dltHub

Lightweight Python code to move data

We focus on the needs & constraints of Python-first data platform teams: how to write any data source, achieve data democracy, modernise legacy systems and reduce cloud costs.

OPEN SOURCE

Pip install dlt and go

With over 600k downloads per month, dlt 1.0 is the most popular production-ready Python library for moving data. You can add dlt to your Python scripts to load data from various and often messy data sources into well-structured, live datasets. Unlike other non-Python solutions, with dlt, there's no need to use any backends or containers. We do not replace your data platform, deployments, or security models. Simply import dlt in a Python file or a Jupyter Notebook cell. You can load data from any source that produces Python data structures, including APIs, files, databases, and more.

pip install dlt
DLT+ FOR DATA PLATFORM TEAMS

The Portable Data Lake

With dlt+ we propose a new approach to building data platforms that better meet the needs of diverse data teams working primarily in Python.

dlt+ works where you work - whether that’s local storage, data lakes, open storage formas, Pythonic engines & AI supported workfows.

Want to be the among the first to try the Portable Data Lake?

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Quotation mark icon{testimonial.author?.name}

The current machine learning revolution has been enabled by the Cambrian explosion of Python open-source tools that have become so accessible that a wide range of practitioners can use them. As a simple-to-use Python library, dlt is the first tool that this new wave of people can use. By leveraging this library, we can extend the machine learning revolution into enterprise data.

Quotation mark icon
Julien Chaumond
CTO/Co-Founder at Hugging Face
Quotation mark icon{testimonial.author?.name}

Python and machine learning under security constraints are key to our success. We found that our cloud ETL provider could not meet our needs. dlt is a lightweight yet powerful open source tool we can run together with Snowflake. Our event streaming and batch data loading performs at scale and low cost. Now anyone who knows Python can self-serve to fulfil their data needs.

Quotation mark icon
Maximilian Eber
CPTO & Co-Founder at Taktile
OPEN SOURCE

Access any data you want in Python

Today it is easier to pip install dlt and write a custom pipeline than to setup and configure a traditional ETL platform. In June '24 we crossed 5,000 dlt total custom sources created by the community since we launched dlt in summer '23. Because dlt is code we continue to automate engineering work and pass on productivity gains to organisations using dlt. Our new REST API Source toolkit is a short, declarative configuration driven way of creating sources. dlt-init-openapi is a a new tool that generates pipelines code out of any OpenAPI spec.

Quotation mark icon{testimonial.author?.name}

dlt has enabled me to completely rewrite all of our core SaaS service pipelines in 2 weeks and have data pipelines in production with full confidence. We also achieved data democracy for our data platform. Our product, business, and operation teams can independently satisfy a majority of their data needs through no-code self-service. The teams built multi-touch attribution for how Harness acquires customers, and models for how Harness customers utilize licenses. If the teams want to build anything else to push the company forward, they don't need to wait for permission or data access to do it.

Quotation mark icon
{testimonial.author?.name}
Alex Butler
Senior Data Engineer at Harness

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