{"id":15159734,"url":"https://github.com/streamlit/arrow-js","last_synced_at":"2025-09-30T10:30:54.723Z","repository":{"id":74322102,"uuid":"387279397","full_name":"streamlit/arrow-js","owner":"streamlit","description":"A fork of `apache-arrow@3.0.0` that fixes `BigInt64Array` issue in Safari.","archived":true,"fork":false,"pushed_at":"2021-07-18T23:12:09.000Z","size":1555,"stargazers_count":2,"open_issues_count":0,"forks_count":2,"subscribers_count":26,"default_branch":"master","last_synced_at":"2024-09-28T12:15:38.015Z","etag":null,"topics":[],"latest_commit_sha":null,"homepage":"","language":"JavaScript","has_issues":true,"has_wiki":null,"has_pages":null,"mirror_url":null,"source_name":null,"license":"apache-2.0","status":null,"scm":"git","pull_requests_enabled":true,"icon_url":"https://github.com/streamlit.png","metadata":{"files":{"readme":"README.md","changelog":null,"contributing":null,"funding":null,"license":"LICENSE.txt","code_of_conduct":null,"threat_model":null,"audit":null,"citation":null,"codeowners":null,"security":null,"support":null,"governance":null,"roadmap":null,"authors":null,"dei":null,"publiccode":null,"codemeta":null}},"created_at":"2021-07-18T22:16:22.000Z","updated_at":"2023-04-25T21:32:57.000Z","dependencies_parsed_at":null,"dependency_job_id":"fb5cba5f-2cd1-448f-86bb-d58f5bb6959c","html_url":"https://github.com/streamlit/arrow-js","commit_stats":{"total_commits":2,"total_committers":1,"mean_commits":2.0,"dds":0.0,"last_synced_commit":"af9f267084d7829033e7e10f79587b49df4f9806"},"previous_names":[],"tags_count":0,"template":false,"template_full_name":null,"repository_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/streamlit%2Farrow-js","tags_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/streamlit%2Farrow-js/tags","releases_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/streamlit%2Farrow-js/releases","manifests_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/streamlit%2Farrow-js/manifests","owner_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/owners/streamlit","download_url":"https://codeload.github.com/streamlit/arrow-js/tar.gz/refs/heads/master","host":{"name":"GitHub","url":"https://github.com","kind":"github","repositories_count":234724895,"owners_count":18877279,"icon_url":"https://github.com/github.png","version":null,"created_at":"2022-05-30T11:31:42.601Z","updated_at":"2022-07-04T15:15:14.044Z","host_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub","repositories_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories","repository_names_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repository_names","owners_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/owners"}},"keywords":[],"created_at":"2024-09-26T21:42:07.119Z","updated_at":"2025-09-30T10:30:48.832Z","avatar_url":"https://github.com/streamlit.png","language":"JavaScript","funding_links":[],"categories":[],"sub_categories":[],"readme":"\u003c!---\n  Licensed to the Apache Software Foundation (ASF) under one\n  or more contributor license agreements.  See the NOTICE file\n  distributed with this work for additional information\n  regarding copyright ownership.  The ASF licenses this file\n  to you under the Apache License, Version 2.0 (the\n  \"License\"); you may not use this file except in compliance\n  with the License.  You may obtain a copy of the License at\n\n    http://www.apache.org/licenses/LICENSE-2.0\n\n  Unless required by applicable law or agreed to in writing,\n  software distributed under the License is distributed on an\n  \"AS IS\" BASIS, WITHOUT WARRANTIES OR CONDITIONS OF ANY\n  KIND, either express or implied.  See the License for the\n  specific language governing permissions and limitations\n  under the License.\n--\u003e\n\n# [Apache Arrow](https://github.com/apache/arrow) in JS\n\n[![npm version](https://img.shields.io/npm/v/apache-arrow.svg)](https://www.npmjs.com/package/apache-arrow)\n[![Build Status](https://travis-ci.org/apache/arrow.svg?branch=master)](https://travis-ci.org/apache/arrow)\n[![Coverage Status](https://coveralls.io/repos/github/apache/arrow/badge.svg)](https://coveralls.io/github/apache/arrow)\n\nArrow is a set of technologies that enable big data systems to process and transfer data quickly.\n\n## Install `apache-arrow` from NPM\n\n`npm install apache-arrow` or `yarn add apache-arrow`\n\n(read about how we [package apache-arrow](#packaging) below)\n\n# Powering Columnar In-Memory Analytics\n\n[Apache Arrow](https://github.com/apache/arrow) is a columnar memory layout specification for encoding vectors and table-like containers of flat and nested data. The Arrow spec aligns columnar data in memory to minimize cache misses and take advantage of the latest SIMD (Single input multiple data) and GPU operations on modern processors.