How To Deploy Streamlit App?

ByCarla Denker Blog

How to Deploy a Streamlit App

Streamlit is a popular open-source framework for building data apps. It’s easy to use, with a simple drag-and-drop interface that lets you create interactive web apps without having to write any code. But once you’ve created your Streamlit app, how do you deploy it so that others can use it?

In this article, we’ll show you how to deploy a Streamlit app to three different platforms:

  • Heroku, a cloud-based platform that allows you to deploy and host web applications.
  • Google Cloud Platform, a suite of cloud computing services that includes a platform for hosting web applications.
  • Amazon Web Services (AWS), a cloud computing platform that offers a variety of services, including a platform for hosting web applications.

We’ll also provide tips on how to make your Streamlit app more accessible and user-friendly.

By the end of this article, you’ll know how to deploy your Streamlit app to any of these platforms, so that you can share it with the world.

Step Instructions Example
1. Install the Streamlit CLI Run the following command in your terminal: pip install streamlit
2. Create a Streamlit app Create a new file called app.py and add the following code: 
import streamlit as st

def main():
  st.title("Hello, world!")
  st.write("This is a Streamlit app.")

if __name__ == "__main__":
  main()
3. Run the Streamlit app Run the following command in your terminal: streamlit run app.py

Prerequisites

What is Streamlit?

Streamlit is an open-source Python library that makes it easy to create beautiful, interactive web apps for machine learning and data science. With Streamlit, you can quickly and easily build apps that can be used to explore data, create visualizations, and share models. Streamlit is designed to be used by data scientists and engineers who want to create and deploy production-ready web apps without having to learn a lot of web development.

Benefits of using Streamlit

There are many benefits to using Streamlit, including:

  • Rapid development: Streamlit makes it easy to quickly and easily build web apps. You can create a new app in minutes, and you don’t need to know any web development.
  • Interactive visualizations: Streamlit makes it easy to create interactive visualizations of your data. You can use Streamlit to create charts, graphs, and maps, and you can easily embed these visualizations in your apps.
  • Model deployment: Streamlit makes it easy to deploy models to production. You can use Streamlit to create apps that serve models in real time, and you can easily scale your apps to handle large amounts of traffic.

Requirements for deploying a Streamlit app

To deploy a Streamlit app, you will need:

  • A Python environment with the Streamlit library installed
  • A web server that can host your app
  • A domain name for your app

Deployment Options

There are two main options for deploying a Streamlit app: local deployment and cloud deployment.

Local deployment

Local deployment is the simplest way to deploy a Streamlit app. To deploy a Streamlit app locally, you can use the following steps:

1. Create a new Python environment and install the Streamlit library.
2. Write your Streamlit app.
3. Run the following command to start your app:

streamlit run app.py

Your app will be hosted on your local machine, and you can access it by visiting the following URL in your browser:

http://localhost:8501

Cloud deployment

Cloud deployment is a more scalable and reliable way to deploy a Streamlit app. To deploy a Streamlit app to the cloud, you can use a variety of services, including:

  • Google Cloud Platform
  • Amazon Web Services
  • Microsoft Azure

To deploy a Streamlit app to the cloud, you will need to create a new project in your cloud provider’s console. You will then need to create a new service to host your app. Once your service is created, you can deploy your app by following the instructions provided by your cloud provider.

Streamlit is a powerful tool for creating and deploying web apps for machine learning and data science. With Streamlit, you can quickly and easily build interactive visualizations of your data, and you can easily deploy your apps to production.

If you are interested in learning more about Streamlit, I encourage you to check out the following resources:

  • [Streamlit documentation](https://docs.streamlit.io/en/stable/)
  • [Streamlit tutorials](https://docs.streamlit.io/en/stable/tutorial/index.html)
  • [Streamlit community forum](https://discuss.streamlit.io/)

I hope this article has been helpful!

Deployment Steps

To deploy a Streamlit app, you need to follow these steps:

1. Create a Streamlit app. You can create a Streamlit app using the Streamlit CLI or the Streamlit library. For more information, see the [Streamlit documentation](https://docs.streamlit.io/en/stable/).
2. Configure your app for deployment. You need to configure your app to use a specific deployment method. For more information, see the [Streamlit documentation](https://docs.streamlit.io/en/stable/deploying.html).
3. Deploy your app. You can deploy your app to a local server, a cloud platform, or a third-party hosting service. For more information, see the [Streamlit documentation](https://docs.streamlit.io/en/stable/deploying.html).

Local deployment steps

To deploy a Streamlit app to a local server, you can use the following steps:

1. Install the Streamlit CLI.
2. Create a new directory for your app.
3. Write your Streamlit app.
4. Run the following command to start your app in development mode:

streamlit run app.py

5. Open your browser and go to the URL that is printed in the terminal.

6. To stop your app, press `Ctrl`+`C` in the terminal.

Cloud deployment steps

To deploy a Streamlit app to a cloud platform, you can use the following steps:

1. Create a new project in the cloud platform of your choice.
2. Install the Streamlit CLI.
3. Create a new directory for your app.
4. Write your Streamlit app.
5. Run the following command to build your app:

streamlit build

6. Upload the built app to your cloud platform.
7. Open your browser and go to the URL that is provided by your cloud platform.

