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.
Trusted By
1.4m
Pypi downloads per month
3000+
OSS companies in production
250+
Snowflake customers in production
OPEN SOURCE (DLT)
pip install dlt and go
dlt is the most popular production-ready Python library for moving data. It loads 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 your favorite AI code editor, or add it to your Jupyter Notebook. You can load data from any source that produces Python data structures, including APIs, files, databases, and more.
import dlt
from dlt.sources.filesystem import filesystem
resource = filesystem(
bucket_url="s3://example-bucket",
file_glob="*.csv"
)
pipeline = dlt.pipeline(
pipeline_name="filesystem_example",
destination="duckdb",
dataset_name="filesystem_data",
)
pipeline.run(resource)VIBE CODE YOUR DATA PIPELINES
Unlimited data access
Can’t find the source you need in our documentation? You can easily define a custom source with our declarative REST API source. Our community builds 1000s of custom sources each month. We’ve developed various LLM rules and MCP servers that make converting your SaaS connectors or upgrading legacy pipelines with AI code editors simple. With the dlt ai setup command you can easily configure your favorite editor for maximum vibe coding success.
EARLY ACCESS DLT+
Upgrade your data platform with dlt+
We're turning the most common in-house patterns into reusable, interoperable components, so you can upgrade your data platform piece by piece, without starting from scratch. We're in early access and partnering with teams upgrading to Iceberg - come build with us.
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.
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.
