{"id":13935921,"url":"https://github.com/sepandhaghighi/pyrgg","last_synced_at":"2025-04-05T07:05:17.443Z","repository":{"id":20309959,"uuid":"89410101","full_name":"sepandhaghighi/pyrgg","owner":"sepandhaghighi","description":"🔧 Python Random Graph 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align=\"center\"\u003e\n\t\u003cimg src=\"https://github.com/sepandhaghighi/pyrgg/raw/master/otherfile/logo.png\" width=\"450\"\u003e\n\t\u003ch1\u003ePyRGG: Python Random Graph Generator\u003c/h1\u003e\n\t\u003ca href=\"https://www.pyrgg.site\"\u003e\u003cimg src=\"https://img.shields.io/website-up-down-green-red/http/shields.io.svg?label=website\"\u003e\u003c/a\u003e\n\t\u003ca href=\"https://badge.fury.io/py/pyrgg\"\u003e\u003cimg src=\"https://badge.fury.io/py/pyrgg.svg\" alt=\"PyPI version\" height=\"18\"\u003e\u003c/a\u003e\n\t\u003ca href=\"https://anaconda.org/sepandhaghighi/pyrgg\"\u003e\u003cimg src=\"https://anaconda.org/sepandhaghighi/pyrgg/badges/version.svg\"\u003e\u003c/a\u003e\n\t\u003ca href=\"https://codecov.io/gh/sepandhaghighi/pyrgg\"\u003e\u003cimg src=\"https://codecov.io/gh/sepandhaghighi/pyrgg/branch/master/graph/badge.svg\" alt=\"Codecov\"\u003e\u003c/a\u003e\n\t\u003ca href=\"https://www.python.org/\"\u003e\u003cimg src=\"https://img.shields.io/badge/built%20with-Python3-green.svg\" alt=\"built with Python3\"\u003e\u003c/a\u003e\n\t\u003ca href=\"https://discord.gg/dfYAWVMaCW\"\u003e\u003cimg src=\"https://img.shields.io/discord/1013411447130308669.svg\" alt=\"Discord Channel\"\u003e\u003c/a\u003e\n\u003c/div\u003e\t\t\t\n\t\t\t\t\n## Overview\t\n\n\u003cp align=\"justify\"\u003e\t\t\nPyRGG is a user-friendly synthetic random graph generator that is written in Python and supports multiple graph file formats, such as \u003ca href =\"https://www.diag.uniroma1.it/challenge9/format.shtml#graph\"\u003eDIMACS-Graph\u003c/a\u003e files. It can generate graphs of various sizes and is specifically designed to create input files for a wide range of graph-based research applications, including testing, benchmarking, and performance analysis of graph processing frameworks. PyRGG is aimed at computer scientists who are studying graph algorithms and graph processing frameworks.\n\u003c/p\u003e\n\n\u003ctable\u003e\n\t\u003ctr\u003e \n\t\t\u003ctd align=\"center\"\u003eOpen Hub\u003c/td\u003e\n\t\t\u003ctd align=\"center\"\u003e\u003ca href=\"https://www.openhub.net/p/pyrgg\"\u003e\u003cimg src=\"https://www.openhub.net/p/pyrgg/widgets/project_thin_badge.gif\"\u003e\u003c/a\u003e\u003c/td\u003e\t\n\t\u003c/tr\u003e\n\t\u003ctr\u003e\n\t\t\u003ctd align=\"center\"\u003ePyPI Counter\u003c/td\u003e\n\t\t\u003ctd align=\"center\"\u003e\u003ca href=\"https://pepy.tech/projects/pyrgg\"\u003e\u003cimg src=\"https://static.pepy.tech/badge/pyrgg\" alt=\"PyPI Downloads\"\u003e\u003c/a\u003e\u003c/td\u003e\n\t\u003c/tr\u003e\n\t\u003ctr\u003e\n\t\t\u003ctd align=\"center\"\u003eGithub Stars\u003c/td\u003e\n\t\t\u003ctd align=\"center\"\u003e\u003ca href=\"https://github.com/sepandhaghighi/pyrgg\"\u003e\u003cimg