74c833b62c19f09c905d77e1cb25edad73f97370
Page load indicators
Oscars Pool 2026
Little nodejs + mongodb app that I hack together with ChatGPT and Cursor to keep track of watched movies for an incoming Oscars Pool with some friends.
Features
- User accounts: register, login, JWT auth
- Simple registration verification via
DOG_NAMES - Mark nominees as watched (per user), with watched date
- Browse movies by Oscar year + API for available years
- User stats: watched count/ratio and watched titles
- Movie details pulled from OMDb (title/plot/rating/poster) via IMDb ID
- Admin movie management: add, edit (optionally refresh from OMDb), delete
- Built-in player page with multiple source options (VOD link, direct video file, embed)
- Resume playback: per-user playback progress saving (time/duration)
- Global settings: active Oscar year, “completion” modal content for checklist
- Password flows: admin temp password reset + forced change on next login
- Version endpoint backed by latest GitHub commit (cached)
Setup
Create a .env file at the project root (same folder as package.json).
Minimal steps:
npm install
node index.js
Add this to your .env (required: MONGO_URI, JWT_SECRET):
# required
MONGO_URI=mongodb://127.0.0.1:27017/oscars-pool # MongoDB connection string
JWT_SECRET=replace-with-a-random-string # JWT signing secret (auth)
# optional
DOG_NAMES=woof,WOOF,Woof # simple registration "verification"
OMDB_API=your_omdb_key # OMDb API key (movie info)
GITHUB_OWNER=quoije # version history
GITHUB_REPO=oscars-pool # version history
Generate a good JWT_SECRET:
openssl rand -hex 32
Database (MongoDB)
This app uses MongoDB via Mongoose. Provide a connection string in MONGO_URI.
- Use MongoDB Atlas (recommended) or a local MongoDB instance.
MONGO_URIexamples:- Atlas:
mongodb+srv://USER:[email protected]/<dbName>?retryWrites=true&w=majority - Local:
mongodb://127.0.0.1:27017/<dbName>
- Atlas:
- Collections are created/managed automatically from the models in
models/(e.g.User,Movie,Setting,PlaybackProgress).
Languages
JavaScript
71.5%
HTML
19.8%
CSS
4.8%
Python
3.9%
