esMorph

A fast Spanish morphological analyzer written in Rust with a Python API

Documentation · PyPI · crates.io · Español

esMorph is a morphological analyzer of Spanish: a Rust core with a Python API. For a word form it finds the analyses in a dictionary built from Wiktionary - the lemma, the part of speech and the Universal Dependencies features - orders them by probability and builds the forms of the word: conjugation, gender and number.

It analyzes 1.2 million tokens per second from Python, 28 times faster than spaCy, and lemmatizes as fast as simplemma, whose lemmas are right less often on the UD test sets of AnCora, PUD and COSER. Parts of speech, features and lemmas follow the UD guidelines and the conventions of the AnCora treebank, so the results can be compared with spaCy, Stanza and other UD tools.

• Analyzer - the analyses of a word form by probability, lists of words and lemmatization, checking a word form against the dictionary
• Universal Dependencies - parts of speech, features and lemmas by the UD guidelines and the AnCora conventions
• Verbs with clitics - a verb with enclitic pronouns and its words: dámelo is da + me + lo
• Tokens out of the dictionary - punctuation, numbers, ordinals, Roman numerals, names, addresses and abbreviations by rules
• Unknown words - analyses by the ending, a hyphen or a prefix, and the forms of guessed words
• Inflection - the forms of a lexeme and the form with given UD features
• Comparison - accuracy, inflection and speed compared with simplemma, spaCy, Stanza, ablaut and verbecc

Installation

Python 3.11 or newer is required.

pip install esmorph

Or with uv:

uv add esmorph

Wheels are built for Linux (Alpine included), macOS and Windows and for the free-threaded Python 3.14t; Rust is not needed to install them, and the dictionary is in the package. On other platforms pip builds the package from source, which requires Rust 1.88 or newer. See the Installation page.

For Rust there is the crate esmorph with the dictionary (cargo add esmorph; the documentation is on docs.rs).

Quick start

>>> from esmorph import Analyzer

>>> morph = Analyzer()
>>> morph.lemmatize("Los niños cantaban en la plaza".split())
['el', 'niño', 'cantar', 'en', 'el', 'plaza']
>>> analysis = morph.analyze("camiones")[0]
>>> analysis.lemma, analysis.pos, analysis.feats
('camión', 'NOUN', {'Gender': 'Masc', 'Number': 'Plur'})
>>> morph.analyze("hablar")[0].inflect(Tense="Past", Person="3", Number="Plur")
'hablaron'
>>> [form.word for form in morph.analyze("bonitas")[0].forms()]
['bonito', 'bonita', 'bonitos', 'bonitas']

The analyzer is created once: it loads the dictionary, and then it can be used in the whole program.

Features

Analysis of a word form

analyze gives the analyses of a word form, the most probable first: objects Analysis with the lemma, the part of speech, the UD features, the probability and the source of the analysis. Case does not matter for finding a word, though a word with a capital letter may also be a name, and a word without its accents is found too. Analyses are immutable: they can be compared, put into sets and pickled.

>>> [(a.lemma, a.pos, round(a.prob, 3)) for a in morph.analyze("canto")]
[('canto', 'NOUN', 0.999), ('cantar', 'VERB', 0.001)]
>>> analysis = morph.analyze("dámelo")[0]
>>> analysis.lemma, analysis.pos, analysis.words
('dar', 'VERB', ('da', 'me', 'lo'))
>>> morph.is_known("Camion"), morph.is_known("qzxw")
(True, False)

analyze_many analyzes a list of words, and lemmatize gives their lemmas without the GIL. The analyzer and the analyses are pickled, so they work with multiprocessing and joblib.

See the documentation: analyzer, word analysis.

>>> [(w, morph.analyze(w)[0].lemma, morph.analyze(w)[0].pos) for w in ["la", "su", "hay", "madrid"]]
[('la', 'el', 'DET'), ('su', 'su', 'DET'), ('hay', 'haber', 'VERB'), ('madrid', 'Madrid', 'PROPN')]
>>> morph.analyze("la")[0].feats
{'Definite': 'Def', 'Gender': 'Fem', 'Number': 'Sing', 'PronType': 'Art'}

>>> [(a.lemma, a.pos, a.source) for w in ["2.ª", "10.000", "xii"] for a in morph.analyze(w)]
[('2.º', 'ADJ', 'rule'), ('10000', 'NUM', 'rule'), ('xii', 'NUM', 'rule')]
>>> [(morph.analyze(w)[0].lemma, morph.analyze(w)[0].source) for w in ["supergallos", "esbeltísima"]]
[('supergallo', 'guess'), ('esbeltísimo', 'guess')]
>>> morph.analyze("zumbeábamos")[0].inflect(Tense="Pres", Person="3", Number="Sing")
'zumbea'

>>> morph.analyze("gata")[0].inflect(Number="Plur")
'gatas'
>>> morph.analyze("hablás")[0].inflect(Mood="Imp")
'hablá'

Development

The project uses uv to manage dependencies, maturin to build the Rust module and ruff for linting and formatting. Python 3.11 or newer and Rust 1.88 or newer are required.

git clone https://github.com/SergeyShk/esMorph.git
cd esMorph

make deps        # create the environment, install the dependencies and build the Rust module
make dictionary  # build the dictionary from the snapshot of Wiktionary and the counts of treebanks
make test        # run the Python tests, the docstring examples (doctest) and the Rust tests
make lint        # ruff, mypy, rustfmt and clippy

The full list of commands is make help. The documentation is bilingual: English pages docs/*.md with Spanish docs/*.es.md next to them; update both versions when editing a page.

Before submitting changes, install the hooks that run the linters on commit and the tests on push:

uv run pre-commit install

Contributing

Bug reports, ideas and pull requests are welcome, in English or Spanish - the issues are open. The workflow and the checks to run before submitting a pull request are in CONTRIBUTING.md.

Authors

• Sergey Shkarin (kouki.sergey@gmail.com)

License

The code is distributed under the MIT license. The dictionary is built from Wiktionary and the treebanks UD Spanish AnCora and UD Spanish GSD, and is distributed under the CC BY-SA 4.0 license.

Citation

If you use esMorph in research or software, please cite it with the following BibTeX entry: this helps the project grow and be maintained. The same metadata is in CITATION.cff - GitHub shows it under "Cite this repository".

@software{esMorph,
  author = {Sergey Shkarin},
  title = {{esMorph, a fast morphological analyzer for Spanish}},
  year = 2026,
  url = {https://github.com/SergeyShk/esMorph}
}