Skip to main content
logo sknetwork https://img.shields.io/pypi/v/scikit-network.svg https://travis-ci.org/sknetwork-team/scikit-network.svg Documentation Status https://codecov.io/gh/sknetwork-team/scikit-network/branch/master/graph/badge.svg https://img.shields.io/pypi/pyversions/scikit-network.svg

Python package for the analysis of large graphs:

  • Memory-efficient representation as sparse matrices in the CSR format of scipy

  • Fast algorithms

  • Simple API inspired by scikit-learn

Resources

Quickstart

Install scikit-network:

$ pip install scikit-network

Import scikit-network in a Python project:

import sknetwork as skn

See examples in the tutorials; the notebooks are available here.

History

0.19.1 (2020-09-09)

  • Fix visualization features

  • Fix documentation

0.19.0 (2020-09-02)

  • Added link prediction module

  • Added pie-node visualization of memberships

  • Added Weisfeiler-Lehman graph coloring

  • Added Force Atlas 2 graph layout

  • Added triangle listing algorithm for directed and undirected graph

  • Added k-core decomposition algorithm

  • Added k-clique listing algorithm

  • Added color map option in visualization module

  • Updated NetSet URL

0.18.0 (2020-06-08)

  • Added Katz centrality

  • Refactor connectivity module into paths and topology

  • Refactor Diffusion into Dirichlet

  • Added parsers for adjacency list TSV and GraphML

  • Added shortest paths and distances

0.17.0 (2020-05-07)

  • Add clustering by label propagation

  • Add models

  • Add function to build graph from edge list

  • Change a parameter in SVG visualization functions

  • Minor corrections

0.16.0 (2020-04-30)

  • Refactor basics module into connectivity

  • Cython version for label propagation

  • Minor corrections

0.15.2 (2020-04-24)

  • Clarified requirements

  • Minor corrections

0.15.1 (2020-04-21)

  • Added OpenMP support for all platforms

0.15.0 (2020-04-20)

  • Updated ranking module : new pagerank solver, new HITS params, post-processing

  • Polynomes in linear algebra

  • Added meta.name attribute for Bunch

  • Minor corrections

0.14.0 (2020-04-17)

  • Added spring layout in embedding

  • Added label propagation in classification

  • Added save / load functions in data

  • Added display edges parameter in svg graph exports

  • Corrected typos in documentation

0.13.3 (2020-04-13)

  • Minor bug

0.13.2 (2020-04-13)

  • Added wheels for multiple platforms (OSX, Windows (32 & 64 bits) and many Linux) and Python version (3.6/3.7/3.8)

  • Documentation update (SVG dendrograms, tutorial updates)

0.13.1a (2020-04-09)

  • Minor bug

0.13.0a (2020-04-09)

  • Changed from Numba to Cython for better performance

  • Added visualization module

  • Added k-nearest neighbors classifier

  • Added Louvain hierarchy

  • Added predict method in embedding

  • Added soft clustering to clustering algorithms

  • Added soft classification to classification algorithms

  • Added graphs in data module

  • Various API change

0.12.1 (2020-01-20)

  • Added heat kernel based node classifier

  • Updated loaders for WikiLinks

  • Fixed file-related issues for Windows

0.12.0 (2019-12-10)

  • Added VerboseMixin for verbosity features

  • Added Loaders for WikiLinks & Konect databases

0.11.0 (2019-11-28)

  • sknetwork: new API for bipartite graphs

  • new module: Soft node classification

  • new module: Node classification

  • new module: data (merge toy graphs + loader)

  • clustering: Spectral Clustering

  • ranking: new algorithms

  • utils: K-neighbors

  • hierarchy: Spectral WardDense

  • data: loader (Vital Wikipedia)

0.10.1 (2019-08-26)

  • Minor bug

0.10.0 (2019-08-26)

  • Clustering (and related metrics) for directed and bipartite graphs

  • Hierarchical clustering (and related metrics) for directed and bipartite graphs

