Skip to main content

With CocoIndex, users declare the transformation, CocoIndex creates & maintains an index, and keeps the derived index up to date based on source update, with minimal computation and changes.

Project description

CocoIndex

Data transformation for AI

GitHub Documentation License PyPI version

PyPI Downloads CI release Link Check prek Discord

cocoindex-io%2Fcocoindex | Trendshift

Ultra performant data transformation framework for AI, with core engine written in Rust. Support incremental processing and data lineage out-of-box. Exceptional developer velocity. Production-ready at day 0.

⭐ Drop a star to help us grow!


CocoIndex Transformation


CocoIndex makes it effortless to transform data with AI, and keep source data and target in sync. Whether you’re building a vector index, creating knowledge graphs for context engineering or performing any custom data transformations — goes beyond SQL.


CocoIndex Features


Exceptional velocity

Just declare transformation in dataflow with ~100 lines of python

# import
data['content'] = flow_builder.add_source(...)

# transform
data['out'] = data['content']
    .transform(...)
    .transform(...)

# collect data
collector.collect(...)

# export to db, vector db, graph db ...
collector.export(...)

CocoIndex follows the idea of Dataflow programming model. Each transformation creates a new field solely based on input fields, without hidden states and value mutation. All data before/after each transformation is observable, with lineage out of the box.

Particularly, developers don't explicitly mutate data by creating, updating and deleting. They just need to define transformation/formula for a set of source data.

Plug-and-Play Building Blocks

Native builtins for different source, targets and transformations. Standardize interface, make it 1-line code switch between different components - as easy as assembling building blocks.

CocoIndex Features

Data Freshness

CocoIndex keep source data and target in sync effortlessly.

Incremental Processing

It has out-of-box support for incremental indexing:

  • minimal recomputation on source or logic change.
  • (re-)processing necessary portions; reuse cache when possible

Quick Start

If you're new to CocoIndex, we recommend checking out

Setup

  1. Install CocoIndex Python library

Note: CocoIndex v1 is currently in preview (pre-release). Use the --pre flag with pip, or configure your package manager to allow pre-releases.

pip install -U --pre cocoindex
  1. Install Postgres if you don't have one. CocoIndex uses it for incremental processing.

  2. (Optional) Install Claude Code skill for enhanced development experience. Run these commands in Claude Code:

/plugin marketplace add cocoindex-io/cocoindex-claude
/plugin install cocoindex-skills@cocoindex

📖 Documentation

For detailed documentation, visit CocoIndex Documentation, including a Quickstart guide.

🤝 Contributing

We love contributions from our community ❤️. For details on contributing or running the project for development, check out our contributing guide.

👥 Community

Welcome with a huge coconut hug 🥥⋆。˚🤗. We are super excited for community contributions of all kinds - whether it's code improvements, documentation updates, issue reports, feature requests, and discussions in our Discord.

Join our community here:

Support us

We are constantly improving, and more features and examples are coming soon. If you love this project, please drop us a star ⭐ at GitHub repo GitHub to stay tuned and help us grow.

License

CocoIndex is Apache 2.0 licensed.

Project details


Release history Release notifications | RSS feed

Download files

Download the file for your platform. If you're not sure which to choose, learn more about installing packages.

Source Distribution

cocoindex-1.0.0a48.tar.gz (339.1 kB view details)

Uploaded Source

Built Distributions

If you're not sure about the file name format, learn more about wheel file names.

cocoindex-1.0.0a48-cp314-cp314t-win_amd64.whl (6.8 MB view details)

Uploaded CPython 3.14tWindows x86-64

cocoindex-1.0.0a48-cp314-cp314t-manylinux_2_28_x86_64.whl (6.6 MB view details)

Uploaded CPython 3.14tmanylinux: glibc 2.28+ x86-64

cocoindex-1.0.0a48-cp314-cp314t-manylinux_2_28_aarch64.whl (6.4 MB view details)