src=\"https://img.shields.io/github/stars/sepandhaghighi/pyrgg.svg?style=social\u0026label=Stars\"\u003e\u003c/a\u003e\u003c/td\u003e\n\t\u003c/tr\u003e\n\u003c/table\u003e\n\n\n\n\u003ctable\u003e\n\t\u003ctr\u003e \n\t\t\u003ctd align=\"center\"\u003eBranch\u003c/td\u003e\n\t\t\u003ctd align=\"center\"\u003emaster\u003c/td\u003e\t\n\t\t\u003ctd align=\"center\"\u003edev\u003c/td\u003e\t\n\t\u003c/tr\u003e\n\t\u003ctr\u003e\n\t\t\u003ctd align=\"center\"\u003eCI\u003c/td\u003e\n\t\t\u003ctd align=\"center\"\u003e\u003cimg src=\"https://github.com/sepandhaghighi/pyrgg/actions/workflows/test.yml/badge.svg?branch=master\"\u003e\u003c/td\u003e\n\t\t\u003ctd align=\"center\"\u003e\u003cimg src=\"https://github.com/sepandhaghighi/pyrgg/actions/workflows/test.yml/badge.svg?branch=dev\"\u003e\u003c/td\u003e\n\t\u003c/tr\u003e\n\u003c/table\u003e\n\n\n\u003ctable\u003e\n\t\u003ctr\u003e \n\t\t\u003ctd align=\"center\"\u003eCode Quality\u003c/td\u003e\n\t\t\u003ctd align=\"center\"\u003e\u003ca href=\"https://www.codacy.com/app/sepand-haghighi/pyrgg?utm_source=github.com\u0026amp;utm_medium=referral\u0026amp;utm_content=sepandhaghighi/pyrgg\u0026amp;utm_campaign=Badge_Grade\"\u003e\u003cimg src=\"https://api.codacy.com/project/badge/Grade/11ec048bcd594d84997380b64d2d4add\"/\u003e\u003c/a\u003e\u003c/td\u003e\t\n        \u003ctd align=\"center\"\u003e\u003ca href=\"https://codebeat.co/projects/github-com-sepandhaghighi-pyrgg-dev\"\u003e\u003cimg alt=\"codebeat badge\" src=\"https://codebeat.co/badges/3f6c7449-3dfc-406b-b233-9fe615c2d103\" /\u003e\u003c/a\u003e\u003c/td\u003e\t\n\t\t\u003ctd align=\"center\"\u003e\u003ca href=\"https://www.codefactor.io/repository/github/sepandhaghighi/pyrgg\"\u003e\u003cimg src=\"https://www.codefactor.io/repository/github/sepandhaghighi/pyrgg/badge\" alt=\"CodeFactor\" /\u003e\u003c/a\u003e\u003c/td\u003e\t\n\t\u003c/tr\u003e\n\u003c/table\u003e\n\n\n## Installation\t\t\n\n### PyPI\n- Check [Python Packaging User Guide](https://packaging.python.org/installing/)     \n- `pip install pyrgg==1.6`\t\t\t\t\t\t\n\n### Source Code\n- Download [Version 1.6](https://github.com/sepandhaghighi/pyrgg/archive/v1.6.zip) or [Latest Source ](https://github.com/sepandhaghighi/pyrgg/archive/dev.zip)\n- `pip install .`\n\n### Conda\n- Check [Conda Managing Package](https://conda.io)\n- `conda install -c sepandhaghighi pyrgg`\n\n### Exe Version\n\n⚠️ Only Windows\n\n⚠️ For PyRGG targeting Windows \u003c 10, the user needs to take special care to include the Visual C++ run-time `.dlls`(for more information visit [here](https://pyinstaller.org/en/v3.3.1/usage.html#windows))\n\n- Download [Exe-Version 1.6](https://github.com/sepandhaghighi/pyrgg/releases/download/v1.6/PYRGG-1.6.exe)\n- Run `PYRGG-1.6.exe`\n\n### System Requirements\nPyRGG will likely run on a modern dual core PC. Typical configuration is:\n\n- Dual Core CPU (2.0 Ghz+)\n- 4GB of RAM\n\n⚠️ Note that it may run on lower end equipment though good performance is not guaranteed\n\n\n## Usage\n- Open `CMD` (Windows) or `Terminal` (Linux)\n- Run `pyrgg` or `python -m pyrgg` (or run `PYRGG.exe`)\n- Enter data\t\t\n\n\u003cdiv align=\"center\"\u003e\n\n\u003ca