[{"data":1,"prerenderedAt":-1},["ShallowReactive",2],{"project-2696":3},{"id":4,"name":5,"fullName":6,"owner":5,"repo":5,"description":7,"homepage":8,"htmlUrl":9,"language":10,"languages":9,"totalLinesOfCode":9,"stars":11,"forks":12,"watchers":13,"openIssues":14,"contributorsCount":15,"subscribersCount":15,"size":15,"stars1d":16,"stars7d":17,"stars30d":18,"stars90d":15,"forks30d":15,"starsTrendScore":19,"compositeScore":20,"rankGlobal":9,"rankLanguage":9,"license":21,"archived":22,"fork":22,"defaultBranch":23,"hasWiki":22,"hasPages":22,"topics":24,"createdAt":9,"pushedAt":9,"updatedAt":32,"readmeContent":33,"aiSummary":34,"trendingCount":15,"starSnapshotCount":15,"syncStatus":35,"lastSyncTime":36,"discoverSource":37},2696,"networkx","networkx\u002Fnetworkx","Network Analysis in Python","https:\u002F\u002Fnetworkx.org",null,"Python",16998,3518,275,145,0,5,19,111,23,45,"Other",false,"main",[25,26,27,28,29,30,31],"complex-networks","graph-algorithms","graph-analysis","graph-generation","graph-theory","graph-visualization","python","2026-06-12 02:00:43","NetworkX\n========\n\n\n.. image::\n    https:\u002F\u002Fgithub.com\u002Fnetworkx\u002Fnetworkx\u002Factions\u002Fworkflows\u002Ftest.yml\u002Fbadge.svg?branch=main\n    :target: https:\u002F\u002Fgithub.com\u002Fnetworkx\u002Fnetworkx\u002Factions\u002Fworkflows\u002Ftest.yml\n\n.. image::\n    https:\u002F\u002Fimg.shields.io\u002Fpypi\u002Fv\u002Fnetworkx.svg?\n    :target: https:\u002F\u002Fpypi.python.org\u002Fpypi\u002Fnetworkx\n\n.. image::\n    https:\u002F\u002Fimg.shields.io\u002Fpypi\u002Fl\u002Fnetworkx.svg?\n    :target: https:\u002F\u002Fgithub.com\u002Fnetworkx\u002Fnetworkx\u002Fblob\u002Fmain\u002FLICENSE.txt\n\n.. image::\n    https:\u002F\u002Fimg.shields.io\u002Fpypi\u002Fpyversions\u002Fnetworkx.svg?\n    :target: https:\u002F\u002Fpypi.python.org\u002Fpypi\u002Fnetworkx\n\n.. image::\n    https:\u002F\u002Finsights.linuxfoundation.org\u002Fapi\u002Fbadge\u002Fhealth-score?project=networkx\n    :target: https:\u002F\u002Finsights.linuxfoundation.org\u002Fproject\u002Fnetworkx\n\n\nNetworkX is a Python package for the creation, manipulation,\nand study of the structure, dynamics, and functions\nof complex networks.\n\n- **Website (including documentation):** https:\u002F\u002Fnetworkx.org\n- **Mailing list:** https:\u002F\u002Fgroups.google.com\u002Fforum\u002F#!forum\u002Fnetworkx-discuss\n- **Source:** https:\u002F\u002Fgithub.com\u002Fnetworkx\u002Fnetworkx\n- **Bug reports:** https:\u002F\u002Fgithub.com\u002Fnetworkx\u002Fnetworkx\u002Fissues\n- **Report a security vulnerability:** https:\u002F\u002Ftidelift.com\u002Fsecurity\n- **Tutorial:** https:\u002F\u002Fnetworkx.org\u002Fdocumentation\u002Flatest\u002Ftutorial.html\n- **GitHub Discussions:** https:\u002F\u002Fgithub.com\u002Fnetworkx\u002Fnetworkx\u002Fdiscussions\n- **Discord (Scientific Python) invite link:** https:\u002F\u002Fdiscord.com\u002Finvite\u002Fvur45CbwMz\n- **NetworkX meetings calendar (open to all):** https:\u002F\u002Fscientific-python.org\u002Fcalendars\u002Fnetworkx.ics\n\nSimple example\n--------------\n\nFind the shortest path between two nodes in an undirected graph:\n\n.. code:: pycon\n\n    >>> import networkx as nx\n    >>> G = nx.Graph()\n    >>> G.add_edge(\"A\", \"B\", weight=4)\n    >>> G.add_edge(\"B\", \"D\", weight=2)\n    >>> G.add_edge(\"A\", \"C\", weight=3)\n    >>> G.add_edge(\"C\", \"D\", weight=4)\n    >>> nx.shortest_path(G, \"A\", \"D\", weight=\"weight\")\n    ['A', 'B', 'D']\n\nInstall\n-------\n\nInstall the latest released version of NetworkX:\n\n.. code:: shell\n\n    $ pip install networkx\n\nInstall with all optional dependencies:\n\n.. code:: shell\n\n    $ pip install networkx[default]\n\nFor additional details,\nplease see the `installation guide \u003Chttps:\u002F\u002Fnetworkx.org\u002Fdocumentation\u002Fstable\u002Finstall.html>`_.\n\nBugs\n----\n\nPlease report any bugs that you find `here \u003Chttps:\u002F\u002Fgithub.com\u002Fnetworkx\u002Fnetworkx\u002Fissues>`_.\nOr, even better, fork the repository on `GitHub \u003Chttps:\u002F\u002Fgithub.com\u002Fnetworkx\u002Fnetworkx>`_\nand create a pull request (PR). We welcome all changes, big or small, and we\nwill help you make the PR if you are new to `git` (just ask on the issue and\u002For\nsee the `contributor guide \u003Chttps:\u002F\u002Fnetworkx.org\u002Fdocumentation\u002Flatest\u002Fdeveloper\u002Fcontribute.html>`_).\n\nLicense\n-------\n\nReleased under the `3-clause BSD license \u003Chttps:\u002F\u002Fgithub.com\u002Fnetworkx\u002Fnetworkx\u002Fblob\u002Fmain\u002FLICENSE.txt>`_::\n\n    Copyright (c) 2004-2025, NetworkX Developers\n    Aric Hagberg \u003Chagberg@lanl.gov>\n    Dan Schult \u003Cdschult@colgate.edu>\n    Pieter Swart \u003Cswart@lanl.gov>\n","NetworkX 是一个用于创建、操作和研究复杂网络结构、动态及功能的 Python 包。它支持图算法、图分析、图生成以及图可视化等核心功能，能够处理各种类型的图数据结构，包括无向图、有向图、多重图等，并提供了丰富的图论算法库。NetworkX 适用于需要进行网络分析的各种场景，如社交网络分析、生物信息学中的蛋白质相互作用网络建模、互联网拓扑结构研究等。其简洁易用的 API 和强大的功能使其成为科研人员和开发者的首选工具之一。",2,"2026-06-11 02:50:56","top_language"]