How To Bring Your Data & AI Algorithms into Production Ready Web App Using Python
Tags: webdev, python, programming, devops
Published: 2024-03-12 11:35:37

When bringing your data and AI algorithms into a production-ready web app using Python, tools like Streamlit and Taipy can be incredibly useful. These tools empower data scientists and machine learning engineers to create interactive, user-friendly applications without the need for extensive web development experience. 

By leveraging Streamlit or Taipy, you can focus on showcasing your data and algorithms effectively, making your applications more accessible and impactful.

What is Streamlit?

Streamlit is a Python library that makes creating web apps for machine learning, data science, and other projects easy. It allows you to turn your Python scripts into interactive web apps without writing a lot of code. With Streamlit, you can quickly build and share your projects with others, making it a valuable tool for showcasing your work and collaborating with others.

I believe everyone loves stories, so let’s understand what Steamlit is in the form of a story, Here it goes –

Imagine you have a magical book that can turn your stories into interactive adventures. That’s what Streamlit is for Python developers! It’s like having a special pen that brings your ideas to life on a web page.

Unlike other libraries that require you to learn complex spells (like HTML, CSS, and JavaScript), Streamlit lets you create web apps using simple Python scripts. It’s as easy as writing a story, with commands that let you add buttons, sliders, and charts to your app without extra effort.

So, instead of spending days learning new languages, you can focus on telling your story and creating amazing web apps that everyone can enjoy. Streamlit is like a bridge between your imagination and the web, making it easier and more fun to share your ideas with the world.

Sounds interesting right?

But what if I tell you there is another library in Python that can do much more than Streamlit can do?

Yes you heard it right and that library is ‘Taipy‘

What is Taipy?

Taipy is a complete Python library that covers the full software development cycle. From simple pilots to production-ready web applications in no time. It’s specifically crafted for data scientists and machine learning engineers, offering a streamlined approach to building full-stack applications. No more compromise on performance, customization, and scalability. 

However, let’s compare it to Streamlit on the GUI side.

With Taipy, you can create web applications without needing to dive deep into HTML, CSS, and JS coding. Besides this, Taipy is cloud agnostic, and it offers a free deployment platform for its community users to help preview app rendering: Taipy Cloud. 

Python open-source AI is taking over the world, and Taipy is definitely part of it.

While Taipy is not intended to replace web developers, it serves as a valuable alternative for those who need to develop applications without prior web development experience. For data scientists and individuals working with data, Taipy offers a simplified approach to application development, significantly easing the development process.

Take a look at Taipy, an open-source Python library to build end-to-end production applications And if you do like this library, drop a star to the repo.

What Taipy offers:

Taipy provides a bunch of features:

Large data support.
Fast graphical performance.
Dataflow management and task optimization.
A REST API.
A cache system to skip repetitive tasks.
Authentication and authorization support.
With Taipy, you can create web applications without needing to dive deep into HTML, CSS, and JS. It offers Taipy Cloud, a platform that simplifies web app development and deployment.

“Data and AI algorithms into production-ready web apps”

With Taipy, you can bring your web app ideas to life with ease, even if you’re not an expert in web development.

[Read More](https://codemagnet.in/2024/03/08/how-to-bring-your-data-ai-algorithms-into-production-ready-web-app-using-python/)