Rishe (ریشه): fast Persian text processing for Python, built in Rust
pip install rishe gives you Persian normalization, tokenization, sentence
splitting, lemmatization, ezafe detection and informal → formal conversion
from one Rust core: no models to download, prebuilt wheels for Linux, macOS
and Windows. The core is also available as a Rust crate.
- Normalization is ~70× faster than Hazm and Shekar; tokenization is on par with them. See docs/BENCHMARKS.md for the full numbers, including where Rishe loses.
Pipeline.pipe()processes batches in parallel (rayon) with the GIL released.
Status: alpha (0.1). Rishe is a fast preprocessing layer, not a replacement for Hazm or Shekar: there is no POS tagging, NER, parsing, spell checking or embeddings.
Install
pip install rishe # Python >= 3.9
or, from Rust (Cargo.toml): rishe = "0.1"
Quick start
from rishe import Pipeline
pipe = Pipeline()
doc = pipe("اون داره تو خونه کتاب میخونه، چیه؟")
doc.tokens # ['آن', 'دارد', 'تو', 'خانه', 'کتاب', 'میخواند', '،', 'چیست', '؟']
doc.lemmas # ['آن', 'داشت', 'تو', 'خانه', 'کتاب', 'خواند', '،', 'چیست', '؟']
doc.formal_text # 'آن دارد تو خانه کتاب میخواند، چیست؟'
doc.sentences, doc.normalized_text, doc.ezafe_markers
pipe.word_tokenize("سلام، دنیا!") # ['سلام', '،', 'دنیا', '!']
pipe.lemmatize("میروم") # 'رفت' (past-stem lemmas, UD style)
pipe.pipe(texts) # parallel batch -> list[ProcessedDoc]
use rishe::Pipeline;
let pipe = Pipeline::create(true, true, true); // unify digits, strip diacritics, fix ZWNJ
let doc = pipe.process("کتابهای خوب را به دوستانم میدهم.");
println!("{:?}", doc.tokens);
Known limitations
Pipeline.__call__also rewrites colloquial words to formal ones, sodoc.tokenscan differ from the surface text. Useword_tokenizefor plain tokenization.- Informal → formal conversion is lexicon- and rule-based. Common forms
(
اون,خونه,داره,چیه,میخوام) work; many suffixed or rarer forms (خونهام,کتابه) are left unchanged. - Lemmas follow the Universal Dependencies convention (verbs lemmatize to the past stem). Accuracy on UD is ~0.90 (Seraji) and ~0.88 (PerDT).
- Ezafe detection is rule-based and has not been evaluated.
Building from source
cargo test
maturin develop --release # Python extension into the current venv
python scripts/benchmark.py # needs: hazm shekar conllu
scripts/extract_lexicons.py regenerates data/*.tsv from Hazm's data
files; build.rs compiles them into FSTs.
License
Dual-licensed under Apache-2.0 or MIT, at your option. The bundled lexicons are derived from Hazm data (MIT); see NOTICE.md.
1 maintainer
Metadata
1 maintainer
Release files for rishe 0.1.0
For a detailed explanation of source distributions (sdists) and built distributions (wheels), please see the package formats documentation.
Source distribution (sdist)
| File | Size | Uploaded | Provenance | |
|---|---|---|---|---|
| rishe-0.1.0.tar.gz | 1.0 MB | With provenance | Details |
Built distributions (wheels)
| File | Reset | |||
|---|---|---|---|---|
| rishe-0.1.0-cp39-abi3-win_amd64.whl | CPython 3.9 | abi3 | Windows x86-64 | Details |
| rishe-0.1.0-cp39-abi3-musllinux_1_2_x86_64.whl | CPython 3.9 | abi3 | Linux musl 1.2+ x86-64 | Details |
| rishe-0.1.0-cp39-abi3-musllinux_1_2_aarch64.whl | CPython 3.9 | abi3 | Linux musl 1.2+ ARM64 | Details |
| rishe-0.1.0-cp39-abi3-manylinux_2_17_x86_64.manylinux2014_x86_64.whl | CPython 3.9 | abi3 | Linux glibc 2.17+ x86-64 | Details |
| rishe-0.1.0-cp39-abi3-manylinux_2_17_aarch64.manylinux2014_aarch64.whl | CPython 3.9 | abi3 | Linux glibc 2.17+ ARM64 | Details |
| rishe-0.1.0-cp39-abi3-macosx_11_0_arm64.whl | CPython 3.9 | abi3 | macOS 11.0+ ARM64 | Details |
| rishe-0.1.0-cp39-abi3-macosx_10_12_x86_64.whl | CPython 3.9 | abi3 | macOS 10.12+ x86-64 | Details |
Total release size: 9.5 MB
Release files / rishe-0.1.0.tar.gz
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