\n\nApache Arrow is the emerging standard for large in-memory columnar data ([Spark](https://spark.apache.org/), [Pandas](https://wesmckinney.com/blog/pandas-and-apache-arrow/), [Drill](https://drill.apache.org/), [Graphistry](https://www.graphistry.com), ...). By standardizing on a common binary interchange format, big data systems can reduce the costs and friction associated with cross-system communication.\n\n# Get Started\n\nCheck out our [API documentation][7] to learn more about how to use Apache Arrow's JS implementation. You can also learn by example by checking out some of the following resources:\n\n* [Observable: Introduction to Apache Arrow][5]\n* [Observable: Manipulating flat arrays arrow-style][6]\n* [Observable: Rich columnar data tables - Dictionary-encoded strings, 64bit ints, and nested structs][8]\n* [/js/test/unit](https://github.com/apache/arrow/tree/master/js/test/unit) - Unit tests for Table and Vector\n\n## Cookbook\n\n### Get a table from an Arrow file on disk (in IPC format)\n\n```js\nimport { readFileSync } from 'fs';\nimport { Table } from 'apache-arrow';\n\nconst arrow = readFileSync('simple.arrow');\nconst table = Table.from([arrow]);\n\nconsole.log(table.toString());\n\n/*\n foo,  bar,  baz\n   1,    1,   aa\nnull, null, null\n   3, null, null\n   4,    4,  bbb\n   5,    5, cccc\n*/\n```\n\n### Create a Table when the Arrow file is split across buffers\n\n```js\nimport { readFileSync } from 'fs';\nimport { Table } from 'apache-arrow';\n\nconst table = Table.from([\n    'latlong/schema.arrow',\n    'latlong/records.arrow'\n].map((file) =\u003e readFileSync(file)));\n\nconsole.log(table.toString());\n\n/*\n        origin_lat,         origin_lon\n35.393089294433594,  -97.6007308959961\n35.393089294433594,  -97.6007308959961\n35.393089294433594,  -97.6007308959961\n29.533695220947266, -98.46977996826172\n29.533695220947266, -98.46977996826172\n*/\n```\n\n### Create a Table from JavaScript arrays\n\n```js\nimport {\n  Table,\n  FloatVector,\n  DateVector\n} from 'apache-arrow';\n\nconst LENGTH = 2000;\n\nconst rainAmounts = Float32Array.from(\n  { length: LENGTH },\n  () =\u003e Number((Math.random() * 20).toFixed(1)));\n\nconst rainDates = Array.from(\n  { length: LENGTH },\n  (_, i) =\u003e new Date(Date.now() - 1000 * 60 * 60 * 24 * i));\n\nconst rainfall = Table.new(\n  [FloatVector.from(rainAmounts), DateVector.from(rainDates)],\n  ['precipitation', 'date']\n);\n```\n\n### Load data with `fetch`\n\n```js\nimport { Table } from \"apache-arrow\";\n\nconst table = await Table.from(fetch(\"/simple.arrow\"));\nconsole.log(table.toString());\n\n```\n\n### Columns look like JS Arrays\n\n```js\nimport { readFileSync } from 'fs';\nimport { Table } from 'apache-arrow';\n\nconst table = Table.from([\n    'latlong/schema.arrow',\n    'latlong/records.arrow'\n].map(readFileSync));\n\nconst column = table.getColumn('origin_lat');\n\n// Copy the data into a TypedArray\nconst typed = column.toArray();\nassert(typed instanceof Float32Array);\n\nfor (let i = -1, n = column.length; ++i \u003c n;) {\n    assert(column.get(i) === typed[i]);\n}\n```\n\n### Usage with MapD Core\n\n```js\nimport MapD from 'rxjs-mapd';\nimport { Table } from 'apache-arrow';\n\nconst port = 9091;\nconst host = `localhost`;\nconst db = `mapd`;\nconst user = `mapd`;\nconst password = `HyperInteractive`;\n\nMapD.open(host, port)\n  .connect(db, user, password)\n  .flatMap((session) =\u003e\n    // queryDF returns Arrow buffers\n    session.queryDF(`\n      SELECT origin_city\n      FROM flights\n      WHERE dest_city ILIKE 'dallas'\n      LIMIT 5`\n    ).disconnect()\n  )\n  .map(([schema, records]) =\u003e\n    // Create Arrow Table from results\n    Table.from([schema, records]))\n  .map((table) =\u003e\n    // Stringify the table to CSV with row numbers\n    table.toString({ index: true }))\n  .subscribe((csvStr) =\u003e\n    console.log(csvStr));\n/*\nIndex,   origin_city\n    0, Oklahoma City\n    1, Oklahoma City\n    2, Oklahoma City\n    3,   San Antonio\n    4,   San Antonio\n*/\n```\n\n# Getting involved\n\nSee [DEVELOP.md](DEVELOP.md)\n\nEven if you do not plan to contribute to Apache Arrow itself or Arrow\nintegrations in other projects, we'd be happy to have you involved:\n\n* Join the mailing list: send an email to\n  [dev-subscribe@arrow.apache.org][1]. Share your ideas and use cases for the\n  project.\n* [Follow our activity on JIRA][3]\n* [Learn the format][2]\n* Contribute code to one of the reference implementations\n\nWe prefer to receive contributions in the form of GitHub pull requests. Please send pull requests against the [github.com/apache/arrow][4] repository.