Uploaded CPython 3.14tmanylinux: glibc 2.28+ ARM64

cocoindex-1.0.0a48-cp314-cp314t-macosx_11_0_arm64.whl (6.6 MB view details)

Uploaded CPython 3.14tmacOS 11.0+ ARM64

cocoindex-1.0.0a48-cp311-abi3-win_amd64.whl (6.8 MB view details)

Uploaded CPython 3.11+Windows x86-64

cocoindex-1.0.0a48-cp311-abi3-manylinux_2_28_x86_64.whl (6.6 MB view details)

Uploaded CPython 3.11+manylinux: glibc 2.28+ x86-64

cocoindex-1.0.0a48-cp311-abi3-manylinux_2_28_aarch64.whl (6.4 MB view details)

Uploaded CPython 3.11+manylinux: glibc 2.28+ ARM64

cocoindex-1.0.0a48-cp311-abi3-macosx_11_0_arm64.whl (6.6 MB view details)

Uploaded CPython 3.11+macOS 11.0+ ARM64

cocoindex-1.0.0a48-cp311-abi3-macosx_10_12_x86_64.whl (6.5 MB view details)

Uploaded CPython 3.11+macOS 10.12+ x86-64

File details

Details for the file cocoindex-1.0.0a48.tar.gz.

File metadata

  • Download URL: cocoindex-1.0.0a48.tar.gz
  • Upload date:
  • Size: 339.1 kB
  • Tags: Source
  • Uploaded using Trusted Publishing? Yes
  • Uploaded via: maturin/1.13.1

File hashes

Hashes for cocoindex-1.0.0a48.tar.gz
Algorithm Hash digest
SHA256 539d0af5af3655c67dd8b114d317a5a188dd11a48551a0f2dea97670a0cf73d1
MD5 817f62d3d08ee6a1525948b889c7297b
BLAKE2b-256 008254d1ee70757fe9755b9f6496712ac36e72cf9283b29292fdfe98f2fabe09

See more details on using hashes here.

File details

Details for the file cocoindex-1.0.0a48-cp314-cp314t-win_amd64.whl.

File metadata

File hashes

Hashes for cocoindex-1.0.0a48-cp314-cp314t-win_amd64.whl
Algorithm Hash digest
SHA256 8ceba9bc2e6d460205b951f79bb033ee00372014e31859ec7179cfdf4c5d6596
MD5 1a0f502b6598d71a59d6802598aa78f9
BLAKE2b-256 18c39b82f1e12c7e80053e0707ee9e26c35a71f7a24dc623c39b82ee8d4c0a6f

See more details on using hashes here.

File details

Details for the file cocoindex-1.0.0a48-cp314-cp314t-manylinux_2_28_x86_64.whl.

File metadata

File hashes

Hashes for cocoindex-1.0.0a48-cp314-cp314t-manylinux_2_28_x86_64.whl
Algorithm Hash digest
SHA256 7ac1c86c04ed848be359bbb3e03e9e82e58eef405065fab8e9f8e315da9efb15
MD5 b71228c85412d807d4f9df6164596b2e
BLAKE2b-256 ff459ccdf7e51577823a0410542168404765c0d347cb691654bc8275260a1d6f

See more details on using hashes here.

File details

Details for the file cocoindex-1.0.0a48-cp314-cp314t-manylinux_2_28_aarch64.whl.

File metadata

File hashes

Hashes for cocoindex-1.0.0a48-cp314-cp314t-manylinux_2_28_aarch64.whl
Algorithm Hash digest
SHA256 b122a1a9f3a894f59468fa82d5a77556d1a4995a653331c38011ea1933515ef4
MD5 978e31a342685f2a565005e8662f6678
BLAKE2b-256 83427452f0f85160c9009216b38e859d2cee166162ef16b33bdf5d98983390df

See more details on using hashes here.

