashes for gevent-1.3b1-cp35-cp35m-win_amd64.whl
Algorithm Hash digest
SHA256 f2e3f638e6bbede7295447c6ed8864ae151c45e85875996299996f4136d231df
MD5 7a8b5c60358c83551a26175885209ff8
BLAKE2b-256 e49042364d43de704bb55397355ade3d98c76a8afd361753fef9c73e3d334220

See more details on using hashes here.

File details

Details for the file gevent-1.3b1-cp35-cp35m-win32.whl.

File metadata

File hashes

Hashes for gevent-1.3b1-cp35-cp35m-win32.whl
Algorithm Hash digest
SHA256 83127cd5bab985ad35f7523af32d32ce8f437834a30938b1f5a5b3ff76268eef
MD5 3f0829da266de9d14a7f853ae63a7f27
BLAKE2b-256 1d282e72ffa227375407ee29246c5955360294b0edeaeae2cd6208c0c084a18c

See more details on using hashes here.

File details

Details for the file gevent-1.3b1-cp35-cp35m-manylinux1_x86_64.whl.

File metadata

File hashes

Hashes for gevent-1.3b1-cp35-cp35m-manylinux1_x86_64.whl
Algorithm Hash digest
SHA256 42816718f9039c54f32a8bffe333a63e6e1cc9c673151dd07390b7e7d874bcf4
MD5 f4b678a1f3c50e31a85e6ac0bde87e4e
BLAKE2b-256 02809a2555a94a5767808b64faf54c9f93899faeba61461c1053eb84f8a49597

See more details on using hashes here.

File details

Details for the file gevent-1.3b1-cp35-cp35m-macosx_10_6_intel.whl.

File metadata

File hashes

Hashes for gevent-1.3b1-cp35-cp35m-macosx_10_6_intel.whl
Algorithm Hash digest
SHA256 dbbe5285ce4d788b8b4643a7ee74544999537661b882b269a3a7bc1cff24b695
MD5 a1bdfcdea8ce83bff1c5121b4bc1813e
BLAKE2b-256 7bb575e1d597bee2cdd889583550db60a3fa7a66e24c6682b0fe51c06f2676a1

See more details on using hashes here.

File details

Details for the file gevent-1.3b1-cp34-cp34m-win_amd64.whl.

File metadata

File hashes

Hashes for gevent-1.3b1-cp34-cp34m-win_amd64.whl
Algorithm Hash digest
SHA256 a140b720c0836e6121092f34649c750e7cff7fdda6b9169b001cac581246612a
MD5 7dc62b1eeac5063347fd2d253f9d6479
BLAKE2b-256 05db0623fe1a940a97a50de53e6ed224db4846a7d04b309ac89fd1e741cb3c45

See more details on using hashes here.

File details

Details for the file gevent-1.3b1-cp34-cp34m-win32.whl.

File metadata

File hashes

Hashes for gevent-1.3b1-cp34-cp34m-win32.whl
Algorithm Hash digest
SHA256 26878e0432cab7cdd85ed08caa0c277d38164a067ea2586c210a49948db9df28
MD5 f8f81504420d4ae527db9a6013eca8d9
BLAKE2b-256 7ed4a1f1273f8f03173d60866939b876d08bb2aaf229b3bc4f8cf37a032b3bf5

See more details on using hashes here.

File details

Details for the file gevent-1.3b1-cp34-cp34m-manylinux1_x86_64.whl.

File metadata

File hashes

Hashes for gevent-1.3b1-cp34-cp34m-manylinux1_x86_64.whl
Algorithm Hash digest
SHA256 1b75ddcdadce3174d8b0a5ea3f46af36274fe0275a47a73ee3e5be94c0471be5
MD5 2f56f338b40b3e9b0813d5f104a3dc91
BLAKE2b-256 e8ddd40d5156831422b4fc434a06c3a725c541c4dc8084e0840b44e878b6b2ed

See more details on using hashes here.

File details

Details for the file gevent-1.3b1-cp34-cp34m-macosx_10_6_intel.whl.

File metadata

File hashes

Hashes for gevent-1.3b1-cp34-cp34m-macosx_10_6_intel.whl
Algorithm Hash digest
SHA256 c541e1d4f738c9760335a988b47527b0e816d62ce88eb09a61382e551b96dea5
MD5 ba7564976da2e42ee0ecef89a423286f
BLAKE2b-256 1189cc0677f6bd9a1668c5e9e6f9e20a0e70f9a2168d1120261111d98bad8050

See more details on using hashes here.

File details

Details for the file gevent-1.3b1-cp27-cp27mu-manylinux1_x86_64.whl.

File metadata

File hashes

Hashes for gevent-1.3b1-cp27-cp27mu-manylinux1_x86_64.whl
Algorithm Hash digest
SHA256 6217c69fbac737d62b67bb07434a61a437373f4211f594ade9210f5a2d053607
MD5 3d2f5521bf847efbb6b0e1ca2da16fa9
BLAKE2b-256 cddc800621bafa44c339a45fca57ff0c7d9a816f8c4263440268f5aed9d576e8

See more details on using hashes here.

File details

Details for the file gevent-1.3b1-cp27-cp27m-win_amd64.whl.

File metadata

File hashes

Hashes for gevent-1.3b1-cp27-cp27m-win_amd64.whl
Algorithm Hash digest
SHA256 2b2be6b0991c17826f4f7a6ee0be3a62ae2825c92158d9a8ae567b399452a579
MD5 f48cf69ed9642bb71b00dcecca686ef5
BLAKE2b-256 42b34c67a3e160b895accac883d18f7c48df4a4fab4daa426b038bf6be75e097

See more details on using hashes here.

File details

Details for the file gevent-1.3b1-cp27-cp27m-win32.whl.

File metadata

File hashes

Hashes for gevent-1.3b1-cp27-cp27m-win32.whl
Algorithm Hash digest
SHA256 e39617b8ae37b840e5b6c149ed5ce26cd5d0d2b348dd4410b1f584d7eac4b333
MD5 13d6b5ce07cca8c95297c9ec0b2a5ca8
BLAKE2b-256 c857f2b6a8728c1825606226237940e0ed03ecb524b2fe23dcbc8bdf8a93f8a2

See more details on using hashes here.

File details

Details for the file gevent-1.3b1-cp27-cp27m-manylinux1_x86_64.whl.

File metadata

File hashes

Hashes for gevent-1.3b1-cp27-cp27m-manylinux1_x86_64.whl
Algorithm Hash digest
SHA256 11108689372672000cf5393451cde5b4583b8394a747c1faf56ea5afcca687ef
MD5 e9bb09b036926395b7d1f4270c2204ed
BLAKE2b-256 4783d482f3b41c4f5beae9f673547b2b45f3eac8b98e4a927151998f6fb3641d

See more details on using hashes here.

File details

Details for the file gevent-1.3b1-cp27-cp27m-macosx_10_6_intel.whl.

File metadata

File hashes

Hashes for gevent-1.3b1-cp27-cp27m-macosx_10_6_intel.whl
Algorithm Hash digest
SHA256 86b6cf0a5f9d88ff85c6e9c595e5fdc8cb38249efe660cf6fbe0eeb50df241e9
MD5 e4827a8e8a512bdf725b9ec50c0c8040
BLAKE2b-256 a69a9011e7c81ed99a428159a23907b22b8c7d7d58ebdf604757d8824ef25234

See more details on using hashes here.

Supported by

AWS Cloud computing and Security Sponsor Datadog Monitoring Depot Continuous Integration Fastly CDN Google Download Analytics Pingdom Monitoring Sentry Error logging StatusPage Status page