When you are ready to share your Streamlit dashboard, you have a few deployment options to consider. The most popular method is using Streamlit Community Cloud, which allows you to host your app for free and share it with anyone via a simple URL. Alternatively, you can run your app locally and share access within your network or by distributing the code for others to run on their own machines. Regardless of your approach, reproducibility is essential: you want others to experience your dashboard exactly as you designed it, with all dependencies and data working correctly.

To prepare your Streamlit app for deployment, you should organize your code in a single entry-point file — commonly named app.py or streamlit_app.py. Alongside your script, include a requirements.txt file listing all necessary libra sries, as shown above. This ensures anyone deploTo prepare your Streamlit app for deployment, you should organize your code in a single entry-point file — commonly named app.py or streamlit_app.py. Alongside your script, include a requirements.txt file listing all necessary libraries, as shown above. To quickly generate this file, you can run the command pip freeze > requirements.txt in your terminal to capture all current dependencies in your environment. This ensures anyone deploying or running your dashboard will have the correct environment set up. For Streamlit Community Cloud, you simply upload your code and requirements to a public GitHub repository, then connect it to Streamlit's platform to launch your app. For local sharing, instruct users to install the dependencies from requirements.txt and run the app with the streamlit run app.py command. Careful attention to reproducibility — such as fixing library versions and documenting any setup steps — will help others reliably use and interact with your dashboard.