  • Fix bugs on embedding algorithms

0.9.0 (2019-07-24)

  • Change parser output

  • Fix bugs in ranking algorithms (zero-degree nodes)

  • Add notebooks

  • Import algorithms from scipy (shortest path, connected components, bfs/dfs)

  • Change SVD embedding (now in decreasing order of singular values)

0.8.2 (2019-07-19)

  • Minor bug

0.8.1 (2019-07-18)

  • Added diffusion ranking

  • Minor fixes

  • Minor doc tweaking

0.8.0 (2019-07-17)

  • Changed Louvain, BiLouvain, Paris and PageRank APIs

  • Changed PageRank method

  • Documentation overhaul

  • Improved Jupyter tutorials

0.7.1 (2019-07-04)

  • Added Algorithm class for nicer repr of some classes

  • Added Jupyter notebooks as tutorials in the docs

  • Minor fixes

0.7.0 (2019-06-24)

  • Updated PageRank

  • Added tests for Numba versioning

0.6.1 (2019-06-19)

  • Minor bug

0.6.0 (2019-06-19)

  • Largest connected component

  • Simplex projection

  • Sparse Low Rank Decomposition

  • Numba support for Paris

  • Various fixes and updates

0.5.0 (2019-04-18)

  • Unified Louvain.

0.4.0 (2019-04-03)

  • Added Louvain for directed graphs and ComboLouvain for bipartite graphs.

0.3.0 (2019-03-29)

  • Updated clustering module and documentation.

0.2.0 (2019-03-21)

  • First real release on PyPI.

0.1.1 (2018-05-29)

  • First release on PyPI.

Metadata

Release files for scikit-network 0.19.1

For a detailed explanation of source distributions (sdists) and built distributions (wheels), please see the package formats documentation.

Built distributions (wheels)

Table of built distributions (wheels) for scikit-network 0.19.1
File
scikit_network-0.19.1-cp38-cp38-win_amd64.whl CPython 3.8 CPython 3.8 Windows x86-64 Details
scikit_network-0.19.1-cp38-cp38-win32.whl CPython 3.8 CPython 3.8 Windows x86-32 Details
scikit_network-0.19.1-cp38-cp38-manylinux2010_x86_64.whl CPython 3.8 CPython 3.8 Linux glibc 2.12+ x86-64 Details
scikit_network-0.19.1-cp38-cp38-macosx_10_9_x86_64.whl CPython 3.8 CPython 3.8 macOS 10.9+ x86-64 Details
scikit_network-0.19.1-cp37-cp37m-win_amd64.whl CPython 3.7 CPython 3.7 pymalloc Windows x86-64 Details
scikit_network-0.19.1-cp37-cp37m-win32.whl CPython 3.7 CPython 3.7 pymalloc Windows x86-32 Details
scikit_network-0.19.1-cp37-cp37m-manylinux2010_x86_64.whl CPython 3.7 CPython 3.7 pymalloc Linux glibc 2.12+ x86-64 Details
scikit_network-0.19.1-cp37-cp37m-macosx_10_9_x86_64.whl CPython 3.7 CPython 3.7 pymalloc macOS 10.9+ x86-64 Details
scikit_network-0.19.1-cp36-cp36m-win_amd64.whl CPython 3.6 CPython 3.6 pymalloc Windows x86-64 Details
scikit_network-0.19.1-cp36-cp36m-win32.whl CPython 3.6 CPython 3.6 pymalloc Windows x86-32 Details
scikit_network-0.19.1-cp36-cp36m-manylinux2010_x86_64.whl CPython 3.6 CPython 3.6 pymalloc Linux glibc 2.12+ x86-64 Details
scikit_network-0.19.1-cp36-cp36m-macosx_10_9_x86_64.whl CPython 3.6 CPython 3.6 pymalloc macOS 10.9+ x86-64 Details

