Installation

Setting up your environment

1. Make sure you are using Python 3.8-3.12 and have pip installed

python --version
pip --version

If you have a different Python version installed or are missing pip, follow the instructions below to update your Python version and/or install pip.

Ubuntu

You can install Python 3.10 with apt.

sudo apt update
sudo apt install python3.10
sudo apt install python3.10-venv

macOS

On macOS, you can use Homebrew to install Python 3.10.

brew update
brew install python@3.10

Windows

After installing Python 3.10 (64-bit version) for Windows, you can install pip.

C:\> pip3 install -U pip

2. Set up and activate a virtual environment for your Python project

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.

Ubuntu

Create a new virtual environment in your working folder. This will create an ./env directory where your virtual environment will be stored:

python -m venv ./env

Activate the virtual environment:

source ./env/bin/activate

macOS

Create a new virtual environment in your working folder. This will create an ./env directory where your virtual environment will be stored:

python -m venv ./env

Activate the virtual environment:

source ./env/bin/activate

Windows

Create a new virtual environment in your working folder. This will create an ./env directory where your virtual environment will be stored:

C:\> python -m venv ./env

Activate the virtual environment:

C:\> .\env\Scripts\activate

3. Install dlt library

You can now install dlt in your virtual environment by running:

# install the newest dlt version or upgrade the existing version to the newest one
pip install -U dlt

Other installation examples:

# install dlt with support for duckdb
pip install "dlt[duckdb]"
# install dlt version smaller than 0.5.0
pip install "dlt<0.5.0"

3.1. Install dlt via Pixi or Conda

Install dlt using pixi:

pixi add dlt

Install dlt using conda:

conda install -c conda-forge dlt

4. Done!

You are now ready to build your first pipeline with dlt. Check out these tutorials to get started:

• Load data from a REST API
• Load data from a SQL database
• Load data from a cloud storage or a file system

Or read a more detailed tutorial on how to build a custom data pipeline with dlt.