🎬 Movie Database App

A command-line tool to manage a personal movie collection: list, sort, filter, fuzzy-search, and rate your movies and visualize stats.

Features

• List all movies, sorted by rating or by release year (asc/desc)
• Filter by minimum rating and/or a release-year range
• Fuzzy title search — custom Levenshtein-distance implementation, no external libs
• Pick a random movie for tonight
• Add, update, delete movies
• Stats: average & median rating, best- and worst-rated movie(s)
• Generate a ratings histogram and save it to disk (matplotlib)

Installation

git clone https://github.com/Tobbyte/movie_db.git
cd movie_db
pip install -r requirements.txt

Requires Python 3.10+ (uses X | None type hints).

Usage

python movies.py

Navigate with the on-screen menu (0–11).

Project structure

movies.py                 # entry point, CLI menu loop
app_config/
  app_config.py            # constants: menu items, colors, rating bounds, file paths
data_handling/
  movie_storage.py          # CRUD against the JSON "database"
  data_provider.py          # sorting & filtering
  movie_search.py           # search orchestration (exact + fuzzy)
  my_fuzzy_search.py        # custom Levenshtein-distance fuzzy matcher
helpers/
  helpers.py                 # input validation & formatted output
  histogram.py                # matplotlib ratings histogram
user_input/
  user_input.py               # all prompts + validation loops
data_dir/data.json         # the "database" (title -> {rating, release})

Data format

{
  "Movie Title": {
    "rating": 9.5,
    "release": 1991
  }
}

Known limitations

(documented in the code as intentionally out of scope for this version)

• No existence-check before add/update/delete — e.g. adding an existing title just raises an error instead of offering to update it
• Fuzzy search is only used for the search menu, not for update/delete
• "Clear screen" is a print-based hack, not a real terminal clear

Fuzzy search specifically: ( --> unchanged from movie phase 1 <-- )

• Naive Levenshtein distance, computed against every DB entry — no indexing or other optimization
• A match requires at least one word in the search term and the compared title to share a first letter; otherwise it's excluded even if it's within the distance threshold
• Only "the" is filtered out as a filler word (excluded_terms); the list isn't configurable/extensible yet
• Searching for a filler word itself (e.g. "the") won't reliably return every title containing it, since the edit-distance threshold still applies

Notes

Built with ❤️ and without AI code generation or autocomplete (aside from IntelliSense).^*

^* ... except a draft of this readme.