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| # Installation | |
| DataFusion is easy to install, just like any other Python library. | |
| ## Using uv | |
| If you do not yet have a virtual environment, create one: | |
| ```bash | |
| uv venv | |
| ``` | |
| You can add datafusion to your virtual environment with the usual: | |
| ```bash | |
| uv pip install datafusion | |
| ``` | |
| Or, to add to a project: | |
| ```bash | |
| uv add datafusion | |
| ``` | |
| ## Using pip | |
| ``` bash | |
| pip install datafusion | |
| ``` | |
| ## uv & JupyterLab setup | |
| This section explains how to install DataFusion in a uv environment with other libraries that allow for a nice Jupyter workflow. This setup is completely optional. These steps are only needed if you'd like to run DataFusion in a Jupyter notebook and have an interface like this: | |
|  | |
| Create a virtual environment with DataFusion, Jupyter, and other useful dependencies and start the desktop application. | |
| ```bash | |
| uv venv | |
| uv pip install datafusion jupyterlab jupyterlab_code_formatter | |
| uv run jupyter lab | |
| ``` | |
| ## Examples | |
| See the [DataFusion Python Examples](https://github.com/apache/arrow-datafusion-python/tree/main/examples) for a variety of Python scripts that show DataFusion in action! |