Problem statement: MUBI has a great collection of art house movies, but pretty limited filtering functionalities, it also misses relevant movie information for my decision making such as MetaCritic's score (aka metaScore)
Goal: make Mubi's collection easy to query by converting it into a structured dataset (CSV)
Example of queries (e.g. show me Comedies with MetaScores higher than 80 available on Mubi.)
- Extract list of movies available to watch on Mubi, query MetaCritic to access meta_score, and stores results as a table into a csv file
pip install -r requirements.txt
python main.py
When executing the above, you will:
- crawl all movies available on Mubi (more specifically, all movies in the top 40 collections displayed on https://mubi.com/showing),
- query metacritic's APIs to get metascores
- and store all the results in a CSV file named
data/{current_date}_mubi.csv
| field | type | example value | source |
|---|---|---|---|
| title | str | Drug War | mubi |
| duration | int | 106 | mubi |
| year | int | 2012 | mubi |
| web_url | str | https://mubi.com/films/drug-war | mubi |
| critic_review_rating | float | 4.85 | mubi |
| director | str | Johnie To | mubi |
| genres | list[str] | ['Crime'] | mubi |
| historic_countries | list[str] | ['Hong Kong', 'China'] | mubi |
| meta_score | int | 86 | metacritic |