Total release size: 34.7 MB

Release files / scikit_network-0.19.1-cp38-cp38-win_amd64.whl

Download URL scikit_network-0.19.1-cp38-cp38-win_amd64.whl
Size 1.4 MB
Tags CPython 3.8 Windows x86-64
SHA-256 checksum
How to use checksums
8ba7c86cfae86f6ecb0580bf0127d09ac206b92224da238ed91d6581bb58474e
BLAKE2b-256 checksum
How to use checksums
ba223ead4fea77f5e88f611c25a5f9c1e7cc41671922dce24c43b6b6d9e3b762
Upload date
Uploaded using Trusted Publishing?
What is trusted publishing?
No
Uploaded via twine/3.2.0 pkginfo/1.5.0.1 requests/2.24.0 setuptools/41.2.0 requests-toolbelt/0.9.1 tqdm/4.48.2 CPython/3.8.0

Release files / scikit_network-0.19.1-cp38-cp38-win32.whl

Download URL scikit_network-0.19.1-cp38-cp38-win32.whl
Size 1.1 MB
Tags CPython 3.8 Windows x86-32
SHA-256 checksum
How to use checksums
757e5326232ba147a087bf2cf3d8d84387ed5cc4aba8c5968beeca79532e8dde
BLAKE2b-256 checksum
How to use checksums
531390c91cca8aa03ede72dc071be2443892e6af0f86c7d625c864dabd083d74
Upload date
Uploaded using Trusted Publishing?
What is trusted publishing?
No
Uploaded via twine/3.2.0 pkginfo/1.5.0.1 requests/2.24.0 setuptools/41.2.0 requests-toolbelt/0.9.1 tqdm/4.48.2 CPython/3.8.0

Release files / scikit_network-0.19.1-cp38-cp38-manylinux2010_x86_64.whl

Download URL scikit_network-0.19.1-cp38-cp38-manylinux2010_x86_64.whl
Size 7.8 MB
Tags CPython 3.8 Linux glibc 2.12+ x86-64
SHA-256 checksum
How to use checksums
2787350db379713d35161c5f1e3282c72ed090e2fda1ef9708d774c521edc3fe
BLAKE2b-256 checksum
How to use checksums
9ee91a91d6565cbf28840c0c100621956dd3f866303fa281c76ddc29c22ceccb
Upload date
Uploaded using Trusted Publishing?
What is trusted publishing?
No
Uploaded via twine/3.2.0 pkginfo/1.5.0.1 requests/2.24.0 setuptools/47.3.1 requests-toolbelt/0.9.1 tqdm/4.48.2 CPython/3.6.7

Release files / scikit_network-0.19.1-cp38-cp38-macosx_10_9_x86_64.whl

Download URL scikit_network-0.19.1-cp38-cp38-macosx_10_9_x86_64.whl
Size 1.7 MB
Tags CPython 3.8 macOS 10.9+ x86-64
SHA-256 checksum
How to use checksums
d8b6bb81ba227728ffc3b6cf7763d15cdd642ceb2d4bd370099b785e70517ba2
BLAKE2b-256 checksum
How to use checksums
bb9ea905fe1bf897cfcad715ba5a357a81f1456c922c051b777d3b0dcae1bc37
Upload date
Uploaded using Trusted Publishing?
What is trusted publishing?
No
Uploaded via twine/3.2.0 pkginfo/1.5.0.1 requests/2.24.0 setuptools/46.4.0 requests-toolbelt/0.9.1 tqdm/4.48.2 CPython/3.8.4

