Skip to main content

High performance graph data structures and algorithms

Project description

Python interface to the igraph high performance graph library, primarily aimed at complex network research and analysis.

Graph plotting functionality is provided by the Cairo library, so make sure you install the Python bindings of Cairo if you want to generate publication-quality graph plots.

See the Cairo homepage for details.

From release 0.5, the C core of the igraph library is not included in the Python distribution - you must compile and install the C core separately. Windows installers already contain a compiled igraph DLL, so they should work out of the box. Linux users should refer to the igraph homepage for compilation instructions (but check your distribution first, maybe there are pre-compiled packages available). OS X Lion users may benefit from the disk images in the Python Package Index.

Unofficial installers for 64-bit Windows machines and/or different Python versions can also be found here. Many thanks to the maintainers of this page!

Project details


Download files

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

Source Distribution

python-igraph-0.6.tar.gz (342.1 kB view details)

Uploaded Source

Built Distributions

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

python_igraph-0.6-py2.7-macosx10.7.dmg (3.9 MB view details)

Uploaded Source

python_igraph-0.6-py2.6-macosx10.7.dmg (3.9 MB view details)

Uploaded Source

python-igraph-0.6.win32-py3.2.msi (2.0 MB view details)

Uploaded Source

python-igraph-0.6.win32-py2.7.msi (2.0 MB view details)

Uploaded Source

python-igraph-0.6.win32-py2.6.msi (2.0 MB view details)

Uploaded Source

File details

Details for the file python-igraph-0.6.tar.gz.

File metadata

  • Download URL: python-igraph-0.6.tar.gz
  • Upload date:
  • Size: 342.1 kB
  • Tags: Source
  • Uploaded using Trusted Publishing? No

File hashes

Hashes for python-igraph-0.6.tar.gz
Algorithm Hash digest
SHA256 a0835738508f6b5c021bf25bde53b36c5b42df060d68bf4bdb1e30f35b6fc962
MD5 405bf77d0ad6b1522583178e00b3e736
BLAKE2b-256 cc07117004e610cb7bc5c8ea9accef29d34ab53240e450fad3d019ed73e2086f

See more details on using hashes here.

File details

Details for the file python_igraph-0.6-py2.7-macosx10.7.dmg.

File metadata

File hashes

Hashes for python_igraph-0.6-py2.7-macosx10.7.dmg
Algorithm Hash digest
SHA256 dae8695da407ae3248e9f44f65b957033d3d1c20e91e0aef987ff27b962c1a3c
MD5 d659b978af760d8d3dc3d8b57e4b2c8d
BLAKE2b-256 e87cab424830ca4de2d5fbfc30d135f9681f3430755f8dcb4f2e5185cef95445

See more details on using hashes here.

File details

Details for the file python_igraph-0.6-py2.6-macosx10.7.dmg.

File metadata

File hashes

Hashes for python_igraph-0.6-py2.6-macosx10.7.dmg
Algorithm Hash digest
SHA256 6892f45ebc7790d0b1b963caa68deafb8e8a21f621b28c6767f7a9c68cfa4eee
MD5 44f4ff12cd9e58c581bfcbb182b430c6
BLAKE2b-256 4a7a8c436eda329745c40a21492d0faaf668f601cf7200740d3decc9b4542704

See more details on using hashes here.

File details

Details for the file python-igraph-0.6.win32-py3.2.msi.

File metadata

File hashes

Hashes for python-igraph-0.6.win32-py3.2.msi
Algorithm Hash digest
SHA256 7694a4b3e3cc42054792dad77d06edffa0e9b86364c8755abd639da68984f902
MD5 955ac8a0d01f5135aa9fe0e81f41b6a8
BLAKE2b-256 420e772b95d10dfc5f38fe3e5882cfb8d1a7d79c063eda9b279dec349f5d63ca

See more details on using hashes here.

File details

Details for the file python-igraph-0.6.win32-py2.7.msi.

File metadata

File hashes

Hashes for python-igraph-0.6.win32-py2.7.msi
Algorithm Hash digest
SHA256 e816679be6c98d348a064f1fd3ed011d51865a225709daa6f10e17ee9ad16b7b
MD5 f1c6c51e7f4cd531c9ec8de44a638dc1
BLAKE2b-256 fe9b01f8116e8ba193cb66f9eec4c9906c1f87e16555cba80f04fa33f95acd39

See more details on using hashes here.

File details

Details for the file python-igraph-0.6.win32-py2.6.msi.

File metadata

File hashes

Hashes for python-igraph-0.6.win32-py2.6.msi
Algorithm Hash digest
SHA256 4d8d597edd97eae9984398f576f53e0ca7474627ad715104d0d8f035adeb01d3
MD5 84b9921969324d3a1f282c685b73692d
BLAKE2b-256 9fdef026c991b23a3aeac15ed0a1c57b49dfc6de29088c5a53bf651512eaa3cf

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