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Build the dashboard in Streamlit, use Plotly for interactive charts, and let GitHub Actions test repository changes. The workflow checks code; it does not host the live app. For a documented GitHub-based hosting path, Streamlit Community Cloud connects to a repository and deploys the app from it.
What each part of the stack does
- Streamlit builds the Python app: its widgets collect user choices, and your code uses those choices to prepare and display data. Its first-app tutorial covers data handling, charts, maps, and widgets.
- Plotly creates interactive chart objects. Streamlit displays a Plotly
FigureorDataobject withst.plotly_chart. - GitHub stores the source repository. GitHub Actions runs automated checks against changes in that repository.
- A hosting provider runs the live app. Its deployment mechanism determines how checked source changes reach that app.
Keeping these roles distinct helps avoid a common misunderstanding: a passing GitHub Actions workflow does not, by itself, publish or host a Streamlit dashboard.
Build the app and connect Plotly
- Create an entrypoint. Start with a Python file such as
streamlit_app.py. Load or prepare the data, then render a basic chart. Streamlit’s documentation and tutorial show the framework’s app and data features. - Add controls that affect the result. Use Streamlit widgets for filters or selections, then use their values in your data-preparation logic. This makes the displayed result respond to the reader’s choices.
- Build a Plotly chart when its interactions or chart types are useful. Create a Plotly figure and pass it to Streamlit:
st.plotly_chart(figure)The Streamlit API reference accepts a Plotly Figure or Data object and specifies plotly>=4.0.0. Treat that as the documented minimum for this API, not as a recommendation to leave dependencies unpinned or unmanaged.
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A hosted app runs in a remote environment; packages installed only on your computer will not automatically be available there. Declare the app’s required packages in the project’s dependency file, such as a root requirements.txt, and follow the selected host’s current instructions for any additional software requirements. Streamlit Community Cloud supplies Python and Streamlit, but your app still needs its other dependencies declared. See Streamlit’s guidance on managing deployment dependencies.
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Keep credentials and other private configuration out of source code. Configure them using the hosting provider’s secret-management process. Streamlit’s deployment concepts describe dependencies, secrets, and remote app startup as central parts of deployment.
Run automated checks with GitHub Actions
Put a workflow file in .github/workflows/ so GitHub Actions can test changes before or as they reach the deployment branch. Streamlit’s CI example runs on pushes and pull requests to main. It uses actions/checkout@v4, actions/setup-python@v5 with Python 3.11, and streamlit/streamlit-app-action@v0.0.3, with the app entrypoint set as app-path.
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Those action versions and the Python version are the values in Streamlit’s documentation example, not a claim that they are the newest or right for every project. Before adopting them, check the actions’ releases and your project’s supported Python versions.
The documented Streamlit app action installs pytest and dependencies from a root requirements.txt, runs built-in smoke tests for the specified app and any additional pages, and runs Python tests it finds in the repository. Ruff linting can also be enabled. If your project uses another dependency manager or test command, adapt the workflow and add the necessary installation and test steps.
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- Run the checks on pull requests so problems are visible before merging.
- Run them on updates to the branch used for deployment.
- Set the app path to the actual entrypoint and confirm the workflow installs the dependencies your app needs.
Deploy from GitHub to Streamlit Community Cloud
For the Community Cloud path, connect your GitHub account, select the repository, choose the app entrypoint, and deploy. The person deploying must have admin permissions on the source repository. Private repositories and organization repositories may require additional authorization; see Streamlit’s instructions to connect a GitHub account.
After deployment, repository pushes are reflected in the app. Streamlit’s app management documentation notes that dependency changes trigger a full redeployment, which takes longer. Check the live app after a change: confirm it starts, reads its data source, renders the chart, and can access configured secrets.
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Choose a host based on your app’s needs
Streamlit’s deployment overview lists Community Cloud, Snowflake, and tutorials for other providers. It describes Community Cloud as suited to non-commercial, personal, and educational apps, and Snowflake as enterprise-grade. Those broad descriptions do not determine which option fits a particular project.
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- Audience and use: Is the app personal, educational, public, or for business use?
- Access control: Who can view the app, and what repository permissions or private-repository authorization does deployment require?
- Security and data: How will secrets be managed, and does the data or organization require specific controls?
- Operations: How does the provider install dependencies, start the app, expose logs, handle restarts, and deploy changes?
- Cost and limits: Check each provider’s current pricing, quotas, and usage policies directly. The available Streamlit overview does not establish comparable current figures.
CI and hosting answer different questions: GitHub Actions checks whether a change passes your configured tests; the host runs the app and handles deployment. Streamlit’s deployment tutorials provide provider-specific paths to explore.
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