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Version](https://img.shields.io/pypi/pyversions/graphistry.svg)](https://pypi.python.org/pypi/graphistry)\n[![License](https://img.shields.io/pypi/l/graphistry.svg)](https://pypi.python.org/pypi/graphistry)\n![PyPI - Downloads](https://img.shields.io/pypi/dm/graphistry)\n\n[![Uptime Robot status](https://img.shields.io/uptimerobot/status/m787548531-e9c7b7508fc76fea927e2313?label=hub.graphistry.com)](https://status.graphistry.com/) [\u003cimg src=\"https://img.shields.io/badge/slack-Graphistry%20chat-orange.svg?logo=slack\"\u003e](https://join.slack.com/t/graphistry-community/shared_invite/zt-53ik36w2-fpP0Ibjbk7IJuVFIRSnr6g)\n[![Twitter Follow](https://img.shields.io/twitter/follow/graphistry)](https://twitter.com/graphistry)\n\n\u003ctable style=\"width:100%;\"\u003e\n  \u003ctr valign=\"top\"\u003e\n    \u003ctd align=\"center\"\u003e\u003ca href=\"https://hub.graphistry.com/graph/graph.html?dataset=Facebook\u0026splashAfter=true\" target=\"_blank\"\u003e\u003cimg src=\"https://i.imgur.com/z8SIh2E.png\" title=\"Click to open.\"\u003e\u003c/a\u003e\n    \u003ca href=\"https://hub.graphistry.com/graph/graph.html?dataset=Facebook\u0026splashAfter=true\" target=\"_blank\"\u003eDemo: Interactive visualization of 80,000+ Facebook friendships\u003c/a\u003e (\u003ca href=\"http://snap.stanford.edu\" target=\"_blank\"\u003esource data\u003c/a\u003e\u003c/em\u003e)\n    \u003c/td\u003e\n  \u003c/tr\u003e\n\u003c/table\u003e\n\nPyGraphistry is an open source Python library for data scientists and developers to leverage the power of graph visualization, analytics, AI, including with native GPU acceleration:\n\n* [**Python dataframe-native graph processing:**](https://pygraphistry.readthedocs.io/en/latest/10min.html) Quickly ingest \u0026 prepare data in many formats, shapes, and scales as graphs. Use tools like Pandas, Spark, [RAPIDS (GPU)](https://www.rapids.ai), and [Apache Arrow](https://arrow.apache.org/).\n\n* [**Integrations:**](https://pygraphistry.readthedocs.io/en/latest/plugins.html) Connect to graph databases, data platforms, Python tools, and more.\n\n  | Category | Connector Tutorials |\n  |----------|---------------------|\n  | **Data Platforms, SQL \u0026 Logs** | [![Databricks](https://img.shields.io/badge/Databricks-FF3621?style=flat\u0026logo=databricks\u0026logoColor=white)](https://pygraphistry.readthedocs.io/en/latest/demos/demos_databases_apis/databricks_pyspark/graphistry-notebook-dashboard.html) [![Splunk](https://img.shields.io/badge/Splunk-000000?style=flat\u0026logo=splunk\u0026logoColor=white)](https://pygraphistry.readthedocs.io/en/latest/demos/demos_databases_apis/splunk/splunk_demo_public.html) [![PostgreSQL](https://img.shields.io/badge/PostgreSQL-4169E1?style=flat\u0026logo=postgresql\u0026logoColor=white)](https://pygraphistry.readthedocs.io/en/latest/demos/demos_databases_apis/sql/postgres.html) [![Azure Data Explorer (Kusto)](https://img.shields.io/badge/Azure_Data_Explorer_(Kusto)-0078D4?style=flat\u0026logo=microsoftazure\u0026logoColor=white)](https://pygraphistry.readthedocs.io/en/latest/demos/demos_databases_apis/microsoft/kusto/graphistry_ADX_kusto_demo.html) [![Google Cloud Spanner](https://img.shields.io/badge/Google_Cloud_Spanner-4285F4?style=flat\u0026logo=googlecloud\u0026logoColor=white)](https://pygraphistry.readthedocs.io/en/latest/demos/demos_databases_apis/spanner/google_spanner_finance_graph.html) |\n  | **Graph Databases** | [![Neo4j](https://img.shields.io/badge/Neo4j-4581C3?style=flat\u0026logo=neo4j\u0026logoColor=white)](https://pygraphistry.readthedocs.io/en/latest/demos/demos_databases_apis/neo4j/official/graphistry_bolt_tutorial_public.html) [![Amazon