href=\"https://asciinema.org/a/539844\" target=\"_blank\"\u003e\u003cimg src=\"https://asciinema.org/a/539844.svg\" /\u003e\u003c/a\u003e\n\n\u003c/div\u003e\n\n## Engines\n\n### PyRGG\n\n\u003ctable\u003e\n\t\u003ctr\u003e\n\t\t\u003cth\u003eParameter\u003c/th\u003e\n\t\t\u003cth\u003eDescription\u003c/th\u003e\n\t\u003c/tr\u003e\n\t\u003ctr\u003e\n\t\t\u003ctd align=\"center\"\u003eVertices Number\u003c/td\u003e\n\t\t\u003ctd align=\"center\"\u003eThe total number of vertices in the graph\u003c/td\u003e\n\t\u003c/tr\u003e\n\t\u003ctr\u003e\n\t\t\u003ctd align=\"center\"\u003eMin Edge Number\u003c/td\u003e\n\t\t\u003ctd align=\"center\"\u003eThe minimum number of edges connected to each vertex\u003c/td\u003e\n\t\u003c/tr\u003e\n\t\u003ctr\u003e\n\t\t\u003ctd align=\"center\"\u003eMax Edge Number\u003c/td\u003e\n\t\t\u003ctd align=\"center\"\u003eThe maximum number of edges connected to each vertex\u003c/td\u003e\n\t\u003c/tr\u003e\n\t\u003ctr\u003e\n\t\t\u003ctd align=\"center\"\u003eWeighted / Unweighted\u003c/td\u003e\n\t\t\u003ctd align=\"center\"\u003eSpecifies whether the graph is weighted or unweighted\u003c/td\u003e\n\t\u003c/tr\u003e\n\t\u003ctr\u003e\n\t\t\u003ctd align=\"center\"\u003eMin Weight\u003c/td\u003e\n\t\t\u003ctd align=\"center\"\u003eThe minimum weight of the edges (if weighted)\u003c/td\u003e\n\t\u003c/tr\u003e\n\t\u003ctr\u003e\n\t\t\u003ctd align=\"center\"\u003eMax Weight\u003c/td\u003e\n\t\t\u003ctd align=\"center\"\u003eThe maximum weight of the edges (if weighted)\u003c/td\u003e\n\t\u003c/tr\u003e\n\t\u003ctr\u003e\n\t\t\u003ctd align=\"center\"\u003eSigned / Unsigned\u003c/td\u003e\n\t\t\u003ctd align=\"center\"\u003eSpecifies whether the edge weights are signed or unsigned\u003c/td\u003e\n\t\u003c/tr\u003e\n\t\u003ctr\u003e\n\t\t\u003ctd align=\"center\"\u003eDirected / Undirected\u003c/td\u003e\n\t\t\u003ctd align=\"center\"\u003eSpecifies whether the graph is directed or undirected\u003c/td\u003e\n\t\u003c/tr\u003e\n\t\u003ctr\u003e\n\t\t\u003ctd align=\"center\"\u003eSelf Loop / No Self Loop\u003c/td\u003e\n\t\t\u003ctd align=\"center\"\u003eSpecifies whether self-loop is allowed or not\u003c/td\u003e\n\t\u003c/tr\u003e\n\t\u003ctr\u003e\n\t\t\u003ctd align=\"center\"\u003eSimple / Multigraph\u003c/td\u003e\n\t\t\u003ctd align=\"center\"\u003eSpecifies whether the graph is a simple graph or a multigraph\u003c/td\u003e\n\t\u003c/tr\u003e\n\u003c/table\u003e\n\n### Erdős–Rényi-Gilbert\n\n\u003ctable\u003e\n\t\u003ctr\u003e\n\t\t\u003cth\u003eParameter\u003c/th\u003e\n\t\t\u003cth\u003eDescription\u003c/th\u003e\n\t\u003c/tr\u003e\n\t\u003ctr\u003e\n\t\t\u003ctd align=\"center\"\u003eVertices Number\u003c/td\u003e\n\t\t\u003ctd align=\"center\"\u003eThe total number of vertices in the graph\u003c/td\u003e\n\t\u003c/tr\u003e\n\t\u003ctr\u003e\n\t\t\u003ctd align=\"center\"\u003eProbability\u003c/td\u003e\n\t\t\u003ctd align=\"center\"\u003eThe probability for edge creation between any two vertices\u003c/td\u003e\n\t\u003c/tr\u003e\n\t\u003ctr\u003e\n\t\t\u003ctd align=\"center\"\u003eDirected / Undirected\u003c/td\u003e\n\t\t\u003ctd