mazini

Arabic verb conjugator for JavaScript / TypeScript. Give it a root and a pattern (وزن) and it returns every form of the verb: the past, the three non-past moods, the imperative, active and passive, in all thirteen persons, plus the participles and the مصدر — 119 slots, fully vocalised, with the attested alternative spellings where Arabic has them.

It is a pure-TypeScript port of Arabic Wiktionary's conjugation engine, وحدة:ar-verb (itself descended from Module:ar-verb on English Wiktionary), and it is verified two ways:

• Against the book. Every one of the 15,549 printed forms of the 462 paradigms in أنطوان الدحداح, معجم تصريف الأفعال العربية — the reference work on the subject, transcribed and published as the ar-conjugation dataset — is among the forms the engine generates.

• Against the original. For 7,851 inputs (every root × pattern combination of a 154-root grid, plain, passive and assimilated, plus every book verb) the output is byte-identical to the Lua module's: 741,188 forms, footnotes and metadata fields, and the same 201 rejected inputs.

• Pure JS, zero dependencies, no data files. ESM + CommonJS, typed. Node 18–24 and every browser.

• ~90 KB, nothing downloaded at runtime.

Named after أبو عثمان المازني (Abū ʿUthmān al-Māzinī, d. 863), whose كتاب التصريف is the first standalone treatise on Arabic morphology.

Live demo

forzagreen.github.io/mazini-js — conjugate any verb in the browser, and run the 15,549 book assertions yourself.

Install

npm install mazini

Usage

import { conjugate } from "mazini";

const v = conjugate("كتب", "فعَل يفعُل");
v.slots.past_3ms[0].form; // "كَتَبَ"
v.slots.ind_3ms[0].form; // "يَكْتُبُ"
v.slots.imp_2fs[0].form; // "اُكْتُبِي"
v.slots.ap[0].form; // "كَاتِب"
v.verbType; // "فعل ثلاثي مُجرَّد صحيح سالم"

// A pattern can be given by its Arabic name or its form code; both take the same options.
conjugate("قول", "أفعل").slots.past_3ms[0].form; // "أَقَالَ"
conjugate("علم", "V").slots.vn[0].form; // "تَعَلُّم"
conjugate("كتب", "I", { vowels: { past: "a", nonpast: "u" } }); // same as "فعَل يفعُل"

// Two switches, the same ones {{تصريف}} takes on the wiki:
conjugate("أخذ", "افتعل", { reduced: true }).slots.past_3ms[0].form; // "اِتَّخَذَ" (assimilated affix)
conjugate("علم", "فعِل يفعَل", { passive: true }); // a full personal passive for a verb the engine would default to impersonal

The result's slots is a map from slot name (past_3ms, ind_pass_2fp, juss_1p, imp_2fp, ap, pp, vn, …) to the list of forms for that slot, each { form, footnotes }; a slot the verb lacks is absent. Alongside it: lemma, verbForm, wazn, radicals, weakness, passive (the passive type), irregular, morphPatterns, hasActive / hasPassive, uncertainSlots (slots shown as "?", i.e. a form-I مصدر or participle the root alone cannot predict), verbType and classification.

Roots may be written كتب, ك ت ب or ك_ت_ب; hamza seats fold to ء and ى to ي. Bad input throws a MaziniError whose code is stable (bad_root, unknown_wazn, reduced_not_applicable, …).

import { WAZNS, SLOTS, PERSON_NUMBERS, classifyTriliteralVerb, loose } from "mazini";
WAZNS; // the 22 patterns: name, form code, vowels, مجرد/مزيد class
classifyTriliteralVerb("ق", "و", "ل"); // "معتل أجوف واوي"
loose("فَعَلَا") === loose("فَعَلا"); // the comparison the book tests use

What it does not do (yet)

It conjugates from a root and a pattern, which is what every caller on Arabic Wiktionary does. The Lua module can also take a written, vocalised verb and infer its root (infer_radicals), accept per-slot overrides, and render the wikitext table; none of that is ported. The subjunctive, jussive, participles and مصدر are generated but are outside the book's tables, so they are verified only against the Lua module, not against print.

Development

npm install
npm test            # hamza, book, golden, loose, api
npm run build:demo && npm run serve:demo
python3 tools/gen_golden.py   # regenerate test/fixtures/ from ../ar-wiktionary-modules (needs luajit)

test/fixtures/ is generated upstream by ar-wiktionary-modules' tools/port_fixtures.py: golden.jsonl.gz (the module's output for 7,851 inputs), hamza.jsonl.gz (every hamza-seating call it made), loose.jsonl.gz (the normaliser's parity set), book/ (the 462 paradigms as CSV) and MANIFEST.json (the upstream commit).

A Python port with the same API and the same tests: mazini.