/NotreDameTweetGen

Always wanted to read Victor Hugo's the hunchback of Notre Dame, but don't have the time? Why not let a Markov chain digest it for you and feed you the ideas in tweet-sized bites? This applies a second order Markov chain and basic data cleaning techniques to process a known corpus and imitates English grammar.

Primary LanguagePython

Tweet Générateur de Notre-Dame de Paris

Content

Always wanted to read Victor Hugo, but don't have the time 🤷 ? Want to make your friends think you've read this famous author, even if you haven't?

Why not let a Markov chain digest his work for you and feed you the ideas in tweet-sized bites?

This app uses the tweet generator tutorial for Make School's CS 1.2 course ✏️ to make self-built data structures and provide you with interesting, computer generated sentences worthy of a Tweet 📲 .

Deployment

You can find my tweet generator at https://notre-dame-de-paris.herokuapp.com 👩🏾‍💻 . Click on the link and see for yourself!

Running

If you would like to run this project locally on your own device, after cloning it, enter your virtual environment and enter "flask run" in the root folder in your CLI to see the flask app. It is hosted at http://http://127.0.0.1:5000/. If you would just like to run the Markov chain sentence generator, enter "python3 markov.py".

Data Structures and Concepts Explored

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Modules

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