align=\"center\"\u003eSpecifies whether the graph is directed or undirected\u003c/td\u003e\n\t\u003c/tr\u003e\n\u003c/table\u003e\n\n### Erdős–Rényi\n\n\u003ctable\u003e\n\t\u003ctr\u003e\n\t\t\u003cth\u003eParameter\u003c/th\u003e\n\t\t\u003cth\u003eDescription\u003c/th\u003e\n\t\u003c/tr\u003e\n\t\u003ctr\u003e\n\t\t\u003ctd align=\"center\"\u003eVertices Number\u003c/td\u003e\n\t\t\u003ctd align=\"center\"\u003eThe total number of vertices in the graph\u003c/td\u003e\n\t\u003c/tr\u003e\n\t\u003ctr\u003e\n\t\t\u003ctd align=\"center\"\u003eEdge Number\u003c/td\u003e\n\t\t\u003ctd align=\"center\"\u003eThe total number of edges in the graph\u003c/td\u003e\n\t\u003c/tr\u003e\n\t\u003ctr\u003e\n\t\t\u003ctd align=\"center\"\u003eDirected / Undirected\u003c/td\u003e\n\t\t\u003ctd align=\"center\"\u003eSpecifies whether the graph is directed or undirected\u003c/td\u003e\n\t\u003c/tr\u003e\n\u003c/table\u003e\n\n## Supported Formats \t\t\t\n\n### DIMACS\n\n```\n\tp sp \u003cnumber of vertices\u003e \u003cnumber of edges\u003e\n\ta \u003chead_1\u003e \u003ctail_1\u003e \u003cweight_1\u003e\n\n\t.\n\t.\n\t.\n\t\t\n\ta \u003chead_n\u003e \u003ctail_n\u003e \u003cweight_n\u003e\n```\n\n* [Document](http://www.diag.uniroma1.it/challenge9/format.shtml)\n* [Sample 1](https://www.dropbox.com/s/i80tnwuuv4iyqet/100.gr.gz?dl=0) (100 Vertices , 3KB)\n* [Sample 2](https://www.dropbox.com/s/lqk42pwu7o4xauv/1000.gr.gz?dl=0) (1000 Vertices , 13KB)\n* [Sample 3](https://www.dropbox.com/s/93dp8cjs6lnu83u/1000000.gr.gz?dl=0) (1000000 Vertices , 7MB)\n* [Sample 4](https://www.dropbox.com/s/rrxdc4wt0ldonfk/5000000.gr.gz?dl=0) (5000000 Vertices , 37MB)\n\n### CSV\n\n```\n\t\u003chead_1\u003e,\u003ctail_1\u003e,\u003cweight_1\u003e\n\n\t.\n\t.\n\t.\n\t\t\n\t\u003chead_n\u003e,\u003ctail_n\u003e,\u003cweight_n\u003e\n```\n\n* [Document](https://en.wikipedia.org/wiki/Comma-separated_values)\n* [Sample 1](https://www.dropbox.com/s/dmld0eadftnatr5/100.csv?dl=0) (100 Vertices , 3KB)\n* [Sample 2](https://www.dropbox.com/s/juxah4nwamzdegr/1000.csv?dl=0) (1000 Vertices , 51KB)\n\n### TSV\n\n```\n\t\u003chead_1\u003e\t\u003ctail_1\u003e\t\u003cweight_1\u003e\n\n\t.\n\t.\n\t.\n\t\t\n\t\u003chead_n\u003e\t\u003ctail_n\u003e\t\u003cweight_n\u003e\n```\n\n* [Document](https://en.wikipedia.org/wiki/Tab-separated_values)\n* [Sample 1](https://www.dropbox.com/s/j3zgs4kx2paxe75/100.tsv?dl=0) (100 Vertices , 29KB)\n* [Sample 2](https://www.dropbox.com/s/ykagmjgwlpim6dq/1000.tsv?dl=0) (1000 Vertices , 420KB)\n\n### JSON\n\n```\n{\n\t\"properties\": {\n\t\t\"directed\": true,\n\t\t\"signed\": true,\n\t\t\"multigraph\": true,\n\t\t\"weighted\": true,\n\t\t\"self_loop\": true\n\t},\n\t\"graph\": {\n\t\t\"nodes\":[\n\t\t{\n\t\t\t\"id\": 1\n\t\t},\n\n\t\t.\n\t\t.\n\t\t.\n\n\t\t{\n\t\t\t\"id\": n\n\t\t}\n\t\t],\n\t\t\"edges\":[\n\t\t{\n\t\t\t\"source\": head_1,\n\t\t\t\"target\": tail_1,\n\t\t\t\"weight\": weight_1\n\t\t},\n\n\t\t.\n\t\t.\n\t\t.