Streamlit to Build & Deploy Apps like a Data Scientist

Siddharth Gupta (~sidgupta234)




Do you ever find it complicated to learn the complexities of a traditional web framework to push your data science work online? Worry no more! Streamlit (open-source app framework) might help speed things up as it is designed for the required purpose - creating beautiful data-related web apps that can be deployed in minutes. In the hands-on tutorial, we’ll go through various features of Streamlit and build a small lyric fetcher app based on the available dataset (which I have curated and will be sharing the Github link before the talk) of around 24K Billboard top-100 songs.

In the first section, I will discuss with you the basics of Streamlit and some examples of applications made through it. I will also show you the expected final version of what we’ll create during the tutorial.

In the second section, we will ensure that all libraries are set up correctly in your system, and we can run a small “Hello World” code on the local server.

In the third section, we will build our application step-by-step by creating a layout and adding the required elements. These elements would include two drop-down buttons for selecting the song & artist for which we want lyrics, A lyric showcasing column, and a word cloud visualization of the respective lyrics.

In the last segment, I will show you how we can deploy the app online using Heroku and Streamlit, which you can further attempt after the talk on your own.


A beginner level of understanding of HTML, Python, and libraries such as Numpy, Matplotlib, and Pandas should be enough. Ensure you have the said libraries (and wordcloud python library), an editor (Sublime or VSCode), and Streamlit installed in your system.

Content URLs:

Slides and code will be a modified version of the ones present here.



Speaker Info:

Data Analyst at Godrej Capital, Siddharth is interested in Programming, Deep Learning, and Academia! They write Twitter threads across the three topics. When not consumed with work, they post YouTube videos, make Discord bots, play around GitHub or try threading some words on Medium Blog.

Speaker Links:

Github Linkedin

Section: Data Science, AI & ML
Type: Workshops
Target Audience: Intermediate
Last Updated: