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gnu: python-leidenalg: Update to 0.10.2.

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* gnu/packages/graph.scm (python-leidenalg): Update to 0.10.2.
[inputs]: Add libleidenalg.
[description]: Update to account for removal of C++ implementation.

Change-Id: Ia00e819eda4c03f25e54dc72483c7bcaf2ab396f
This commit is contained in:
Greg Hogan 2025-05-05 15:52:35 +00:00
parent 35a15c5a70
commit c0fc7d2a0a
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1 changed files with 6 additions and 11 deletions
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gnu/packages/graph.scm
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@ -715,14 +715,14 @@ of millions of nodes (as long as they can fit in memory).")
(define-public python-leidenalg (define-public python-leidenalg
(package (package
(name "python-leidenalg") (name "python-leidenalg")
(version "0.9.1") (version "0.10.2")
(source (source
(origin (origin
(method url-fetch) (method url-fetch)
(uri (pypi-uri "leidenalg" version)) (uri (pypi-uri "leidenalg" version))
(sha256 (sha256
(base32 (base32
"1wvmi6ca9kf8pbxg6b18n64h82wr9a6wcdazyn82pww0dwxzwp3y")))) "0k1f35bmgff8vc5fcyqa2dqfa1x17rb0vqzwkdqlm0sr5fllfh8g"))))
(build-system python-build-system) (build-system python-build-system)
(arguments (arguments
'(#:tests? #f ;tests are not included '(#:tests? #f ;tests are not included
@ -739,19 +739,14 @@ of millions of nodes (as long as they can fit in memory).")
(native-inputs (native-inputs
(list pkg-config python-setuptools-scm)) (list pkg-config python-setuptools-scm))
(inputs (inputs
(list igraph)) (list igraph libleidenalg))
(propagated-inputs (propagated-inputs
(list python-igraph)) (list python-igraph))
(home-page "https://github.com/vtraag/leidenalg") (home-page "https://github.com/vtraag/leidenalg")
(synopsis "Community detection in large networks") (synopsis "Community detection in large networks")
(description (description "Leiden is a general algorithm for methods of community
"Leiden is a general algorithm for methods of community detection in detection in large networks and is an extension of the Louvain algorithm. This
large networks. This package implements the Leiden algorithm in C++ and packages provides a Python wrapper to the C++ implementation.")
exposes it to Python. Besides the relative flexibility of the implementation,
it also scales well, and can be run on graphs of millions of nodes (as long as
they can fit in memory). The core function is @code{find_partition} which
finds the optimal partition using the Leiden algorithm, which is an extension
of the Louvain algorithm, for a number of different methods.")
(license license:gpl3+))) (license license:gpl3+)))
(define-public edge-addition-planarity-suite (define-public edge-addition-planarity-suite