Neptune](https://img.shields.io/badge/Amazon_Neptune-FF9900?style=flat\u0026logo=amazonaws\u0026logoColor=white)](https://pygraphistry.readthedocs.io/en/latest/demos/demos_databases_apis/neptune/neptune_cypher_viz_using_bolt.html) [![TigerGraph](https://img.shields.io/badge/TigerGraph-FF6600?style=flat)](https://pygraphistry.readthedocs.io/en/latest/demos/demos_databases_apis/tigergraph/tigergraph_pygraphistry_bindings.html) [![ArangoDB](https://img.shields.io/badge/ArangoDB-DDE072?style=flat\u0026logo=arangodb\u0026logoColor=black)](https://pygraphistry.readthedocs.io/en/latest/demos/demos_databases_apis/arango/arango_tutorial.html) [![Memgraph](https://img.shields.io/badge/Memgraph-DD2222?style=flat)](https://pygraphistry.readthedocs.io/en/latest/demos/demos_databases_apis/memgraph/visualizing_iam_dataset.html) |\n  | **Python Tools \u0026 Libraries** | [![CSV](https://img.shields.io/badge/CSV-217346?style=flat\u0026logo=microsoftexcel\u0026logoColor=white)](https://pygraphistry.readthedocs.io/en/latest/demos/upload_csv_miniapp.html) [![Pandas](https://img.shields.io/badge/Pandas-150458?style=flat\u0026logo=pandas\u0026logoColor=white)](https://pygraphistry.readthedocs.io/en/latest/demos/demos_databases_apis/gpu_rapids/part_i_cpu_pandas.html) [![Apache Arrow](https://img.shields.io/badge/Apache_Arrow-000000?style=flat\u0026logo=apachearrow\u0026logoColor=white)](https://pygraphistry.readthedocs.io/en/latest/performance.html) [![NVIDIA RAPIDS](https://img.shields.io/badge/NVIDIA_RAPIDS-76B900?style=flat\u0026logo=nvidia\u0026logoColor=white)](https://pygraphistry.readthedocs.io/en/latest/demos/demos_databases_apis/gpu_rapids/cugraph.html) [![NetworkX](https://img.shields.io/badge/NetworkX-013243?style=flat)](https://pygraphistry.readthedocs.io/en/latest/demos/demos_databases_apis/networkx/networkx.html) [![Graphviz](https://img.shields.io/badge/Graphviz-2A2A2A?style=flat\u0026logo=graphviz\u0026logoColor=white)](https://pygraphistry.readthedocs.io/en/latest/demos/demos_databases_apis/graphviz/graphviz.html) |\n\n  *[View all connectors →](https://pygraphistry.readthedocs.io/en/latest/notebooks/plugins.connectors.html)*\n\n* [**Prototype locally and deploy remotely:**](https://www.graphistry.com/get-started) Prototype from notebooks like Jupyter and Databricks using local CPUs \u0026 GPUs, and then power production dashboards \u0026 pipelines with Graphistry Hub and your own self-hosted servers.\n\n* [**Query graphs with GFQL:**](https://pygraphistry.readthedocs.io/en/latest/gfql/index.html) Use GFQL, the first dataframe-native graph query language, to ask relationship questions that are difficult for tabular tools and without requiring a database.\n\n* [**graphistry[ai]:**](https://pygraphistry.readthedocs.io/en/latest/gfql/combo.html#) Call streamlined graph ML \u0026 AI methods to benefit from clustering, UMAP embeddings, graph neural networks, automatic feature engineering, and more.\n\n* [**Visualize \u0026 explore large graphs:**](https://pygraphistry.readthedocs.io/en/latest/visualization/10min.html#) In just a few minutes, create stunning interactive visualizations with millions of edges and many point-and-click built-ins like drilldowns, timebars, and filtering. When ready, customize with Python, JavaScript, and REST APIs.\n\n* [**Columnar \u0026 GPU acceleration:**](https://pygraphistry.readthedocs.io/en/latest/performance.html) CPU-mode ingestion and wrangling is fast due to native use of Apache Arrow and columnar analytics, and the optional RAPIDS-based GPU mode delivers 100X+ speedups.\n\nFrom global 10 banks, manufacturers, news agencies, and government agencies, to startups, game companies, scientists, biotechs, and NGOs, many teams are tackling their graph workloads with Graphistry.