\n\nIf you are looking for some ideas on what to contribute, check out the [JIRA\nissues][3] for the Apache Arrow project. Comment on the issue and/or contact\n[dev@arrow.apache.org](https://mail-archives.apache.org/mod_mbox/arrow-dev/)\nwith your questions and ideas.\n\nIf you’d like to report a bug but don’t have time to fix it, you can still post\nit on JIRA, or email the mailing list\n[dev@arrow.apache.org](https://mail-archives.apache.org/mod_mbox/arrow-dev/)\n\n## Packaging\n\n`apache-arrow` is written in TypeScript, but the project is compiled to multiple JS versions and common module formats.\n\nThe base `apache-arrow` package includes all the compilation targets for convenience, but if you're conscientious about your `node_modules` footprint, we got you.\n\nThe targets are also published under the `@apache-arrow` namespace:\n\n```sh\nnpm install apache-arrow # \u003c-- combined es5/UMD, es2015/CommonJS/ESModules/UMD, and TypeScript package\nnpm install @apache-arrow/ts # standalone TypeScript package\nnpm install @apache-arrow/es5-cjs # standalone es5/CommonJS package\nnpm install @apache-arrow/es5-esm # standalone es5/ESModules package\nnpm install @apache-arrow/es5-umd # standalone es5/UMD package\nnpm install @apache-arrow/es2015-cjs # standalone es2015/CommonJS package\nnpm install @apache-arrow/es2015-esm # standalone es2015/ESModules package\nnpm install @apache-arrow/es2015-umd # standalone es2015/UMD package\nnpm install @apache-arrow/esnext-cjs # standalone esNext/CommonJS package\nnpm install @apache-arrow/esnext-esm # standalone esNext/ESModules package\nnpm install @apache-arrow/esnext-umd # standalone esNext/UMD package\n```\n\n### Why we package like this\n\nThe JS community is a diverse group with a varied list of target environments and tool chains. Publishing multiple packages accommodates projects of all stripes.\n\nIf you think we missed a compilation target and it's a blocker for adoption, please open an issue.\n\n# People\n\nFull list of broader Apache Arrow [committers](https://arrow.apache.org/committers/).\n\n* Brian Hulette,  _committer_\n* Paul Taylor, Graphistry, Inc.,  _committer_\n\n# Powered By Apache Arrow in JS\n\nFull list of broader Apache Arrow [projects \u0026 organizations](https://arrow.apache.org/powered_by/).\n\n## Open Source Projects\n\n* [Apache Arrow](https://arrow.apache.org) -- Parent project for Powering Columnar In-Memory Analytics, including affiliated open source projects\n* [rxjs-mapd](https://github.com/graphistry/rxjs-mapd) -- A MapD Core node-driver that returns query results as Arrow columns\n* [Perspective](https://github.com/jpmorganchase/perspective) -- Perspective is a streaming data visualization engine by J.P. Morgan for JavaScript for building real-time \u0026 user-configurable analytics entirely in the browser.\n* [Falcon](https://github.com/uwdata/falcon) is a visualization tool for linked interactions across multiple aggregate visualizations of millions or billions of records.\n\n## Companies \u0026 Organizations\n\n* [CCRi](https://www.ccri.com/) -- Commonwealth Computer Research Inc, or CCRi, is a Central Virginia based data science and software engineering company\n* [GOAI](https://gpuopenanalytics.com/) -- GPU Open Analytics Initiative standardizes on Arrow as part of creating common data frameworks that enable developers and statistical researchers to accelerate data science on GPUs\n* [Graphistry, Inc.](https://www.graphistry.com/) - An end-to-end GPU accelerated visual investigation platform used by teams for security, anti-fraud, and related investigations. Graphistry uses Arrow in its NodeJS GPU backend and client libraries, and is an early contributing member to GOAI and Arrow\\[JS\\] working to bring these technologies to the enterprise.\n\n# License\n\n[Apache 2.0](https://github.com/apache/arrow/blob/master/LICENSE)\n\n[1]: mailto:dev-subscribe@arrow.apache.org\n[2]: https://github.com/apache/arrow/tree/master/format\n[3]: https://issues.apache.org/jira/browse/ARROW\n[4]: https://github.com/apache/arrow\n[5]: https://beta.observablehq.com/@theneuralbit/introduction-to-apache-arrow\n[6]: https://beta.observablehq.com/@lmeyerov/manipulating-flat-arrays-arrow-style\n[7]: https://arrow.apache.org/docs/js/\n[8]: https://observablehq.com/@lmeyerov/rich-data-types-in-apache-arrow-js-efficient-data-tables-wit\n","project_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fstreamlit%2Farrow-js","html_url":"https://awesome.ecosyste.ms/projects/github.com%2Fstreamlit%2Farrow-js","lists_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fstreamlit%2Farrow-js/lists"}