python-igraph

High performance graph data structures and algorithms

These details have not been verified by PyPI

Project links

Homepage

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. You can try either pycairo or cairocffi, cairocffi is recommended, in particular if you are on Python 3.x because there were bug reports affecting igraph graph plots in Jupyter notebooks when using pycairo (but not with cairocffi).

Project details

These details have not been verified by PyPI

Project links

Homepage

Release history Release notifications | RSS feed

0.11.8

Oct 28, 2024

0.11.6

Jul 8, 2024

0.11.5

May 7, 2024

0.11.4

Feb 14, 2024

0.11.3

Nov 20, 2023

0.11.2

Oct 12, 2023

0.10.8

Sep 12, 2023

0.10.6

Jul 19, 2023

0.10.5

Jul 1, 2023

0.10.4

Jan 28, 2023

0.10.3

Jan 1, 2023

0.10.2

Oct 17, 2022

0.10.1

Sep 13, 2022

0.10.0

Sep 6, 2022

0.9.11

Jun 8, 2022

0.9.10

Apr 11, 2022

0.9.9

Jan 10, 2022

0.9.8

Oct 29, 2021

0.9.7

Oct 15, 2021

0.9.6

Jun 12, 2021

0.9.5

Jun 11, 2021

0.9.4

May 31, 2021

This version

0.9.1

Mar 26, 2021

0.9.0

Feb 26, 2021

0.8.3

Oct 8, 2020

0.8.2

Apr 28, 2020

0.8.1

Apr 27, 2020

0.8.0

Feb 8, 2020

0.7.1.post6

Jun 5, 2015

0.7.1.post5

Jun 5, 2015

0.7.1-4

Mar 5, 2015

0.7.1-3

Mar 5, 2015

0.7.1-2

Feb 10, 2015

0.7.1-1

Feb 9, 2015

0.7.1

Feb 9, 2015

0.7

Mar 10, 2014

0.6.5

Feb 28, 2013

0.6

Jun 17, 2012

0.5.4

Sep 15, 2010

0.5.3

Jan 15, 2010

0.5.2

Apr 27, 2009

0.5.1

Aug 16, 2008

0.5

Feb 15, 2008

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-0.9.1.tar.gz (3.6 MB view details)

Uploaded Mar 26, 2021 Source

Built Distributions

python_igraph-0.9.1-pp37-pypy37_pp73-win32.whl (2.1 MB view details)

Uploaded Mar 26, 2021 PyPy Windows x86

python_igraph-0.9.1-pp37-pypy37_pp73-manylinux2010_x86_64.whl (2.8 MB view details)

Uploaded Mar 26, 2021 PyPy manylinux: glibc 2.12+ x86-64

python_igraph-0.9.1-pp37-pypy37_pp73-macosx_10_9_x86_64.whl (1.9 MB view details)

Uploaded Mar 26, 2021 PyPy macOS 10.9+ x86-64

python_igraph-0.9.1-pp36-pypy36_pp73-win32.whl (2.1 MB view details)

Uploaded Mar 26, 2021 PyPy Windows x86

python_igraph-0.9.1-pp36-pypy36_pp73-manylinux2010_x86_64.whl (2.8 MB view details)

Uploaded Mar 26, 2021 PyPy manylinux: glibc 2.12+ x86-64

python_igraph-0.9.1-pp36-pypy36_pp73-macosx_10_9_x86_64.whl (1.9 MB view details)

Uploaded Mar 26, 2021 PyPy macOS 10.9+ x86-64

python_igraph-0.9.1-cp39-cp39-win_amd64.whl (2.3 MB view details)

Uploaded Mar 26, 2021 CPython 3.9 Windows x86-64

python_igraph-0.9.1-cp39-cp39-win32.whl (2.1 MB view details)

Uploaded Mar 26, 2021 CPython 3.9 Windows x86

python_igraph-0.9.1-cp39-cp39-manylinux2010_x86_64.whl (3.2 MB view details)

Uploaded Mar 26, 2021 CPython 3.9 manylinux: glibc 2.12+ x86-64

python_igraph-0.9.1-cp39-cp39-manylinux2010_i686.whl (3.1 MB view details)

Uploaded Mar 26, 2021 CPython 3.9 manylinux: glibc 2.12+ i686

python_igraph-0.9.1-cp39-cp39-macosx_10_9_x86_64.whl (2.0 MB view details)

Uploaded Mar 26, 2021 CPython 3.9 macOS 10.9+ x86-64

python_igraph-0.9.1-cp38-cp38-win_amd64.whl (2.3 MB view details)

Uploaded Mar 26, 2021 CPython 3.8 Windows x86-64

python_igraph-0.9.1-cp38-cp38-win32.whl (2.1 MB view details)