\n\n## Gallery\n\nThe [notebook demo gallery](https://pygraphistry.readthedocs.io/en/latest/demos/for_analysis.html) shares many more live visualizations, demos, and integration examples\n\n\u003ctable\u003e\n    \u003ctr valign=\"top\"\u003e\n        \u003ctd width=\"33%\" align=\"center\"\u003e\u003ca href=\"https://hub.graphistry.com/graph/graph.html?dataset=Twitter\u0026splashAfter=true\" target=\"_blank\"\u003eTwitter Botnet\u003cbr\u003e\u003cimg width=\"266\" src=\"https://i.imgur.com/qm5MCqS.jpg\"\u003e\u003c/a\u003e\u003c/td\u003e\n        \u003ctd width=\"33%\" align=\"center\"\u003eEdit Wars on Wikipedia\u003cbr\u003e\u003ca href=\"https://i.imgur.com/074zFve.png\" target=\"_blank\"\u003e\u003cimg width=\"266\" src=\"https://i.imgur.com/074zFve.png\"\u003e\u003c/a\u003e\u003cem\u003e(\u003ca href=\"https://snap.stanford.edu\" target=\"_blank\"\u003edata\u003c/a\u003e\u003c/em\u003e)\u003c/td\u003e\n        \u003ctd width=\"33%\" align=\"center\"\u003e\u003ca href=\"https://hub.graphistry.com/graph/graph.html?dataset=bitC\u0026splashAfter=true\" target=\"_blank\"\u003e100,000 Bitcoin Transactions\u003cbr\u003e\u003cimg width=\"266\" height=\"266\" src=\"https://i.imgur.com/axIkjfd.png\"\u003e\u003c/a\u003e\u003c/td\u003e\n    \u003c/tr\u003e\n    \u003ctr valign=\"top\"\u003e\n        \u003ctd width=\"33%\" align=\"center\"\u003ePort Scan Attack\u003cbr\u003e\u003ca href=\"http://i.imgur.com/vKUDySw.png\" target=\"_blank\"\u003e\u003cimg width=\"266\" src=\"http://i.imgur.com/vKUDySw.png\"\u003e\u003c/a\u003e\u003c/td\u003e\n        \u003ctd width=\"33%\" align=\"center\"\u003e\u003ca href=\"http://hub.graphistry.com/graph/graph.html?dataset=PyGraphistry/M9RL4PQFSF\u0026usertag=github\u0026info=true\u0026static=true\u0026contentKey=Biogrid_Github_Demo\u0026play=3000\u0026center=false\u0026menu=true\u0026goLive=false\u0026left=-2.58e+4\u0026right=4.35e+4\u0026top=-1.72e+4\u0026bottom=2.16e+4\u0026legend={%22title%22:%22%3Ch3%3EBioGRID%20Repository%20of%20Protein%20Interactions%3C/h3%3E%22,%22subtitle%22:%22%3Cp%3EEach%20color%20represents%20an%20organism.%20Humans%20are%20in%20light%20blue.%3C/p%3E%22,%22nodes%22:%22Proteins/Genes%22,%22edges%22:%22Interactions%20reported%20in%20scientific%20publications%22}\" target=\"_blank\"\u003eProtein Interactions \u003cbr\u003e\u003cimg width=\"266\" src=\"http://i.imgur.com/nrUHLFz.png\" target=\"_blank\"\u003e\u003c/a\u003e\u003cem\u003e(\u003ca href=\"http://thebiogrid.org\" target=\"_blank\"\u003edata\u003c/a\u003e)\u003c/em\u003e\u003c/td\u003e\n        \u003ctd width=\"33%\" align=\"center\"\u003e\u003ca href=\"http://hub.graphistry.com/graph/graph.html?\u0026dataset=PyGraphistry/PC7D53HHS5\u0026info=true\u0026static=true\u0026contentKey=SocioPlt_Github_Demo\u0026play=3000\u0026center=false\u0026menu=true\u0026goLive=false\u0026left=-236\u0026right=265\u0026top=-145\u0026bottom=134\u0026usertag=github\u0026legend=%7B%22nodes%22%3A%20%22%3Cspan%20style%3D%5C%22color%3A%23a6cee3%3B%5C%22%3ELanguages%3C/span%3E%20/%20%3Cspan%20style%3D%5C%22color%3Argb%28106%2C%2061%2C%20154%29%3B%5C%22%3EStatements%3C/span%3E%22%2C%20%22edges%22%3A%20%22Strong%20Correlations%22%2C%20%22subtitle%22%3A%20%22%3Cp%3EFor%20more%20information%2C%20check%20out%20the%20%3Ca%20target%3D%5C%22_blank%5C%22%20href%3D%5C%22https%3A//lmeyerov.github.io/projects/socioplt/viz/index.html%5C%22%3ESocio-PLT%3C/a%3E%20project.%20Make%20your%20own%20visualizations%20with%20%3Ca%20target%3D%5C%22_blank%5C%22%20href%3D%5C%22https%3A//github.com/graphistry/pygraphistry%5C%22%3EPyGraphistry%3C/a%3E.