File details

Details for the file cocoindex-1.0.0a48-cp314-cp314t-macosx_11_0_arm64.whl.

File metadata

File hashes

Hashes for cocoindex-1.0.0a48-cp314-cp314t-macosx_11_0_arm64.whl
Algorithm Hash digest
SHA256 e9b330fec2592fdc8906a7d8336ca4fd2e611d58105d5f35717186d968c9c3c1
MD5 5545a1caecf18b520286a993dd7cc029
BLAKE2b-256 044ab92ab4f69f34c12ef702bba4f4139d55e883299119af8b01228b28c58cc2

See more details on using hashes here.

File details

Details for the file cocoindex-1.0.0a48-cp311-abi3-win_amd64.whl.

File metadata

File hashes

Hashes for cocoindex-1.0.0a48-cp311-abi3-win_amd64.whl
Algorithm Hash digest
SHA256 17010dc84c69583464d876f96e2ce8eb8bd9126ec48078546d00458b4e3de4e8
MD5 70aad066147eeb0d986fb2f4afac3086
BLAKE2b-256 7fe9c2cfe31fce9fc2d6060d3700759f2c053bf3b87842fea6a526c3ba36a840

See more details on using hashes here.

File details

Details for the file cocoindex-1.0.0a48-cp311-abi3-manylinux_2_28_x86_64.whl.

File metadata

File hashes

Hashes for cocoindex-1.0.0a48-cp311-abi3-manylinux_2_28_x86_64.whl
Algorithm Hash digest
SHA256 bfe128e51e0f115c52cef710a08a1b69eb139b0b279aa69524bdb0837173a5da
MD5 c95740e7220c1e5fbcd51e732dd2a899
BLAKE2b-256 c77f5580bb7db94230816b73495de65e5be89c3916a7564d60be0ee8a6ec2181

See more details on using hashes here.

File details

Details for the file cocoindex-1.0.0a48-cp311-abi3-manylinux_2_28_aarch64.whl.

File metadata

File hashes

Hashes for cocoindex-1.0.0a48-cp311-abi3-manylinux_2_28_aarch64.whl
Algorithm Hash digest
SHA256 0ce6396d86c3c1f0209e225414972323ca0e51a865cec0d255b9ad0b6eb5df13
MD5 cd565de8ad893e518f64d09d18a1d7b8
BLAKE2b-256 4245d21ff5636688b46c89166ff76f3e373eb47b11882021d12da9cfc6385da8

See more details on using hashes here.

File details

Details for the file cocoindex-1.0.0a48-cp311-abi3-macosx_11_0_arm64.whl.

File metadata

File hashes

Hashes for cocoindex-1.0.0a48-cp311-abi3-macosx_11_0_arm64.whl
Algorithm Hash digest
SHA256 e432403e77fc0041b6adfe504357da8caff5af71e404448506dfd2f6948324c2
MD5 c317bcc26543f21666638b083528a9ec
BLAKE2b-256 86c25a33e1ad650b475c9cd6ed11791dba79d9b0576d8496b82c37fa3115c8e3

See more details on using hashes here.

File details

Details for the file cocoindex-1.0.0a48-cp311-abi3-macosx_10_12_x86_64.whl.

File metadata

File hashes

Hashes for cocoindex-1.0.0a48-cp311-abi3-macosx_10_12_x86_64.whl
Algorithm Hash digest
SHA256 2a2c871335569b62db82ee5b2551a0a8d115cc68f67766128c9c64ce717b25ce
MD5 57576534b67914ed84b68e84b489f16e
BLAKE2b-256 f9d1f0e3c7a74e5620585709117d9547edc781338083ae288d206a475bd75cee

See more details on using hashes here.

Supported by

AWS Cloud computing and Security Sponsor Datadog Monitoring Depot Continuous Integration Fastly CDN Google Download Analytics Pingdom Monitoring Sentry Error logging StatusPage Status page