Uploaded Mar 26, 2021 CPython 3.8 Windows x86

python_igraph-0.9.1-cp38-cp38-manylinux2010_x86_64.whl (3.2 MB view details)

Uploaded Mar 26, 2021 CPython 3.8 manylinux: glibc 2.12+ x86-64

python_igraph-0.9.1-cp38-cp38-manylinux2010_i686.whl (3.1 MB view details)

Uploaded Mar 26, 2021 CPython 3.8 manylinux: glibc 2.12+ i686

python_igraph-0.9.1-cp38-cp38-macosx_10_9_x86_64.whl (2.0 MB view details)

Uploaded Mar 26, 2021 CPython 3.8 macOS 10.9+ x86-64

python_igraph-0.9.1-cp37-cp37m-win_amd64.whl (2.3 MB view details)

Uploaded Mar 26, 2021 CPython 3.7m Windows x86-64

python_igraph-0.9.1-cp37-cp37m-win32.whl (2.1 MB view details)

Uploaded Mar 26, 2021 CPython 3.7m Windows x86

python_igraph-0.9.1-cp37-cp37m-manylinux2010_x86_64.whl (3.2 MB view details)

Uploaded Mar 26, 2021 CPython 3.7m manylinux: glibc 2.12+ x86-64

python_igraph-0.9.1-cp37-cp37m-manylinux2010_i686.whl (3.1 MB view details)

Uploaded Mar 26, 2021 CPython 3.7m manylinux: glibc 2.12+ i686

python_igraph-0.9.1-cp37-cp37m-macosx_10_9_x86_64.whl (2.0 MB view details)

Uploaded Mar 26, 2021 CPython 3.7m macOS 10.9+ x86-64

python_igraph-0.9.1-cp36-cp36m-win_amd64.whl (2.3 MB view details)

Uploaded Mar 26, 2021 CPython 3.6m Windows x86-64

python_igraph-0.9.1-cp36-cp36m-win32.whl (2.1 MB view details)

Uploaded Mar 26, 2021 CPython 3.6m Windows x86

python_igraph-0.9.1-cp36-cp36m-manylinux2010_x86_64.whl (3.1 MB view details)

Uploaded Mar 26, 2021 CPython 3.6m manylinux: glibc 2.12+ x86-64

python_igraph-0.9.1-cp36-cp36m-manylinux2010_i686.whl (3.1 MB view details)

Uploaded Mar 26, 2021 CPython 3.6m manylinux: glibc 2.12+ i686

python_igraph-0.9.1-cp36-cp36m-macosx_10_9_x86_64.whl (2.0 MB view details)

Uploaded Mar 26, 2021 CPython 3.6m macOS 10.9+ x86-64

File details

Details for the file python-igraph-0.9.1.tar.gz.

File metadata

Download URL: python-igraph-0.9.1.tar.gz
Upload date: Mar 26, 2021
Size: 3.6 MB
Tags: Source
Uploaded using Trusted Publishing? No
Uploaded via: twine/3.4.1 importlib_metadata/3.7.3 pkginfo/1.7.0 requests/2.25.1 requests-toolbelt/0.9.1 tqdm/4.59.0 CPython/3.9.2

File hashes

Hashes for python-igraph-0.9.1.tar.gz
Algorithm	Hash digest
SHA256	`f1895a83c57180f03c50fb77334a4d5029327aefee14f03381e10d34a1794410`
MD5	`882930dda7a15fa1e31a36fcdbef1a74`
BLAKE2b-256	`8e6ad6d06a487a3998c458d138eb3e7ab29a72d8e3383863ee9117e4a980c36d`

Algorithm	Hash digest
SHA256	`391c94f3630b07f7de3a9381a31a96b244944c8a804a39e7946fa45876bc5a15`
MD5	`2db9e6c657e7508ec7f94f695f6a49f1`
BLAKE2b-256	`a1f32efc1b4317a9f4ccb7d494cfb92e8bd3332869fb002e832b1b09cfc6d1d0`

Algorithm	Hash digest
SHA256	`64f9745278c412ef131cd5ea174ff67f9473fe7666bcb1e0b4fc7f1b21c3e224`
MD5	`86c864d799bf2f3297382ab968167dda`
BLAKE2b-256	`2c726c1263ec0633c8ca3d62fcc9f352bda8984c1980eb876cfb03a2671798e8`

Algorithm	Hash digest
SHA256	`0f4351522b9716795dc3affbb5aef2ffbcadf20b63da5a310161e55675754752`
MD5	`9351ac5d77946a1b5af0ae4bcc183a43`
BLAKE2b-256	`b71fc345d30d75d05a47e205ca5f4d362f1c940e06243941d4fb23f9eee897cd`

