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dlt — data load tool & dltHub

dlt is the open-source Python library for moving data from any source to any destination. It automatically infers schemas, normalizes nested JSON, handles incremental loads, and evolves types as sources change — so data engineers can ship pipelines in minutes instead of weeks. dltHub extends the library with a managed workspace for building, deploying, and operating pipelines at team scale.

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https://dlthub.com/llms.txt
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Documentation: developer or product docs worth reading, nothing to call
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2026-10-19T10:41:13.226Z
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2026-10-20T10:53:33.821Z
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The beginning of the file, from our validated copy saved 2026-10-20T15:29:51.713Z. Cached copy · Source on dlthub.com

# dlt — data load tool & dltHub

> dlt is the open-source Python library for moving data from any source to any destination. It automatically infers schemas, normalizes nested JSON, handles incremental loads, and evolves types as sources change — so data engineers can ship pipelines in minutes instead of weeks. dltHub extends the library with a managed workspace for building, deploying, and operating pipelines at team scale.

This page follows the [llms.txt convention](https://llmstxt.org) and is a concise, link-first summary aimed at LLMs and agentic coding tools. For a full, auto-generated index of every documentation page — kept in sync on every docs deploy — use the docs llms.txt linked below rather than hand-curating documentation links here.

The marketing, blog, case study, and ecosystem sections below are generated from the dltHub CMS on every deploy/revalidate, so they stay in sync with the website automatically.

## Documentation
- [dlt docs — full index (llms.txt)](https://dlthub.com/docs/llms.txt): Auto-generated, always up-to-date list of every documentation page. Start here for anything code- or API-related.
- [dlt docs home](https://dlthub.com/docs/intro): Human-facing docs entry point.
- [REST API tutorial](https://dlthub.com/docs/tutorial/rest-api): Build a pipeline against any REST API in minutes.
- [SQL database tutorial](https://dlthub.com/docs/tutorial/sql-database): Load from any SQL database using the dlt SQL source.
- [Filesystem / object storage tutorial](https://dlthub.com/docs/tutorial/filesystem): Load JSON, JSONL, CSV, and Parquet from S3, GCS, Azure, or local disk.

## Pages
- [About dltHub](https://dlthub.com/about): Meet the team behind dltHub. We build the infrastructure for AI-native data engineering. Our mission is to make Python practitioners autonomous when they create and use datasets in their organizations.
- [Blog](https://dlthub.com/blog): See the latest articles from dltHub.
- [Case Studies | dltHub](https://dlthub.com/case-studies): How do data engineers use dlt (data load tool)? Dive into our case studies to see how data engineering teams solve problems
- [Contact us](https://dlthub.com/contact): Have questions or want to explore how our paid offerings can help your organization? Our solutions engineers are ready to assist.
- [Cookie Policy](https://dlthub.com/cookies)
- [Book a dltHub demo](https://dlthub.com/demo): Book a live dltHub demo. See how agents build, deploy, and run dlt pipelines on dltHub, mapped to your stack.
- [Data Processing Agreement | dltHub](https://dlthub.com/dpa): Data Processing Agreement between dltHub (ScaleVector GmbH) and Subscribers governing the processing of personal data under GDPR. Effective May 26, 2026.
- [dltHub Education](https://dlthub.com/education): Self-paced courses and certifications to master dlt, from your first pipeline to advanced production deployments.
- [dltHub Events](https://dlthub.com/events): Workshops, conferences, meetups, and webinars where the d
…

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