The Context Layer for unstructured data: typed, versioned datasets over S3, GCS, Azure
DataChain is a Python library and data-processing system that turns files from cloud storage or local filesystems into typed, versioned datasets that can be queried and processed. Teams use it to build repeatable pipelines for unstructured data, with optional knowledge-base and agent features that help coding agents understand and work with those datasets. The catalogue entries connect agents to DataChain's data workflows.
This repository also configures its own agents. See what datachain tells them →
Skill Claude CodeCodex
Use ONLY for abstract DataChain SDK questions — API usage, method signatures, or code patterns — when no specific dataset or bucket is referenced. If the request mentions creating, saving, listing, exploring datasets or buckets, use datachain-knowledge instead.
Skill Claude CodeCodex
Use whenever datasets, cloud storage buckets, or data pipelines are mentioned — creating, saving, querying, listing, exploring, deleting, or processing data in S3, GCS, Azure Blob, or local storage. Also use when running any script that may create datasets as a side effect. Maintains a knowledge base at dc-knowledge/…