Release files / scikit_network-0.19.1-cp37-cp37m-win_amd64.whl

Download URL scikit_network-0.19.1-cp37-cp37m-win_amd64.whl
Size 1.3 MB
Tags CPython 3.7 CPython 3.7 pymalloc Windows x86-64
SHA-256 checksum
How to use checksums
e54f53f6874880a08888e9852c61393bdbf1ed2de08db9e88e9661fa882867d3
BLAKE2b-256 checksum
How to use checksums
adac27e5b94e6f3dd4c8682fe04ead470ba74c3e575057aa91f0b8e74a80c881
Upload date
Uploaded using Trusted Publishing?
What is trusted publishing?
No
Uploaded via twine/3.2.0 pkginfo/1.5.0.1 requests/2.24.0 setuptools/41.2.0 requests-toolbelt/0.9.1 tqdm/4.48.2 CPython/3.8.0

Release files / scikit_network-0.19.1-cp37-cp37m-win32.whl

Download URL scikit_network-0.19.1-cp37-cp37m-win32.whl
Size 1.1 MB
Tags CPython 3.7 CPython 3.7 pymalloc Windows x86-32
SHA-256 checksum
How to use checksums
9eb5c181197393df2c12ac9508d90bf59e8c7d6018da860f3b20850db92e97ad
BLAKE2b-256 checksum
How to use checksums
73e7e5f918c336e8507867d704a9f449b464c28835264212ade42b07789cad6a
Upload date
Uploaded using Trusted Publishing?
What is trusted publishing?
No
Uploaded via twine/3.2.0 pkginfo/1.5.0.1 requests/2.24.0 setuptools/41.2.0 requests-toolbelt/0.9.1 tqdm/4.48.2 CPython/3.8.0

Release files / scikit_network-0.19.1-cp37-cp37m-manylinux2010_x86_64.whl

Download URL scikit_network-0.19.1-cp37-cp37m-manylinux2010_x86_64.whl
Size 7.2 MB
Tags CPython 3.7 CPython 3.7 pymalloc Linux glibc 2.12+ x86-64
SHA-256 checksum
How to use checksums
845f54d3f84c7ef9dca90550ea1bb0e1946d704b019615328a95c0265c2e1288
BLAKE2b-256 checksum
How to use checksums
4a98acde347b01b54b1d34c7c8d7acc406a022c9d9ba4b91258e77ff99b3ff81
Upload date
Uploaded using Trusted Publishing?
What is trusted publishing?
No
Uploaded via twine/3.2.0 pkginfo/1.5.0.1 requests/2.24.0 setuptools/47.3.1 requests-toolbelt/0.9.1 tqdm/4.48.2 CPython/3.6.7

Release files / scikit_network-0.19.1-cp37-cp37m-macosx_10_9_x86_64.whl

Download URL scikit_network-0.19.1-cp37-cp37m-macosx_10_9_x86_64.whl
Size 1.7 MB
Tags CPython 3.7 CPython 3.7 pymalloc macOS 10.9+ x86-64
SHA-256 checksum
How to use checksums
9be6e6799058242196672fdaa818dc8dc1844dcf330ce7c923eb4e0b7e5a3a4c
BLAKE2b-256 checksum
How to use checksums
5055708fc33fa1b3691ab0a68715dd0a0b44e6a3d5cf83edf781a6f729438c01
Upload date
Uploaded using Trusted Publishing?
What is trusted publishing?
No
Uploaded via twine/3.2.0 pkginfo/1.5.0.1 requests/2.24.0 setuptools/46.4.0 requests-toolbelt/0.9.1 tqdm/4.48.2 CPython/3.8.4

Release files / scikit_network-0.19.1-cp36-cp36m-win_amd64.whl

Download URL scikit_network-0.19.1-cp36-cp36m-win_amd64.whl
Size 1.3 MB
Tags CPython 3.6 CPython 3.6 pymalloc Windows x86-64
SHA-256 checksum
How to use checksums
8df12cba62f36c48d2cd94d85103015ac4d2324c90db07f13e77db8fec9e635c
BLAKE2b-256 checksum
How to use checksums
1946b721cfb8bec6ac8267010ea7a72c3159e9405ca0c8cf2d40cdd8c221a204
Upload date
Uploaded using Trusted Publishing?
What is trusted publishing?
No
Uploaded via twine/3.2.0 pkginfo/1.5.0.1 requests/2.24.0 setuptools/41.2.0 requests-toolbelt/0.9.1 tqdm/4.48.2 CPython/3.8.0

