BingeWatch

This project consists of developing a command-line tool that stores and tracks favorite TV series in a local database, monitors new episodes, checks YouTube for related trailers/uploads, and notifies the user based on preferences and scores.

Phase 1: Database Design and Command Parsing

Implement persistent storage and basic command parsing.

Create DB schema (name, IMDB link, last episode, last watch date, score, snooze flag)
Implement commands: add, delete, update score, snooze/unsnooze
Validate inputs and log errors

Functional Output: Valid commands update the database successfully.

Phase 2: IMDB Episode Fetching Logic

Retrieve episode lists from IMDB without external libraries beyond urllib/html.parser.

Fetch IMDB HTML
Extract episode numbers and dates
Detect new episodes vs. last watched

Functional Output: Tool identifies which episodes are new for each series.

Phase 3: Episode Ranking and Filtering by Score

Filter and sort new episodes based on user-defined scores.

Assign priority by score
Exclude snoozed series
Sort new episodes descending by score

Functional Output: List of new episodes ordered by relevance.

Phase 4: YouTube Trailer & Upload Discovery

Search YouTube pages (HTML only) for trailers or uploads related to specific episodes.

Build search queries
Parse HTML results
Extract video titles/URLs

Functional Output: Episode-specific trailer/upload list is generated.

Phase 5: Notifications and Change Detection

Track previously found videos and notify on new uploads.

Compare new vs previous YouTube results
Generate notifications for new items
Log findings and timestamp them

Functional Output: User receives notifications only for newly discovered videos.

Finalize listing output and improve logs/UX.

Implement list to show all new episodes (excluding snoozed)
Add detailed logs for operations
Polish CLI messages and error handling

Functional Output: The tool lists all new episodes, applies filters, logs operations, and behaves reliably.