guessit-js

Extract metadata (title, year, season, episode, codec, language, etc.) from media filenames — TypeScript port of Python guessit.

Live Demo · API Docs · npm

Features

• 100% compatibility with Python guessit (1036/1036 fixtures passing) — and more correct in places: ships fixes for 32 upstream guessit bugs that Python still has (see Differences from Python)
• 3.5x faster than Python (6.87ms vs 23.86ms per parse)
• 50 properties detected: title, year, season, episode, resolution, codec, language, and more — with a machine-readable schema
• Single dependency (rebulk-js)
• Dual format: ESM and CommonJS
• TypeScript: full, precise type definitions (typed GuessItResult, enum'd value fields)
• WASM: runs in any WASI-compatible runtime, bit-identical to the JS build

Install

npm install guessit-js

Usage

import { guessit } from 'guessit-js';

const result = guessit('The.Dark.Knight.2008.1080p.BluRay.x264-GROUP.mkv');
// {
//   title: 'The Dark Knight',
//   year: 2008,
//   screen_size: '1080p',
//   source: 'Blu-ray',
//   video_codec: 'H.264',
//   release_group: 'GROUP',
//   container: 'mkv',
//   type: 'movie'
// }

// Short titles are handled correctly too:
guessit('X2.2003.720p.DSNP.WEB-DL.DDP5.1.H.264-EVO.mkv');
// { title: 'X2', year: 2003, screen_size: '720p',
//   streaming_service: 'Disney+', source: 'Web', ... }

CommonJS

const { guessit } = require('guessit-js');
const result = guessit('Breaking.Bad.S01E02.720p.BluRay.x264-DEMAND.mkv');
console.log(result.title);   // 'Breaking Bad'
console.log(result.season);  // 1
console.log(result.episode); // 2

Options

guessit('file.mkv', { type: 'episode' });
guessit('my 720p show S01E02', { expected_title: ['my 720p show'] });
guessit('file.mkv', { allowed_languages: ['en', 'fr'] });
guessit('file.mkv', { excludes: ['release_group'] });

Detected Properties

| Category | Properties | |----------|-----------| | Title | title, alternative_title, episode_title | | Episode | season, episode, episode_details, episode_count, season_count, absolute_episode, disc, part | | Date | year, date | | Video | screen_size, aspect_ratio, frame_rate, video_codec, video_profile, color_depth | | Audio | audio_codec, audio_profile, audio_channels, audio_bit_rate | | Source | source, streaming_service | | Release | release_group, edition, other, proper_count | | File | container (video / subtitle / archive / image / nfo / torrent / nzb), mimetype, size, crc32, uuid | | Metadata | language, subtitle_language, country, type |

Output schema

The result is fully typed — import GuessItResult for autocomplete and type-checking:

import { guessit, properties, GUESSIT_SCHEMA, type GuessItResult } from 'guessit-js';

const r: GuessItResult = guessit('The.Dark.Knight.2008.1080p.BluRay.x264-GRP.mkv');
r.source;  // typed as the closed enum: "Blu-ray" | "Web" | "HDTV" | …

properties();        // { source: ["Blu-ray", "Web", …], type: ["episode","movie"], … } for all 50 properties
GUESSIT_SCHEMA.source.enum;  // the allowed values, programmatically

• properties() — returns every emittable property with its possible values (value-constrained props list their full enum; free/computed props list [null]), mirroring Python guessit's properties().
• GUESSIT_SCHEMA — the machine-readable schema (type, cardinality, enum) for all properties.
• docs/output-schema.json — a JSON Schema (draft-07) of the output, for validating results or generating clients in other languages.

Regenerate the schema (after parsing changes) with npm run schema. A test (test/schema.test.ts) guarantees it never goes stale — every value emitted across the corpus must be in the schema.

REST API

npm start  # port 3847
curl "http://localhost:3847/api/guessit?filename=Movie.2024.1080p.mkv"

WASM

For non-JS environments (Rust, Go, C++, edge compute). Uses Javy (QuickJS → WASM).

npm run wasm
echo '{"filename":"Movie.2024.1080p.mkv"}' | wasmtime wasm/guessit.wasm

The WASM build is bit-identical to the JS build across the entire test corpus (1026/1026, including accented titles) — verified by test/wasm-full.test.ts.

Differences from Python guessit

guessit-js is a faithful port (1036/1036 fixtures match Python 3.8.0), but it is not bug-for-bug identical — where Python has a genuine parsing bug, guessit-js is corrected. Highlights:

• 32 upstream guessit bugs fixed that Python still gets wrong — e.g. Us.2019 (title vs country US), The.Collector (title vs edition), X2.2003… (short title), grown-ish…[eztv] (hyphenated title split), cd-matching mid-hash, and source/codec/extension tokens leaking into release_group/title. Full ledger: docs/upstream-issues.md.
• More properties / better detection: imdb_id/tmdb_id/tvdb_id, volume, archive & image containers (.rar/.7z/.jpg…), artwork classification (poster/fanart → other), VR / Opening-Ending credits, month-name dates, CJK season/episode markers, and detection of Telugu/Spanish that Python misses.
• Typed, schema-described output: a precise GuessItResult interface, a complete properties() (Python's is partial), and a JSON Schema.
• No Python runtime: zero runtime dependencies, ESM + CJS + WASM, ~3.5x faster.
• Intentional divergences (cases where guessit-js is more correct than Python) are catalogued per-example in docs/python-parity.md.

Known issues

• Music files are not supported (#599): Artist - Album/01 Track.flac is parsed with the video vocabulary (title / alternative_title), not artist/album/track. Out of scope for now.
• No composite quality field (#802): screen_size, source and video_codec are returned separately, not combined into one string (the request is underspecified).
• A few ambiguous anime conventions remain (#690/#696/#747): e.g. Re ZERO …- Season 2 - 15, romaji + (English title) — no unambiguous correct parse.
• 12 debatable cases vs Python (neither clearly right) are listed under "② NEUTRAL" in docs/python-parity.md.

Performance

Warm per-parse, measured on one machine (absolute numbers are hardware-dependent — the live demo times it in your browser):

| Runtime | ms/parse | Notes | |---------|----------|-------| | Browser (V8) | ~2–3 ms | fastest; JIT-compiled | | Node.js 22 (V8) | ~4.4 ms | ~3.5× faster than Python (same machine) — recommended for servers/CLI | | Python 3.8 | ~15.5 ms | reference | | WASM (QuickJS/Javy) | ~35 ms warm · ~150 ms cold | for portability, not speed (see below) |

About the WASM build. It exists so you can run guessit in environments without a JS engine (Rust, Go, C/C++, edge/WASI runtimes). Javy compiles the bundle to QuickJS, which is an interpreter (no JIT), so per-parse compute (~35 ms) is slower than V8 and even than Python — that's inherent to the engine, not the code. If you want speed, use the Node/browser build (V8). If you need WASM, the levers that actually help:

• Amortize startup — instantiate the module once and parse many filenames; most of the ~150 ms single-shot cost is wasmtime + module init, not parsing.
• AOT-compile the module (wasmtime compile guessit.wasm -o guessit.cwasm) to skip per-run JIT of the wasm itself (~30 ms off cold start).
• The ~35 ms warm floor is QuickJS interpretation; beating it would require a JIT-capable WASI JS engine (none production-ready) or a native port — out of scope. WASM correctness is bit-identical to the JS build.

License

LGPL-3.0