\n\n\t\t{\n\t\t\t\"source\": head_n,\n\t\t\t\"target\": tail_n,\n\t\t\t\"weight\": weight_n\n\t\t}\n\t\t]\n\t}\n}\n```\n\n* [Document](https://en.wikipedia.org/wiki/JSON)\n* [Sample 1](https://www.dropbox.com/s/yvevoyb8559nytb/100.json?dl=0) (100 Vertices , 26KB)\n* [Sample 2](https://www.dropbox.com/s/f6kljlch7p2rfhy/1000.json?dl=0) (1000 Vertices , 494KB)\n\n### YAML\n```\n \tgraph:\n \t\tedges:\n \t\t- source: head_1\n \t  \ttarget: tail_1\n \t  \tweight: weight_1\n \t\n \t\t.\n \t\t.\n \t\t.\n\n \t\t- source: head_n\n \t  \ttarget: tail_n\n \t  \tweight: weight_n\n \t\t\t\t\t\n \t\tnodes:\n \t\t- id: 1\n\n \t\t.\n \t\t.\n \t\t.\n\n \t\t- id: n\n \tproperties:\n \t\tdirected: true\n \t\tmultigraph: true\n \t\tself_loop: true\n \t\tsigned: true\n \t\tweighted: true\n```\n\n* [Document](https://en.wikipedia.org/wiki/YAML)\n* [Sample 1](https://www.dropbox.com/s/9seljohtoqjzjzy/30.yaml?dl=0) (30 Vertices , 6KB)\n* [Sample 2](https://www.dropbox.com/s/wtfh38rgmn29npi/100.yaml?dl=0) (100 Vertices , 35KB)\n\n### Weighted Edge List\t\n```\n\t\u003chead_1\u003e \u003ctail_1\u003e \u003cweight_1\u003e\n\t\t\n\t.\n\t.\n\t.\n\t\t\n\t\u003chead_n\u003e \u003ctail_n\u003e \u003cweight_n\u003e\t\n```\n\n* [Document](http://www.cs.cmu.edu/~pbbs/benchmarks/graphIO.html)\n* [Sample 1](https://www.dropbox.com/s/moie1xb2wj90y33/100.wel?dl=0) (100 Vertices , 5KB)\n* [Sample 2](https://www.dropbox.com/s/h6pohl60okhdnt7/1000.wel?dl=0) (1000 Vertices , 192KB)\n\n### ASP\n\n```\n\tnode(1).\n\t.\n\t.\n\t.\n\tnode(n).\n\tedge(head_1,tail_1,weight_1).\n\t.\n\t.\n\t.\n\tedge(head_n,tail_n,weight_n).\n```\n\n* [Document](https://www.mat.unical.it/aspcomp2013/MaximalClique)\n* [Sample 1](https://www.dropbox.com/s/4bufa1m4uamv48z/100.lp?dl=0) (100 Vertices , 7KB)\n* [Sample 2](https://www.dropbox.com/s/w79fh1qva64namw/1000.lp?dl=0) (1000 Vertices , 76KB)\n\n### Trivial Graph Format\n\n```\n\t1\n\t.\n\t.\n\t.\n\tn\n\t#\n\t1 2 weight_1\n\t.\n\t.\n\t.\n\tn k weight_n\n```\n* [Document](https://en.wikipedia.org/wiki/Trivial_Graph_Format)\n* [Sample 1](https://www.dropbox.com/s/tehb6f3gz2o5v9c/100.tgf?dl=0) (100 Vertices , 4KB)\n* [Sample 2](https://www.dropbox.com/s/9mjeq4w973189cc/1000.tgf?dl=0) (1000 Vertices , 61KB)\n\n### UCINET DL Format\n\n```\n\tdl\n\tformat=edgelist1\n\tn=\u003cnumber of vertices\u003e\n\tdata:\n\t1 2 weight_1\n\t.\n\t.\n\t.\n\tn k weight_n\t\n```\n* [Document](https://sites.google.com/site/ucinetsoftware/home)\n* [Sample 1](https://www.dropbox.com/s/82wrl86uowwjud2/100.dl?dl=0) (100 Vertices , 8KB)\n* [Sample 2](https://www.dropbox.com/s/kbzbsy47uvfqdsi/1000.dl?dl=0) (1000 Vertices , 729KB)\n\n### Matrix Market\n\n```\n    %%MatrixMarket matrix coordinate real general\n    \u003cnumber of vertices\u003e  \u003cnumber of vertices\u003e  \u003cnumber of edges\u003e\n    \u003chead_1\u003e    \u003ctail_1\u003e    \u003cweight_1\u003e \n    .\n    .\n    .\n    \u003chead_n\u003e    \u003ctail_n\u003e    \u003cweight_n\u003e \n```\n* [Document](https://math.nist.gov/MatrixMarket/formats.html)\n* [Sample 1](https://www.dropbox.com/s/ztw3vg0roups82q/100.mtx?dl=0) (100 Vertices , 59KB)\n* [Sample 2](https://www.dropbox.com/s/skjjvbbzrpvryl4/1000.mtx?dl=0) (1000 Vertices , 1.8MB)\n\n### Graph Line\n```\n\t\u003chead_1\u003e \u003ctail_1\u003e:\u003cweight_1\u003e \u003ctail_2\u003e:\u003cweight_2\u003e  ... \u003ctail_n\u003e:\u003cweight_n\u003e\n\t\u003chead_2\u003e \u003ctail_1\u003e:\u003cweight_1\u003e \u003ctail_2\u003e:\u003cweight_2\u003e  ... \u003ctail_n\u003e:\u003cweight_n\u003e\n\t.