Manage dependencies for a Databricks app

Define additional Python libraries for a Databricks app using a requirements.txt file. If any listed packages match pre-installed ones, the versions in your file override the defaults.

For example, the following requirements.txt file pins specific versions and adds libraries beyond the pre-installed set:

# Override default version of dash
dash==2.10.0

# Add additional libraries not pre-installed
requests==2.31.0
numpy==1.24.3

# Specify a compatible version range
scikit-learn>=1.2.0,<1.3.0

Pre-installed Python libraries

The following Python libraries are pre-installed in the Databricks app environment. You don’t need to include them in your app unless you require a different version.

Library	Version
databricks-sql-connector	3.4.0
databricks-sdk	0.33.0
mlflow-skinny	2.16.2
gradio	4.44.0
streamlit	1.38.0
shiny	1.1.0
dash	2.18.1
flask	3.0.3
fastapi	0.115.0
uvicorn[standard]	0.30.6
gunicorn	23.0.0
dash-ag-grid	31.2.0
dash-mantine-components	0.14.4
dash-bootstrap-components	1.6.0
plotly	5.24.1
plotly-resampler	0.10.0

Version conflicts

Keep the following in mind when you define dependencies:

• Overriding pre-installed packages may cause compatibility issues if your specified version differs significantly from the pre-installed one.
• Always test your app to ensure that package version changes don't introduce errors.
• Pinning explicit versions in requirements.txt helps maintain consistent app behavior across deployments.