This script downloads data from Oscar movies based on a list of awards nominees.

This project is a work in progress, expect changes and unstability.

The script expects and array with an object for each award with the following format:

 {
    shortName,
    winner,
    nominees: [
      { title},
      { title},
      { title},
      { title},
      { title},
      ...
    ],
  }

Here is an example:

 {
    shortName: "filme",
    winner: "CODA",
    nominees: [
      { title: "Belfast" },
      { title: "CODA" },
      { title: "Don't Look Up" },
      { title: "Drive My Car" },
      { title: "Dune" },
      { title: "King Richard" },
      { title: "Licorice Pizza" },
      { title: "Nightmare Alley" },
      { title: "The Power of the Dog" },
      { title: "West Side Story" },
    ],
  }

The script uses data from two sources:

• The IMDb datasets
• The OMDb API

So you need a valid API Key for the OMDb API, and to download the following IMDb datasets:

• title.akas.tsv.gz: Includes name translation for the movies. You can filter for only your region using ripgrep. rg -e "\tBR\t" title.akas.tsv > titles.akas.br.tsv
• title.basics.tsv.gz: Includes data from all IMDb titles. To filter for only movies, use rg -e "tt[0-9]*\tmovie" title.basics.tsv > movies.tsv
• name.basics.tsv.gz: Includes information for all crew members

You need to manually re-include the header line if you filter using ripgrep

Total size of those files should be around 700mb after filtering (695mb from name.basics). I'm looking for suggestions on how to filter and reduce the size of those files.

You need to import those datasets to a MongoDB database. MongoDB Compass can easily import from tsv files. The following database structure is expected:

-> imdb           // Database
|-> akas          // Collection from title.akas data
|-> movies        // Collection from title.basics data
|-> names         // Collection from name.basics data