RStudio Shiny Tutorial: Deploying Streamlit Applications with Ease

As data scientists and machine learning engineers, it's natural to be curious about the best tools for your projects. At Appsilon, we specialize in R and Shiny, but we also know our way around Python. In fact, it's very useful for Pythonistas as well! With the rise of Streamlit, deploying applications has become a crucial part of any data science workflow.

In this tutorial, we'll provide a walk-through from start to finish on how to deploy Streamlit applications using RStudio Connect. At the time of writing this post, RStudio was in transition for rebranding, including products such as Posit Connect – we'll refer to it here as RSConnect/RStudio Connect.

If you completed our recent Streamlit tutorial series, you might've noticed that your application was deployed using RStudio (Posit) Connect. This is because RStudio Connect provides strong support for Streamlit out-of-the-box. In this article, we'll dive deeper into the process and give some tips for error debugging along the way.

So, what are you waiting for? Let's get started!

Step 1: Prepare Your Application

Before deploying your Streamlit application, make sure it's ready to go. This includes testing your app locally and resolving any errors that may arise.

Step 2: Create an RSConnect Account

To deploy your application, you'll need to create an account on RStudio Connect. Follow the sign-up process and create a new account.

Step 3: Configure Your Application for Deployment

Once you have your RSConnect account set up, configure your Streamlit application for deployment. This includes setting environment variables, configuring your app's settings, and more.

Step 4: Deploy Your Application

With your application configured, it's time to deploy! Follow the steps outlined in the RSConnect documentation on deploying apps to get started.

Step 5: Monitor and Troubleshoot

After deployment, monitor your application to ensure everything is running smoothly. If you encounter any errors or issues, use the tips below for error debugging.

By following these steps, you'll be able to deploy your Streamlit applications with ease using RStudio Connect. Whether you're a Pythonista or an R enthusiast, this tutorial provides a comprehensive guide to getting started with deploying Streamlit apps on RSConnect.

So, which tool is better for your project – Python or R? We've explored the topic in detail in our blogs, and ultimately, it comes down to your specific needs and goals. With RStudio Connect and Streamlit, you have the power to create stunning applications that can be deployed with ease.

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