Algorithm	Hash digest
SHA256	`c2cb544ae4655b28e99a2d293f0cd3de901e971e0fe748c062aeb651d6eb44f3`
MD5	`e6646b2b93c5546a1e2bb6de1b8bdda7`
BLAKE2b-256	`ded87541416746db50a66f9cefb66fd8a92f23ac36124c8b3868269a9ef601c6`

Algorithm	Hash digest
SHA256	`4195d8ada8e625ed692a47610fca2a4b89109f2e257883950d980fa082220745`
MD5	`9ead92af69ef58a4047707addaeda493`
BLAKE2b-256	`897bb40886e9362a4b17005c81e128325110b3638f754cc2cd151230f590606a`

Algorithm	Hash digest
SHA256	`47daca0f986f9268809dc82132468763e52ebaab636300f958c9d74291d77ba7`
MD5	`76debd1b9c32323ae5213f152a06ebde`
BLAKE2b-256	`95148c130cacf77f19d18ed0a9c0c7bbd2d4710670dea7a2517d9c5333fac317`

Algorithm	Hash digest
SHA256	`864d92e8c71ecc28d168bc46417ffc7b61bfc78c83c8b00b180efbdfaf53fde3`
MD5	`d25261e610140ff6c2e8cd2e2bc31b61`
BLAKE2b-256	`f96f24556f6cecbd74a99692c18701581a09d2e4f82179b0f88e10e2cb5ce858`

Algorithm	Hash digest
SHA256	`baffdfe2b2acd9713991bb7570b2a174846b00d4fcdb4459e2738af47bae5736`
MD5	`96b9860b14b333d8b28419812d192013`
BLAKE2b-256	`37de95a9258c39482b6d9041c3a2bd6f65979e8c1586d8fedf03953c3fe082df`

Algorithm	Hash digest
SHA256	`508d2a4c0a81cc208e18b771552c131542d734025832a42153c212b00eec7d82`
MD5	`2e6d6528e7860498b17340225a2c76b9`
BLAKE2b-256	`3e7e9f2401bc1314a35a6db080e283554644f2b3558500fa2d789654c6030e48`

Algorithm	Hash digest
SHA256	`7dd757c6ac9e67e5b42f9e94b570d542a1fa5b7c35c3aec0bc3ac72562c91e0c`
MD5	`8dd58164eb23f827d1f5b300d2a6a7e1`
BLAKE2b-256	`fb47afc8f626273379a62d00dba2aad09be7573886bbf1b7ca85f52992cf0b98`

Algorithm	Hash digest
SHA256	`6e31b0f9cf30d60ef8b9db428b99f62a90677d9c17bd0fa17159a833658c3ed0`
MD5	`b558e68f02aba3b43404b866fd3ff0bc`
BLAKE2b-256	`4a9317d3640a61d3a8a1946363600cca34a8651cd689f2b421f776c0e6121144`

Algorithm	Hash digest
SHA256	`e33fd8948f3a7ecce00e3f6fb786216d357042ccfbc541a9ccd3c67a1ea1a053`
MD5	`8553d5002d7c15a13a573c721ba0f8c2`
BLAKE2b-256	`037ae0309be9eddf0b7c240616d698f707e5f6b9e190ecd9df096502cf9506d9`

Algorithm	Hash digest
SHA256	`55b066f3995dc75500339f4897dcb2d6f2c7367ea0562ee5376e993102877a74`
MD5	`d14b9c0fefffe565621cbeb309dc7e4d`
BLAKE2b-256	`944576f877c91738b30ea792c2a2770e4ce40e71a29e75baf81dfe8277043a0f`

Algorithm	Hash digest
SHA256	`3ce7aedc8c7e9be9441051b28f5c1c53bd719109d621f047729870d7ff851e49`
MD5	`d6f5f7be9a8acf3980e28e0d0af237b9`
BLAKE2b-256	`d154e4f218edc8f8867101901da8e812df69f398c5032372df3a5e3c75f62375`

Algorithm	Hash digest
SHA256	`1ebe1d3e0b2b2052a83d9146656e6da152536043aabc517e4063215b5f7624e3`
MD5	`556f3072bb0b6ab84a1ce75997053e2b`
BLAKE2b-256	`3cd9853358b3ec699935c06e187d604de2df32ebc4366746aa739d87c7ddb330`

Algorithm	Hash digest
SHA256	`102c2a430453d9e90d3032f239fa5688e320bedd62767806f5425c0099d25b51`
MD5	`1554686ccd0e201391fccf42cd012616`
BLAKE2b-256	`cc2649bea4fed47a65d9a9dae72cee01d20bbd719100fbf5f195bd8c33e54969`