\n\t.\n\t.\n\t\u003chead_n\u003e \u003ctail_1\u003e:\u003cweight_1\u003e \u003ctail_2\u003e:\u003cweight_2\u003e  ... \u003ctail_n\u003e:\u003cweight_n\u003e\n```\n\n* [Sample 1](https://www.dropbox.com/s/obmmb5nw1lca9z3/100.gl?dl=0) (100 Vertices , 17KB)\n* [Sample 2](https://www.dropbox.com/s/intufsbudnmfv8m/1000.gl?dl=0) (1000 Vertices , 2.4MB)\n\n### GDF\n\n```\n    nodedef\u003ename VARCHAR,label VARCHAR\n    node_1,node_1_label\n    node_2,node_2_label\n    .\n    .\n    .\n    node_n,node_n_label\n    edgedef\u003enode1 VARCHAR,node2 VARCHAR, weight DOUBLE\n    node_1,node_2,weight_1\n    node_1,node_3,weight_2\n    .\n    .\n    .\n    node_n,node_2,weight_n \n```\n\n* [Sample 1](https://www.dropbox.com/s/7dqox0f8e1f859s/100.gdf?dl=0) (100 Vertices , 21KB)\n* [Sample 2](https://www.dropbox.com/s/xabjzpp0p5sr4b9/1000.gdf?dl=0) (1000 Vertices , 690KB)\n\n### GML\n\n```\n    graph\n    [\n      multigraph 0\n      directed  0\n      node\n      [\n       id 1\n       label \"Node 1\"\n      ]\n      node\n      [\n       id 2\n       label \"Node 2\"\n      ]\n      .\n      .\n      .\n      node\n      [\n       id n\n       label \"Node n\"\n      ]\n      edge\n      [\n       source 1\n       target 2\n       value W1\n      ]\n      edge\n      [\n       source 2\n       target 4\n       value W2\n      ]\n      .\n      .\n      .\n      edge\n      [\n       source n\n       target r\n       value Wn\n      ]\n    ]\n\n```\n\n* [Document](https://en.wikipedia.org/wiki/Graph_Modelling_Language)\n* [Sample 1](https://www.dropbox.com/s/g9uvywn1fwt9aq7/100.gml?dl=0) (100 Vertices , 120KB)\n* [Sample 2](https://www.dropbox.com/s/5gt5udezy56mlz9/1000.gml?dl=0) (1000 Vertices , 2.4MB)\n\n### GEXF\n\n```\n     \u003c?xml version=\"1.0\" encoding=\"UTF-8\"?\u003e\n     \u003cgexf xmlns=\"http://www.gexf.net/1.2draft\" version=\"1.2\"\u003e\n         \u003cmeta lastmodifieddate=\"2009-03-20\"\u003e\n             \u003ccreator\u003ePyRGG\u003c/creator\u003e\n             \u003cdescription\u003eFile Name\u003c/description\u003e\n         \u003c/meta\u003e\n         \u003cgraph defaultedgetype=\"directed\"\u003e\n             \u003cnodes\u003e\n                 \u003cnode id=\"1\" label=\"Node 1\" /\u003e\n                 \u003cnode id=\"2\" label=\"Node 2\" /\u003e\n                 ...\n             \u003c/nodes\u003e\n             \u003cedges\u003e\n                 \u003cedge id=\"1\" source=\"1\" target=\"2\" weight=\"400\" /\u003e\n                 ...\n             \u003c/edges\u003e\n         \u003c/graph\u003e\n     \u003c/gexf\u003e\n```\n\n* [Document](https://github.com/gephi/gexf/wiki/Basic-Concepts#network-topology)\n* [Sample 1](https://www.dropbox.com/s/kgx8xl9j0dpk4us/100.gexf?dl=0) (100 Vertices , 63KB)\n* [Sample 2](https://www.dropbox.com/s/7a380kf35buvusr/1000.gexf?dl=0) (1000 Vertices , 6.4MB)\n\n### Graphviz\n\n```\n\tgraph example \n\t\t{\n\t\tnode1 -- node2 [weight=W1];\n\t\tnode3 -- node4 [weight=W2];\n\t\tnode1 -- node3 [weight=W3];\n\t\t.