For my project I used a React frontend with a Flask backend and a sqlite database. I used React as you requested. I used Flask and sqlite because I was a bit familiar with them already, and they are very easy to use given the time constraint. I used a template to start with for my React frontend which is located in the “WebFrontEnd” folder which contains a readme about where it came from. Other than that template I just used documentation from the various libraries and frameworks.

I would also ask that you view my 1 closed PR on this repo to see how I document my pull requests.

See the below information for descriptions on the data processing I did on the csv.

Thank you for your consideration,

Will

import pandas as pd
import sqlite3
import uuid

I used pandas for most of my data processing and to ingest the csv as you requested.

con = sqlite3.connect("movieData.sqlite")
cur = con.cursor()

moviesDf = pd.read_csv("movie_plots.csv")
moviesDf

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I did some light data processing. I changed the column names to be a bit more friendly to coding and I added a UID.

mRename = moviesDf.rename(columns={"Release Year": "ReleaseYear", "Origin/Ethnicity": "Origin", "Wiki Page": "WikiPage"})

mRename['id'] = [uuid.uuid4() for _ in range(len(mRename.index))]
mRename['id']= mRename['id'].astype('str')
mRename

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mRename.to_sql("movie", con, index=False)

movieData = pd.read_sql_query("SELECT * from movie", con)
movieData

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con.close()