Random films from IMDb

imdb.py

import argparse
import webbrowser

import numpy as np
import pandas as pd

if __name__ == '__main__':
    parser = argparse.ArgumentParser()
    parser.add_argument('--csv-file', default='./WATCHLIST.csv')
    parser.add_argument('--n', default=5)
    parser.add_argument('--min-rating', default=None)
    parser.add_argument('--max-runtime', default=None)
    parser.add_argument('--min-year', default=None)
    parser.add_argument('--max-year', default=None)
    args = parser.parse_args()

    watchlist = pd.read_csv(args.csv_file)
    columns = {'Title': 'title', 'IMDb Rating': 'rating', 'Runtime (mins)': 'runtime',
               'URL': 'url', 'Title Type': 'type', 'Year': 'year'}
    watchlist = watchlist.reindex(columns.keys(), axis='columns').rename(columns=columns)
    watchlist = watchlist.loc[~watchlist.rating.isna()]

    if args.min_rating is not None:
        watchlist = watchlist.loc[watchlist.rating >= args.min_rating]
    if args.max_runtime is not None:
        watchlist = watchlist.loc[watchlist.runtime <= args.max_runtime]
    if args.min_year is not None:
        watchlist = watchlist.loc[watchlist.year >= args.min_year]
    if args.max_year is not None:
        watchlist = watchlist.loc[watchlist.year <= args.max_year]

    rng = np.random.default_rng()
    choice = watchlist.iloc[rng.choice(len(watchlist), size=args.n, replace=False)]

    print('Picked from {} movies :'.format(len(watchlist)))
    for _, row in choice.iterrows():
        print('\t' + row.title)
        webbrowser.open(row.url)