\n\t\t.\n\t\t.\n\t\t}\n```\n\n* [Document](https://graphviz.org/doc/info/lang.html)\n* [Sample 1](https://www.dropbox.com/s/ukev1hi4kguomri/100.gv?dl=0) (100 Vertices , 11KB)\n* [Sample 2](https://www.dropbox.com/s/vpvvliz96mdea1p/1000.gv?dl=0) (1000 Vertices , 106KB)\n* [Online Visualization](https://dreampuf.github.io/GraphvizOnline/)\n\n### Pickle\n\n⚠️ Binary format\n\n* [Document](https://docs.python.org/3.10/library/pickle.html)\n* [Sample 1](https://www.dropbox.com/s/4s8zt9i13z39gts/100.p?dl=0) (100 Vertices , 12KB)\n* [Sample 2](https://www.dropbox.com/s/fzurqu5au0p1b54/1000.p?dl=0) (1000 Vertices , 340KB)\n\n\n## Issues \u0026 Bug Reports\t\t\t\n\nJust fill an issue and describe it. We'll check it ASAP!\t\t\t\t\t\t\t\nor send an email to [info@pyrgg.site](mailto:info@pyrgg.site \"info@pyrgg.site\"). \n\nYou can also join our discord server\t\t\t\n\n\u003ca href=\"https://discord.gg/dfYAWVMaCW\"\u003e\n  \u003cimg src=\"https://img.shields.io/discord/1013411447130308669.svg?style=for-the-badge\" alt=\"Discord Channel\"\u003e\n\u003c/a\u003e\n\n\n## Citing\n\nIf you use PyRGG in your research, please cite the [JOSS paper](http://joss.theoj.org/papers/da33f691984d9a35f66ff93a391bbc26 \"PyRGG JOSS Paper\") ;-)\n\n\u003cpre\u003e\n@article{Haghighi2017,\n  doi = {10.21105/joss.00331},\n  url = {https://doi.org/10.21105/joss.00331},\n  year  = {2017},\n  month = {sep},\n  publisher = {The Open Journal},\n  volume = {2},\n  number = {17},\n  author = {Sepand Haghighi},\n  title = {Pyrgg: Python Random Graph Generator},\n  journal = {The Journal of Open Source Software}\n}\n\u003c/pre\u003e\n\n\u003ctable\u003e\n\t\u003ctr\u003e \n\t\t\u003ctd align=\"center\"\u003eJOSS\u003c/td\u003e\n\t\t\u003ctd align=\"center\"\u003e\u003ca href=\"http://joss.theoj.org/papers/da33f691984d9a35f66ff93a391bbc26\"\u003e\u003cimg src=\"http://joss.theoj.org/papers/da33f691984d9a35f66ff93a391bbc26/status.svg\"\u003e\u003c/a\u003e\u003c/td\u003e\t\n\t\u003c/tr\u003e\n\t\u003ctr\u003e\n\t\t\u003ctd align=\"center\"\u003eZenodo\u003c/td\u003e\n\t\t\u003ctd align=\"center\"\u003e\u003ca href=\"https://zenodo.org/badge/latestdoi/89410101\"\u003e\u003cimg src=\"https://zenodo.org/badge/89410101.svg\" alt=\"DOI\"\u003e\u003c/a\u003e\u003c/td\u003e\n\t\u003c/tr\u003e\n\u003c/table\u003e\n \t\t\t\n\n## References\n\t\t\t\t\t\n\n\u003cblockquote\u003e1- \u003ca href=\"http://www.diag.uniroma1.it/challenge9/format.shtml\"\u003e9th DIMACS Implementation Challenge - Shortest Paths\u003c/a\u003e \u003c/blockquote\u003e\n\n\u003cblockquote\u003e2- \u003ca href=\"http://www.cs.cmu.edu/~pbbs/benchmarks/graphIO.html\"\u003eProblem Based Benchmark Suite\u003c/a\u003e\u003c/blockquote\u003e\n\n\u003cblockquote\u003e3- \u003ca href=\"https://www.mat.unical.it/aspcomp2013/MaximalClique\"\u003eMaximalClique - ASP Competition 2013\u003c/a\u003e\u003c/blockquote\u003e\n\n\u003cblockquote\u003e4- Pitas, Ioannis, ed. Graph-based social media analysis. Vol. 39. CRC Press, 2016. \u003c/blockquote\u003e\t\n\n\u003cblockquote\u003e5- Roughan, Matthew, and Jonathan Tuke. \"The hitchhikers guide to sharing graph data.