Manage dependencies for your Streamlit app¶

Supported versions of the Streamlit library in warehouse runtimes¶

Streamlit in Snowflake supports the following versions of the Streamlit open-source library:

• 1.51.0

• 1.50.0

• 1.49.1

• 1.48.0

• 1.47.0

• 1.46.1

• 1.45.1

• 1.45.0

• 1.44.1

• 1.44.0

• 1.42.0

• 1.39.0

• 1.35.0

• 1.31.1

• 1.29.0

• 1.26.0

• 1.22.0

External access integrations for container runtimes¶

For a general overview of external access integrations (EAIs), see External network access overview.

CREATE OR REPLACE NETWORK RULE pypi_network_rule
  MODE = EGRESS
  TYPE = HOST_PORT
  VALUE_LIST = ('pypi.org', 'pypi.python.org', 'pythonhosted.org', 'files.pythonhosted.org');

CREATE OR REPLACE EXTERNAL ACCESS INTEGRATION pypi_access_integration
  ALLOWED_NETWORK_RULES = (pypi_network_rule)
  ENABLED = true;

GRANT USAGE ON EXTERNAL ACCESS INTEGRATION pypi_access_integration TO ROLE app_developer_role;

ALTER STREAMLIT my_app SET
  EXTERNAL_ACCESS_INTEGRATIONS = (pypi_access_integration);

Dependency files¶

Container runtimes use uv for fast, reliable dependency resolution. uv works like pip to install Python packages, but it’s more performant and customizable. For more information about uv’s features, see the Features overview in the uv documentation.

Container runtimes search for dependency files in the same directory as your app’s entrypoint file. If no dependency files are found, the search continues up the directory tree until reaching the root of your app’s source location. The first dependency file found is used to install your app’s dependencies.

When multiple dependency files exist in the same directory, they are used in the following order of precedence:

• requirements.txt: Lists the Python packages and versions required by your Streamlit app, including Streamlit itself. You can’t configure your Python version with requirements.txt.

  For more information about the format of requirements.txt, see Requirements File Format in the pip documentation.

• pyproject.toml (recommended): Manages your Python version and dependencies. Currently, only Python version 3.11 is supported. When you provide a pyproject.toml file, uv will generate a uv.lock file to lock your dependency versions. This lock file will be updated whenever you update your dependencies. You must use pyproject.toml if you want to use a different package index than PyPI.

  For more information about the format of pyproject.toml, see Writing your pyproject.toml in the Python documentation.

requirements.txt is the simplest way to declare your app’s dependencies and is provided for the convenience of getting started. However, for more advanced dependency management, Snowflake recommends using pyproject.toml instead. For example, this lets you lock dependency versions to ensure that your builds are reproducible.

Commonly, your entrypoint file and dependency file will be in the root of your project directory. However, your entrypoint file can be in a subdirectory and your dependency file can be in the same directory or any parent up to the root of your project.

For example, your project directory might have one of the following structures:

source_directory/
├── requirements.txt
└── streamlit_app.py

source_directory/
├── pyproject.toml
├── streamlit_app.py
└── uv.lock

source_directory/
├── pyproject.toml
├── subdirectory/
│   └── streamlit_app.py
└── uv.lock

source_directory/
└── subdirectory/
    ├── pyproject.toml
    ├── streamlit_app.py
    └── uv.lock

[project]
name = "my-streamlit-app"
version = "0.1.0"
requires-python = ">=3.11"
dependencies = [
    "streamlit[snowflake]==1.50.0",
    "pandas>=2.0.0",
    "plotly>5.0.0",
    "requests>2.0.0,<3.0.0"
]

streamlit[snowflake]==1.50.0
pandas>=2.0.0
plotly>5.0.0
requests>2.0.0,<3.0.0

[project]
name = "my-streamlit-app"
version = "0.1.0"
requires-python = ">=3.11"
dependencies = [
    "streamlit[snowflake]==1.50.0",
    "pandas>=2.0.0",
    "plotly>=5.0.0",
    "requests>2.0.0,<3.0.0"
]

[[tool.uv.index]]
name = "jfrog"
url = "<server_name>.jfrog.io/artifactory/api/pypi/<repository_key>/simple"
default = true

[[tool.uv.index]]
name = "jfrog"
url = "https://<username>:<access_token>@<server_name>.jfrog.io/artifactory/api/pypi/<repository_key>/simple"
default = true

environment.yml file¶

To install dependencies in your warehouse runtime environment using an environment.yml file, create or edit the file in the root of your app’s source location. If you don’t provide an environment.yml file, Snowflake uses only the pre-installed packages for your selected environment. For more information about the structure of environment.yml, see the conda documentation.

The following limitations apply when using environment.yml files in Streamlit in Snowflake warehouse runtimes:

• You can only use the Snowflake Anaconda Channel to install packages.

• You can only use the Streamlit versions listed in Supported versions of the Streamlit library in warehouse runtimes.

• You can’t declare pip packages in the dependencies section, including relative paths to local packages.

The following environment.yml declares Python 3.11 and five Python packages:

name: my-streamlit-app
channels:
  - snowflake
dependencies:
  - python=3.11
  - streamlit=1.50.0
  - pandas=2.*
  - plotly=5.0.*
  - requests
  - snowflake-snowpark-python

Snowflake recommends pinning a version of Streamlit to prevent the app from being upgraded when a new version of Streamlit becomes available in the Snowflake Anaconda Channel.

Local development with conda¶

When developing your warehouse-runtime app locally with conda, you must include additional details in your environment.yml file to ensure the dependencies are installed correctly.

• Identify the Snowflake Anaconda Channel by its URL: https://repo.anaconda.com/pkgs/snowflake.

• Block the default channel.

In your environment.yml file, use the following two channels:

channels:
  - https://repo.anaconda.com/pkgs/snowflake
  - nodefaults

If defaults appears in your ~/.condarc file, comment it out:

channels:
  # - defaults

Snowsight package picker¶

Besides editing the environment.yml file directly for your warehouse-runtime app, you can also use the built-in package picker in Snowsight to add or remove packages from your app’s environment. The package picker is only available for apps using warehouse runtimes. Additionally, the package picker only displays packages compatible with the current Python version of your app. Some system libraries that are independent of Python version might not be shown in the package picker and must be added manually to environment.yml.

1. Sign in to Snowsight.

2. In the navigation menu, select Projects » Streamlit, and then select your Streamlit app.

3. In the upper-right corner, select Edit.

4. In the upper-left corner of the editor pane, select Packages.

   A drop-down pane appears with the Anaconda Packages tab selected.

5. Do any of the following actions:

• To set the Python version, in the Python version selector, choose the desired version.

• To add a package, use the search bar to find packages by name, then select the desired package.

• To remove a package, in the Installed Packages section, select the x icon to the right of the package version.

• To set the version of an installed package, in the Installed Packages section, use the version selector next to the package name.

Snowflake updates your environment.yml file automatically and reboots your app. If you have the environment.yml file open in the editor, refresh the page to see the changes.