A deep dive walkthrough into various aspects of Streamlit library. The commented sections in the main.py file is expected to be uncommented one at a time to go well with the talk/PPT. We also walkthrough XKCD comic fetcher implementation. Who doesn't love Xkcd comics? They are the most relatable and quirky comics I have come across wrt programming and linguistics. While there are 2500+ of them, won't it be nice to fetch a comic relevant to a scenario and share it with friends? That is exactly what I came up with.
Give a keyword, and get the xkcd comic in response. Hope you like it as much as I enjoyed making it!
Live app: xkcd-fetcher.herokuapp.com
Dataset used: xkcd Comic Dataset
Libraries used: Pandas, Streamlit
Ping Siddharth on Twitter, Linkedin, or simply write an e-mail.
For suggestions, improvements you can also just raise an issue or request a pull request!
All image rights reserved to the very awesome xkcd
under Attribution-NonCommercial 2.5 License.
