Netflix Writer

This repo contains source code for ... Netflix AI Greenlight Challenge: Can Data Science Predict the Next Hit Drama?

Quickstart

1. Register for Kaggle and get a Kaggle API Key

2. Install required system packages for your operating system: Windows, macOS, Linux

3. Initialize your environment. This includes creating and activating a Python virtual environment, and then downloading data files for Netflix, IMDb and The Movie Database (TMDB). The final dataset will be located at ./netflix/db/netflix_enriched_dataset.csv.

   The setup process will take between 5 and 15 minutes depending on your compute device and your Internet connection.

   make python-init
   make run

Data Sources

Netflix REST API

Every Tuesday, Netflix publishes four global Top 10 lists for films and TV: Film (English), TV (English), Film (Non-English), and TV (Non-English). These lists rank titles based on weekly hours viewed: the total number of hours that members around the world watched each title from Monday to Sunday of the previous week.

Each season of a series and each film is considered on their own, so you might see both Stranger Things seasons 2 and 3 in the Top 10. Because titles sometimes move in and out of the Top 10, there is also the total number of weeks that a season of a series or film has spent on the list.

Netflix also publishes Top 10 lists for nearly 100 countries and territories (the same locations where there are Top 10 rows on Netflix). Country lists are also ranked based on hours viewed but don’t show country-level viewing directly.

Finally, Netflix provides a list of the Top 10 most popular Netflix films and TV (branded Netflix in any country) in each of the four categories based on the hours that each title was viewed during its first 28 days.

IMDb Non-Commercial Datasets

Subsets of IMDb data are available for access to users for personal and non-commercial use. You can hold local copies of this data, and it is subject to our terms and conditions. Please refer to the Non-Commercial Licensing and copyright/license and verify compliance.

The Movie Database

The TMDB (The Movie Database) is a widely-used resource for movie and TV show data, providing valuable information such as ratings, plot summaries, and more. This dataset contains a collection of 150,000 tv shows from the TMDB database, collected and cleaned.

Polti's Thirty-Six Dramatic Situations

The Thirty-Six Dramatic Situations is a descriptive list which was first proposed by Georges Polti in 1895 to categorize every dramatic situation that might occur in a story or performance.[1] Polti analyzed classical Greek texts, plus classical and contemporaneous French works. He also analyzed a handful of non-French authors. In his introduction, Polti claims to be continuing the work of Carlo Gozzi (1720–1806), who also identified 36 situations.

Completely Remove This Project

make tear-down
deactivate

Helpful Commands

source venv/bin/activate
which python3
which pip3
python --version # you should see Python 3.13.x
pip --version # you should see pip 25.3.x

Support

Please report bugs to the GitHub Issues Page for this project.