Algorithm	Hash digest
SHA256	`2d3fd7c280428d73790fb23f0ceb41486623f0a153aedd2287fffff389c26ac1`
MD5	`9923c75c0d070800f8fb484f92a9a0fd`
BLAKE2b-256	`b4e35324d477ee50ba05a2439cbd2291b7d2f1e343880eaecde64d4f71d9cc77`

Algorithm	Hash digest
SHA256	`725688a32efa0230a99e3339eb7c71a8953959782cb7a67d4f056ebd61e17b39`
MD5	`dda4389bd2a13e59e24a0a2ef094be0c`
BLAKE2b-256	`d3a8f0ebb6d829f214b1af00a0a895a874dff63688c877891ea045bf78885278`

Algorithm	Hash digest
SHA256	`f7c79d946c2db5d040422f61dfa80497ed292ffeb40075fcd4a1117fe2108f4d`
MD5	`a520a1a3b986eacc64422cea5ac9ad9d`
BLAKE2b-256	`ae121fbdb491d89fad8abb7aca0189978655cfdc984a380b846478f2ccdfdad8`

Algorithm	Hash digest
SHA256	`f835c05357a5eaa35ea20ee665203b481463c6d69d836c5d64aa54d71a4064ea`
MD5	`fc557b395189b8063ffbe88067ef7a71`
BLAKE2b-256	`5c78a6d299d5505b26d75a84ff5dc28abd3cad1b5bf654126193465e0ab5a26b`

python-igraph 0.9.1

Navigation

Verified details

Maintainers

Unverified details

Project links

Meta

Classifiers

Project description

Project details

Verified details

Maintainers

Unverified details

Project links

Meta

Classifiers

Release history Release notifications | RSS feed

Download files

Source Distribution

Built Distributions

File details

File metadata

File hashes

File details

File metadata

File hashes

File details

File metadata

File hashes

File details

File metadata

File hashes

File details

File metadata

File hashes

File details

File metadata

File hashes

File details

File metadata

File hashes

File details

File metadata

File hashes

File details

File metadata

File hashes

File details

File metadata

File hashes

File details

File metadata

File hashes

File details

File metadata

File hashes

File details

File metadata

File hashes

File details

File metadata

File hashes

File details

File metadata

File hashes

File details

File metadata

File hashes

File details

File metadata

File hashes

File details

File metadata

File hashes

File details

File metadata

File hashes

File details

File metadata

File hashes

Algorithm	Hash digest
SHA256	`8895ca5ee5107ba34280ede192c08da698b9a61ddea70b38af0bb02e29cb3150`
MD5	`2b781d8f655eed6eda9bdc682d1357a2`
BLAKE2b-256	`e768bc45e06257a973f40078ad2dc81fc5a7c70d19ff24f22c4a3db594878d36`

Algorithm	Hash digest
SHA256	`44c280ec6fd8e66627bb23f8c1b3a66ed6039381d6a3c24e03e019e985aa8c17`
MD5	`097733b32c63a5986bb6646fd7a73f76`
BLAKE2b-256	`a2daf1ea6ced4da81020933d33bf4aeac3794a4504864258298f098d8715f435`

Algorithm	Hash digest
SHA256	`ce3596e87e7e930f16a91a14935c325d4f7d4f2b41ceab7681c5dedcf582888d`
MD5	`b1620810a038dfa5db128e76d1e71189`
BLAKE2b-256	`299c54916f5109599f887073719294b3f465f7f0c8c7f7f9e2a5c691ce4ec246`

Algorithm	Hash digest
SHA256	`c263a078dcd4619d7e98d0c6b3c0f06e3ea7ad4bb57154fb1e9b30a8ad2b5081`
MD5	`2fd54185f7ae7951b0ec21f3d9c275a9`
BLAKE2b-256	`f2ddbf716984e8e01e90414f576d4a9fb60fd3c57d2fa5ff404a138f963cfc35`

Algorithm	Hash digest
SHA256	`ca858739512c65346e97b28ba13c8b22831282fe7ca7d0e61452a5b558f4065a`
MD5	`c8876434e4df25bc42936699d6610ec8`
BLAKE2b-256	`743079c072b4d74aafcd8357a82d1d03edac5105fcb090b0d085277f5d73ff89`

Algorithm	Hash digest
SHA256	`135dd8231036751393baa6dd4b729a32268988ea7470c96d1fd9b5bb31d285d1`
MD5	`28cd8b98389ff92f19b0df1de2cf837d`
BLAKE2b-256	`ccd023e16d23c79e2ec65de420585b8cb1890151cf0d3c5f76af63578dbbf2a6`