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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.