Troubleshooting

There are a few common problems that you may encounter when deploying a Streamlit app. Here are some solutions to these problems:

  • Problem: Your app is not loading.
  • Solution: Make sure that you have installed the Streamlit CLI and that you are running the correct command. For more information, see the [Streamlit documentation](https://docs.streamlit.io/en/stable/deploying.html).
  • Problem: Your app is running slowly.
  • Solution: Make sure that your app is not using too much memory or CPU. You can also try to deploy your app to a more powerful server.
  • Problem: Your app is not displaying correctly.
  • Solution: Make sure that your app is using the correct dimensions and that you are using the correct CSS. You can also try to deploy your app to a different browser.

Deploying a Streamlit app is a relatively simple process. By following the steps in this guide, you can easily deploy your app to a local server or a cloud platform.

Q: What is Streamlit?

A: Streamlit is a Python library that makes it easy to create beautiful, interactive web apps. It is designed to be used by data scientists and engineers who want to quickly and easily build and share their work. Streamlit apps are typically built using Python, but they can also be used with other languages such as R and Julia.

Q: What are the benefits of using Streamlit?

A: There are many benefits to using Streamlit, including:

  • Simplicity: Streamlit is very easy to use, even for those who are not familiar with Python or web development.
  • Rapid development: Streamlit apps can be developed quickly and easily, with no need for complex frameworks or libraries.
  • Interactive: Streamlit apps are interactive, allowing users to explore data and models in real time.
  • Sharing: Streamlit apps can be easily shared with others, making it easy to collaborate and disseminate results.

Q: How do I deploy a Streamlit app?

A: There are several ways to deploy a Streamlit app, including:

  • Local deployment: You can deploy a Streamlit app locally on your own computer. This is the easiest way to get started, but it is not suitable for production environments.
  • Cloud deployment: You can deploy a Streamlit app to a cloud-based service such as Heroku or Google Cloud Platform. This is a more scalable and reliable option, but it can be more complex to set up.
  • Docker deployment: You can deploy a Streamlit app using Docker. This is a good option for developers who want to have more control over the deployment process.

Q: What are the best practices for deploying a Streamlit app?

A: There are a few best practices to follow when deploying a Streamlit app, including:

  • Use a production-ready build: When deploying a Streamlit app to a production environment, it is important to use a production-ready build. This means that the app has been tested and is known to work in a production environment.
  • Use a robust deployment strategy: The deployment strategy you choose should be robust and reliable. This means that the app should be able to handle unexpected errors and downtime.
  • Monitor your app: It is important to monitor your app after it has been deployed. This will help you to identify and fix any problems that may arise.

Q: What are some common problems with deploying Streamlit apps?

A: There are a few common problems that can occur when deploying Streamlit apps, including:

  • Errors: The app may not work as expected due to errors in the code.
  • Downtime: The app may be unavailable due to unexpected errors or downtime.
  • Security vulnerabilities: The app may be vulnerable to security attacks.

Q: How can I avoid common problems with deploying Streamlit apps?

A: There are a few things you can do to avoid common problems with deploying Streamlit apps, including:

  • Test your app thoroughly: Before deploying your app, it is important to test it thoroughly. This will help you to identify and fix any problems before they cause issues in production.
  • Use a robust deployment strategy: The deployment strategy you choose should be robust and reliable. This means that the app should be able to handle unexpected errors and downtime.
  • Monitor your app: It is important to monitor your app after it has been deployed. This will help you to identify and fix any problems that may arise.

    In this blog post, we have discussed how to deploy a Streamlit app. We covered the different deployment methods, including the local development server, the Streamlit Cloud, and the Kubernetes cluster. We also discussed the pros and cons of each method.

The best deployment method for you will depend on your specific needs and requirements. If you are just getting started with Streamlit, the local development server is a good option. It is easy to set up and use, and it does not require any additional infrastructure.

If you need to share your app with others, the Streamlit Cloud is a good option. It is a hosted platform that provides a simple and secure way to share your apps with the world.

If you need to scale your app to handle large amounts of traffic, a Kubernetes cluster is a good option. Kubernetes is a container orchestration platform that can help you to manage and scale your app.

We hope this blog post has been helpful. For more information on deploying Streamlit apps, please refer to the Streamlit documentation.

Author Profile

Carla Denker
Carla Denker
Carla Denker first opened Plastica Store in June of 1996 in Silverlake, Los Angeles and closed in West Hollywood on December 1, 2017. PLASTICA was a boutique filled with unique items from around the world as well as products by local designers, all hand picked by Carla. Although some of the merchandise was literally plastic, we featured items made out of any number of different materials.

Prior to the engaging profile in west3rdstreet.com, the innovative trajectory of Carla Denker and PlasticaStore.com had already captured the attention of prominent publications, each one spotlighting the unique allure and creative vision of the boutique. The acclaim goes back to features in Daily Candy in 2013, TimeOut Los Angeles in 2012, and stretched globally with Allure Korea in 2011. Esteemed columns in LA Times in 2010 and thoughtful pieces in Sunset Magazine in 2009 highlighted the boutique’s distinctive character, while Domino Magazine in 2008 celebrated its design-forward ethos. This press recognition dates back to the earliest days of Plastica, with citations going back as far as 1997, each telling a part of the Plastica story.

After an illustrious run, Plastica transitioned from the tangible to the intangible. While our physical presence concluded in December 2017, our essence endures. Plastica Store has been reborn as a digital haven, continuing to serve a community of discerning thinkers and seekers. Our new mission transcends physical boundaries to embrace a world that is increasingly seeking knowledge and depth.

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