💻 Prompts for lessons 7-10:
📚 L7: Wikipedia Analysis App – Data Analysis
Write a script that takes in a wikipedia category as a command line argument and outputs the cumulative frequency of non-common words across all of the pages in that category, and then run it on "Large_language_models." Use the MediaWiki API.
📚 L8: Wikipedia Analysis App – Caching
[First prompt] Create a local cache of page results so that we aren’t rerunning the retrieval logic for the same category [Second prompt] Create a local cache of the script’s results so that we aren’t rerunning the processing logic for the same category
📚 L9: Wikipedia Analysis App – Fullstack App
Create a webpage that loads from the results cache (if available, otherwise computes the frequencies from scratch) and displays a word cloud where the sizes of the words are proportional to frequency. Use HTML, javascript, and Flask. [Command] create a ColorPalette class that would contain 6 hex colors, and a bunch of common color palettes that extend the class
Integrate @get_all_color_palettes into the word cloud app. Make the color palettes selectable in a drop down and display the colors being used.
📚 L10: Wikipedia Analysis App – Polish
Add raw frequencies to the app as shown in the image.
🧑💻 Repos used in the course
📚 L3 Repo – Fixing Tests Automatically
📚 L6 Repo – Understanding Large Codebases