Store your TMDB_BEARER_TOKEN and DATABASE_URL in a local. This may result in less metadata in your database for fallbacks and such, but the project is explicitly designed to be re-run regularly so your data remains valid and up-to-date, relying on these third-parties to deal with data drift. This format aims to be as compact as possible while still including the most important metadata, so for certain fields like the trailer, we choose the best possible YouTube video according to a set of heuristics and ignore any other related videos. This includes most English movies as well as many of the most popular foreign films. We also compute some useful custom fields like foreign, which is a flag for whether or not most Western audience members would recognize the movie. Rotten Tomatoes critic and audience scores.In addition to basic movie metadata, most movies also include: "plot": "The lives of two mob hitmen, a boxer, a gangster and his wife, and a pair of diner bandits intertwine in four tales of violence and redemption. Movies are transformed into the following format, which combines metadata from TMDB, IMDB, Rotten Tomatoes, and FlickMetrix. All scripts are idempotent, so you should be able to re-run them whenever you want to refresh your data. This includes difficult-to-access data like IMDB ratings, Rotten Tomatoes audience & critic scores, and YouTube trailers.Įverything is handled including data fetching, normalization, cleaning, and filtering.
#INTERNET MOVIE DATABASE FULL#
This project resolves a full set of movies from TMDB and IMDB in batches, storing them into a Postgres database using Prisma. Populate Rotten Tomatoes Movies (Optional) Populates a high quality database of movies from TMDB, IMDB, and Rotten Tomatoes.
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