%3C/p%3E%22%2C%20%22title%22%3A%20%22%3Ch3%3ECorrelation%20Between%20Statements%20about%20Programming%20Languages%3C/h3%3E%22%7D\" target=\"_blank\"\u003eProgramming Languages\u003cbr\u003e\u003cimg width=\"266\" src=\"http://i.imgur.com/0T0EKmD.png\"\u003e\u003c/a\u003e\u003cem\u003e(\u003ca href=\"http://lmeyerov.github.io/projects/socioplt/viz/index.html\" target=\"_blank\"\u003edata\u003c/a\u003e)\u003c/em\u003e\u003c/td\u003e\n    \u003c/tr\u003e\n\u003c/table\u003e\n\n## Install\n\nCommon configurations:\n\n* **Minimal core**\n\n  Includes: The GFQL dataframe-native graph query language, built-in layouts, Graphistry visualization server client\n\n  ```python\n  pip install graphistry\n  ```\n\n  Does not include `graphistry[ai]`, plugins\n\n* **No dependencies and user-level**\n\n  ```python\n  pip install --no-deps --user graphistry\n  ```\n\n* **GPU acceleration** - Optional\n\n  Local GPU: Install [RAPIDS](https://www.rapids.ai) and/or deploy a GPU-ready [Graphistry server](https://www.graphistry.com/get-started)\n  \n  Remote GPU: Use the [remote endpoints](https://www.graphistry.com/blog/graphistry-2-41-3).\n\nFor further options, see the [installation guides](https://pygraphistry.readthedocs.io/en/latest/install/index.html)\n\n## Visualization quickstart\n\nQuickly go from raw data to a styled and interactive Graphistry graph visualization:\n\n```python\nimport graphistry\nimport pandas as pd\n\n# Raw data as Pandas CPU dataframes, cuDF GPU dataframes, Spark, ...\ndf = pd.DataFrame({\n    'src': ['Alice', 'Bob', 'Carol'],\n    'dst': ['Bob', 'Carol', 'Alice'],\n    'friendship': [0.3, 0.95, 0.8]\n})\n\n# Bind\ng1 = graphistry.edges(df, 'src', 'dst')\n\n# Override styling defaults\ng1_styled = g1.encode_edge_color('friendship', ['blue', 'red'], as_continuous=True)\n\n# Connect: Free GPU accounts and self-hosting @ graphistry.com/get-started\ngraphistry.register(api=3, username='your_username', password='your_password')\n\n# Upload for GPU server visualization session\ng1_styled.plot()\n```\n\nExplore [10 Minutes to Graphistry Visualization](https://pygraphistry.readthedocs.io/en/latest/visualization/10min.html) for more visualization examples and options\n\n## PyGraphistry[AI] \u0026 GFQL quickstart - CPU \u0026 GPU\n\n**CPU graph pipeline** combining graph ML, AI, mining, and visualization:\n\n```python\nfrom graphistry import n, e, e_forward, e_reverse\n\n# Graph analytics\ng2 = g1.compute_igraph('pagerank')\nassert 'pagerank' in g2._nodes.columns\n\n# Graph ML/AI\ng3 = g2.umap()\nassert ('x' in g3._nodes.columns) and ('y' in g3._nodes.columns)\n\n# Graph querying with GFQL\ng4 = g3.chain([\n    n(query='pagerank \u003e 0.1'), e_forward(), n(query='pagerank \u003e 0.1')\n])\nassert (g4._nodes.pagerank \u003e 0.1).all()\n\n# Upload for GPU server visualization session\ng4.plot()\n```\n\nThe **automatic GPU modes** require almost no code changes:\n\n```python\nimport cudf\nfrom graphistry import n, e, e_forward, e_reverse\n\n# Modified -- Rebind data as a GPU dataframe and swap in a GPU plugin call\ng1_gpu = g1.edges(cudf.from_pandas(df))\ng2 = g1_gpu.compute_cugraph('pagerank')\n\n# Unmodified -- Automatic GPU mode for all ML, AI, GFQL queries, \u0026 visualization APIs\ng3 = g2.umap()\ng4 = g3.chain([\n    n(query='pagerank \u003e 0.1'), e_forward(), n(query='pagerank \u003e 0.1')\n])\ng4.plot()\n```\n\nExplore [10 Minutes to PyGraphistry](https://pygraphistry.readthedocs.io/en/latest/10min.html) for a wider variety of graph processing.