:::info Supported Python versions

dltHub currently supports Python versions 3.10-3.13.

:::

Quickstart#

To install the dlt[hub] package, create a new Python virtual environment and run:

uv pip install "dlt[hub]"

This will install dlt with two additional extras:

• dlthub which enables features that require a license
• dlt-runtime which enables access to dltHub Runtime

When working with locally you'll need several dependencies like duckdb, marimo, pyarrow or fastmcp. You can install them all with:

uv pip install "dlt[workspace]"

If you need to install uv (a modern package manager), please refer to the next section.

Upgrade existing installation#

To upgrade just the hub extra without upgrading dlt itself run:

uv pip install -U "dlt[hub]==1.20.0"

This will keep current 1.20.0 dlt and upgrade dlthub and dlt-runtime to their newest matching versions.

Enable dltHub Free and Paid features#

Setting up your environment#

Configuration of the Python environment#

In this documentation, we use uv (a modern package manager) to install Python versions, manage virtual environments, and manage project dependencies.
To install uv, you can use pip or follow the OS-specific installation instructions.

Once you have uv installed you can pick any Python version supported by it:

uv python install 3.13

or use any Python version you have installed on your system.

Virtual environment#

We recommend working within a virtual environment when creating Python projects.
This way, all the dependencies for your current project will be isolated from packages in other projects. With uv, run:

uv venv

This will create a virtual environment in the .venv folder using the default system Python version.

uv venv --python 3.13

This will use Python 3.13 for your virtual environment.

Activate the virtual environment using the instructions displayed by uv, i.e.:

source .venv/bin/activate

Licensing#

To access dltHub’s paid features, such as Iceberg support or Python-based transformations, you need a dltHub Software License.

1. Contact us if you want to purchase a license or get a trial license with unlimited use.
2. Issue a limited trial license yourself.

Install your license#

If you've received your license from us, you can install it in one of two ways:

In the secrets.toml file:

license = "your-dlthub-license-key"

As an environment variable:

export DLT_LICENSE_KEY="your-dlthub-license-key"

Features requiring a license:#

• @dlt.hub.transformation - a powerful Python decorator to build transformation pipelines and notebooks
• dbt transformations - a staging layer for data transformations, combining a local cache with schema enforcement, debugging tools, and integration with existing data workflows.
• Iceberg support.
• Data Checks.
• MSSQL Change Tracking source.

For more information about the feature scopes, see Scopes.
Please, also review our End User License Agreement

Self-licensing#

You can self-issue an anonymous 30-day trial license to explore dltHub’s paid features.
This trial license is intended for development, education, and CI operations only. Self-issued licenses are bound to the specific machine on which they were created. They cannot be transferred or reused on other machines, workspaces, or environments.

See the Special Terms in our EULA for more details.

Issue a Trial License#

Choose a scope for the feature you want to test, then issue a license with:

dlt license issue <scope>

for example:

dlt license issue dlthub.transformation

This will do the following:

• Issue a new license (or merge with existing scopes) for the transformations feature.
• Print your license key in the CLI output.
• Put the license key into your toml file.

Scopes#

Display available scopes by running the following command:

dlt license scopes

You can self-issue multiple licenses; newly issued licenses will automatically include previously granted features.

To view your installed licenses:

dlt license info