- Created a web app that provides quotes from the internet based on your mood
- It makes use of an API to scrape quotes from the internet
- The app has 110 quotes at any given time that it uses NLP to categorize
- Sorted the quotes using VaderSentiment SentimentIntensityAnalyzer, from most pleasant to most unfriendly
- Used requests to get the quotes from the API
- On a mobile device, you can swipe through the app!
- I made a web app using Flask. Try it!!! It also works well on mobile.
Python Version: 3.10.5
Packages: pandas, NumPy, sklearn, matplotlib, seaborn, vaderSentiment, requests, nltk
For Web Framework Requirements: pip install -r requirements.txt
API: https://github.com/lukePeavey/quotable
Flask Productionization: https://quotes-web-app-nlp-ml-powered-7d4f6b1a0e84.herokuapp.com/
I used an API command to scrape exactly 110 quotes at a time that were no more than 262 words long:
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Aim for the moon. You might hit a star if you miss. --Stone, Clement
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We can do anything we want to if we stick to it long enough. --Helaine Keller
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You know you're in love when you can't fall asleep because reality is finally better than your dreams. --Dr. Seuss
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...and many others
Getting the quotes, transforming them, and displaying them on the web app:
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Got quotes using requests
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Converted them to JSON before converting them to a data frame of quotes and authors
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Analyzed the quotes using the SentimentIntensityAnalyzer
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Arranged them according to their feelings
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Developed the logic to display quotes that are lighter or darker depending on the user's swipe
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Envato Elements is where I got the bottom graphics (paid)
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Used the website Canva to create the banner
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Handled the HTML and CSS for the quotes
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Swiping was made possible through Javascript code
https://quotes-web-app-nlp-ml-powered-7d4f6b1a0e84.herokuapp.com/