\n\n## PyGraphistry documentation\n\n* [Main PyGraphistry documentation](https://pygraphistry.readthedocs.io/en/latest/)\n* 10 Minutes to: [PyGraphistry](https://pygraphistry.readthedocs.io/en/latest/10min.html), [Visualization](https://pygraphistry.readthedocs.io/en/latest/visualization/10min.html), [GFQL](https://pygraphistry.readthedocs.io/en/latest/gfql/about.html)\n* Get started: [Install](https://pygraphistry.readthedocs.io/en/latest/install/index.html), [UI Guide](https://hub.graphistry.com/docs/ui/index/), [Notebooks](https://pygraphistry.readthedocs.io/en/latest/demos/for_analysis.html)\n* Performance: [PyGraphistry CPU+GPU](https://pygraphistry.readthedocs.io/en/latest/performance.html) \u0026 [GFQL CPU+GPU](https://pygraphistry.readthedocs.io/en/latest/gfql/performance.html)\n* API References\n  * [PyGraphistry API Reference](https://pygraphistry.readthedocs.io/en/latest/api/index.html): [Visualization \u0026 Compute](https://pygraphistry.readthedocs.io/en/latest/visualization/index.html), [PyGraphistry Cheatsheet](https://pygraphistry.readthedocs.io/en/latest/cheatsheet.html)\n  * [GFQL Documentation](https://pygraphistry.readthedocs.io/en/latest/gfql/index.html):  [GFQL Cheatsheet](https://pygraphistry.readthedocs.io/en/latest/gfql/quick.html) and [GFQL Operator Cheatsheet](https://pygraphistry.readthedocs.io/en/latest/gfql/predicates/quick.html)\n  * [Plugins](https://pygraphistry.readthedocs.io/en/latest/plugins.html): Databricks, Splunk, Neptune, Neo4j, RAPIDS, and more\n  * Web: [iframe](https://hub.graphistry.com/docs/api/1/rest/url/#urloptions),  [JavaScript](https://hub.graphistry.com/static/js-docs/index.html?path=/docs/introduction--docs), [REST](https://hub.graphistry.com/docs/api/1/rest/auth/)\n\n## Graphistry ecosystem\n\n* **Graphistry server:**\n  * Launch - [Graphistry Hub, Graphistry cloud marketplaces, and self-hosting](https://www.graphistry.com/get-started)\n  * Self-hosting: [Administration (including Docker)](https://github.com/graphistry/graphistry-cli) \u0026 [Kubernetes](https://github.com/graphistry/graphistry-helm)\n\n* **Graphistry client APIs:**\n  * Web: [iframe](https://hub.graphistry.com/docs/api/1/rest/url/#urloptions), [JavaScript](https://hub.graphistry.com/static/js-docs/index.html?path=/docs/introduction--docs), [REST](https://hub.graphistry.com/docs/api/1/rest/auth/)\n  * [PyGraphistry](https://pygraphistry.readthedocs.io/en/latest/index.html)\n  * [Graphistry for Microsoft PowerBI](https://hub.graphistry.com/docs/powerbi/pbi/)\n\n* **Additional projects**:\n  * [Louie.ai](https://louie.ai/): GenAI-native notebooks \u0026 dashboards to talk to your databases \u0026 Graphistry\n  * [graph-app-kit](https://github.com/graphistry/graph-app-kit): Streamlit Python dashboards with batteries-include graph packages\n  * [cu-cat](https://chat.openai.com/chat): Automatic GPU feature engineering\n\n## Community and support\n\n* [Blog](https://www.graphistry.com/blog) for tutorials, case studies, and updates\n* [Slack](https://join.slack.com/t/graphistry-community/shared_invite/zt-53ik36w2-fpP0Ibjbk7IJuVFIRSnr6g): Join the Graphistry Community Slack for discussions and support\n* [Twitter](https://twitter.com/graphistry) \u0026 [LinkedIn](https://www.linkedin.com/company/graphistry): Follow for updates\n* [GitHub Issues](https://github.com/graphistry/pygraphistry/issues) open source support\n* [Graphistry ZenDesk](https://graphistry.zendesk.com/) dedicated enterprise support\n\n## Contribute\n\nSee [CONTRIBUTING](https://pygraphistry.readthedocs.io/en/latest/CONTRIBUTING.html) and [DEVELOP](https://pygraphistry.readthedocs.io/en/latest/DEVELOP.html) for participating in PyGraphistry development, or reach out to our team\n","project_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fgraphistry%2Fpygraphistry","html_url":"https://awesome.ecosyste.ms/projects/github.com%2Fgraphistry%2Fpygraphistry","lists_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fgraphistry%2Fpygraphistry/lists"}