Batch Movie Info Downloader: Fast Metadata Fetcher for Your Film Library

Batch Movie Info Downloader: Fast Metadata Fetcher for Your Film Library

What it is

• A utility that scans a collection of movie files and retrieves metadata (title, year, synopsis, cast, poster, genres, runtime, ratings) in bulk from online databases like TMDb, IMDb, or OMDb.

Key features

• Batch scanning: Process hundreds or thousands of files in one run.
• Multiple sources: Query TMDb, OMDb, IMDb, TheMovieDB, or local NFO files with fallback order.
• Filename parsing: Extracts title/year from filenames (configurable patterns) and supports manual mapping for ambiguous cases.
• Poster download & resizing: Fetches high-resolution covers and creates thumbnails.
• Save formats: Export metadata to NFO, JSON, CSV, or write into media manager-compatible formats (Kodi, Plex).
• Rate limiting & caching: Respect API limits, use local cache to avoid repeated requests.
• Dry-run & logging: Preview changes and produce detailed logs for troubleshooting.
• CLI + GUI: Command-line for automation and optional GUI for manual review.

Typical workflow

1. Point the tool at your movie folder(s) or supply a list of files.
2. Tool parses filenames and queries configured APIs.
3. Presents matches (auto-accept with confidence threshold or prompt for review).
4. Downloads posters and writes metadata files beside each movie or to a central database.
5. Optionally updates media server databases (Plex/Kodi) or syncs with a library manager.

Best practices

• Use an API key for TMDb/OMDb to improve accuracy and avoid rate limits.
• Run a small sample first to tune filename parsing patterns.
• Keep a local cache and enable incremental mode for large libraries.
• Set a conservative confidence threshold to avoid incorrect matches; manually review low-confidence items.
• Back up existing NFO/metadata before overwriting.

Implementation notes (developer-focused)

• Filename parsing: use regex patterns and fuzzy matching (Levenshtein) against API search results.
• Parallel requests: use worker pools with adaptive concurrency based on API response times.
• Caching: store search results + resolved IDs with TTL; persist to SQLite or lightweight key-value store.
• Image handling: download originals, generate multiple sizes, and deduplicate by checksum.
• Error handling: exponential backoff for 429/5xx, record failures for retry.

Use cases

• Organizing ripped DVDs/Blu‑rays into a media server.
• Creating a searchable offline movie catalog.
• Preparing metadata for media players or archival purposes.
• Enriching a dataset for machine learning or recommendation experiments.

Limitations & risks

• Ambiguous filenames may yield incorrect matches without manual review.
• API rate limits and occasional missing data (especially for obscure titles).
• Copyright considerations when storing and distributing poster images—check source terms.

Quick checklist to get started

• Obtain API keys (TMDb/OMDb).
• Configure filename patterns and target folders.
• Run a 50–100 file test with auto-accept off.
• Review results, adjust parsing/confidence, then run full batch.