Release files / scikit_network-0.19.1-cp36-cp36m-win32.whl

Download URL scikit_network-0.19.1-cp36-cp36m-win32.whl
Size 1.1 MB
Tags CPython 3.6 CPython 3.6 pymalloc Windows x86-32
SHA-256 checksum
How to use checksums
a223f17ef772f7575e7a6a320d7c2c7c489c496bf4b6dac62f0d029215b68b72
BLAKE2b-256 checksum
How to use checksums
cbb6caf4c0625b9dafa9c7d15174d2e9932108e07a1ae0d248c4ba1c658bd5d3
Upload date
Uploaded using Trusted Publishing?
What is trusted publishing?
No
Uploaded via twine/3.2.0 pkginfo/1.5.0.1 requests/2.24.0 setuptools/41.2.0 requests-toolbelt/0.9.1 tqdm/4.48.2 CPython/3.8.0

Release files / scikit_network-0.19.1-cp36-cp36m-manylinux2010_x86_64.whl

Download URL scikit_network-0.19.1-cp36-cp36m-manylinux2010_x86_64.whl
Size 7.2 MB
Tags CPython 3.6 CPython 3.6 pymalloc Linux glibc 2.12+ x86-64
SHA-256 checksum
How to use checksums
2a95ff57c71f451851971e015f223cd7c28848ed75ac4923f53fa8b7b27eb4c1
BLAKE2b-256 checksum
How to use checksums
287d683ec44de004b722cc6dd5d3f3196c4f787e7833e4be20d067949aa70dd1
Upload date
Uploaded using Trusted Publishing?
What is trusted publishing?
No
Uploaded via twine/3.2.0 pkginfo/1.5.0.1 requests/2.24.0 setuptools/47.3.1 requests-toolbelt/0.9.1 tqdm/4.48.2 CPython/3.6.7

Release files / scikit_network-0.19.1-cp36-cp36m-macosx_10_9_x86_64.whl

Download URL scikit_network-0.19.1-cp36-cp36m-macosx_10_9_x86_64.whl
Size 1.7 MB
Tags CPython 3.6 CPython 3.6 pymalloc macOS 10.9+ x86-64
SHA-256 checksum
How to use checksums
09c61e50cc4a45e1718c937f57181c564a6f31f42ec40b44444606fc2b1faeba
BLAKE2b-256 checksum
How to use checksums
7793577d1135172390407ae79d51e6ebd8d2921eea6a490144a7ee033874056c
Upload date
Uploaded using Trusted Publishing?
What is trusted publishing?
No
Uploaded via twine/3.2.0 pkginfo/1.5.0.1 requests/2.24.0 setuptools/46.4.0 requests-toolbelt/0.9.1 tqdm/4.48.2 CPython/3.8.4

Release history Release notifications | RSS feed

0.32.0

4 release files

0.21.0

9 release files

This release

0.19.1 This release

12 release files

0.12.1

2 release files

0.12.0

2 release files

0.11.0

2 release files

0.10.1

2 release files

0.9.0

2 release files

0.8.2

2 release files

0.8.0

2 release files

0.7.1

2 release files

0.7.0

2 release files

0.6.1

2 release files

0.5.0

2 release files

0.4.0

2 release files

0.3.0

2 release files

0.2.0

2 release files

0.1.1

2 release files

Anthropic, PBC Visionary sponsor Bloomberg Visionary sponsor Hudson River Trading Visionary sponsor Meta Visionary sponsor NVIDIA Visionary sponsor Microsoft Sustainability sponsor Depot Continuous Integration AWS Cloud computing and Security Sponsor Datadog Monitoring Fastly CDN Google Download Analytics Sentry Error logging StatusPage Status page