\" 2015 3rd International Conference on Future Internet of Things and Cloud. IEEE, 2015. \u003c/blockquote\u003e\t\n\n\u003cblockquote\u003e6- Borgatti, Stephen P., Martin G. Everett, and Linton C. Freeman. \"Ucinet for Windows: Software for social network analysis.\" Harvard, MA: analytic technologies 6 (2002). \u003c/blockquote\u003e\n\n\u003cblockquote\u003e7- \u003ca href=\"https://math.nist.gov/MatrixMarket/formats.html\"\u003eMatrix Market: File Formats\u003c/a\u003e \u003c/blockquote\u003e\t\t\n\n\u003cblockquote\u003e8- \u003ca href=\"https://socnetv.org/docs/formats.html#GML\"\u003eSocial Network Visualizer\u003c/a\u003e \u003c/blockquote\u003e\n\n\u003cblockquote\u003e9- Adar, Eytan. \"GUESS: a language and interface for graph exploration.\" Proceedings of the SIGCHI conference on Human Factors in computing systems. 2006. \u003c/blockquote\u003e\n\n\u003cblockquote\u003e10- Skiena, Steven S. The algorithm design manual. Springer International Publishing, 2020. \u003c/blockquote\u003e\n\n\u003cblockquote\u003e11- Chakrabarti, Deepayan, Yiping Zhan, and Christos Faloutsos. \"R-MAT: A recursive model for graph mining.\" Proceedings of the 2004 SIAM International Conference on Data Mining. Society for Industrial and Applied Mathematics, 2004. \u003c/blockquote\u003e\n\n\u003cblockquote\u003e12- Zhong, Jianlong, and Bingsheng He. \"An overview of medusa: simplified graph processing on gpus.\" ACM SIGPLAN Notices 47.8 (2012): 283-284.\u003c/blockquote\u003e\n\n\u003cblockquote\u003e13- Ellson, John, et al. \"Graphviz and dynagraph—static and dynamic graph drawing tools.\" Graph drawing software. Springer, Berlin, Heidelberg, 2004. 127-148.\u003c/blockquote\u003e\n\n\u003cblockquote\u003e14- Gilbert, Edgar N. \"Random graphs.\" The Annals of Mathematical Statistics 30.4 (1959): 1141-1144.\u003c/blockquote\u003e\n\n\u003cblockquote\u003e15- Erdős, Paul, and Alfréd Rényi. \"On the strength of connectedness of a random graph.\" Acta Mathematica Hungarica 12.1 (1961): 261-267.\u003c/blockquote\u003e\n\t\t\t\t\t\n \n## Show Your Support\n\t\t\t\t\t\t\t\t\n\u003ch3\u003eStar This Repo\u003c/h3\u003e\t\t\t\t\t\n\nGive a ⭐️ if this project helped you!\n\n\u003ch3\u003eDonate to Our Project\u003c/h3\u003e\t\n\nIf you do like our project and we hope that you do, can you please support us? Our project is not and is never going to be working for profit. We need the money just so we can continue doing what we do ;-) .\t\t\t\n\n\u003ca href=\"http://www.pyrgg.site/donate.html\" target=\"_blank\"\u003e\u003cimg src=\"https://github.com/sepandhaghighi/pyrgg/raw/master/otherfile/donate-button.png\" height=\"90px\" width=\"270px\" alt=\"PyRGG Donation\"\u003e\u003c/a\u003e\n\n","project_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fsepandhaghighi%2Fpyrgg","html_url":"https://awesome.ecosyste.ms/projects/github.com%2Fsepandhaghighi%2Fpyrgg","lists_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fsepandhaghighi%2Fpyrgg/lists"}