Leo Galambos
5e3d3c7c7d
- add the Rust-backed Python API with PyStemmer compatibility - distribute standard compiled models as a separate Python package - generate model artifacts during builds instead of storing them in Git - add GitHub release and Pages-backed package index workflows - add Python tests, benchmarks, documentation, and Gradle integration - refresh the documentation site, branding, and language benchmarks
1.8 KiB
Python Fast Track
This is the shortest path from an empty Python environment to a working Radixor stemmer. The installation includes the native runtime and the separate standard-model package with 20 precompiled language models.
1. Install
=== "PyPI"
```bash
python -m pip install --only-binary=:all: radixor
```
=== "GitHub Releases"
```bash
python -m pip install --only-binary=:all: \
--index-url https://leogalambos.github.io/Radixor/python/simple/ radixor
```
PyPI publication is pending, and the GitHub index becomes live with the first Python releases. Until then, follow the source-checkout procedure on Installation and Builds.
Radixor supports CPython 3.9 and newer. A JVM, Java dependency, and source dictionary are not required.
2. Stem words
from radixor import Stemmer
stemmer = Stemmer("en")
print(stemmer.stem("running"))
print(stemmer.stem_batch(["running", "studies", "cars"]))
Expected first output:
run
stem() and stem_batch() preserve Radixor's original API: a word for which
the trie finds no patch command produces None.
3. Use PyStemmer-compatible fallback semantics
For a low-friction migration from PyStemmer, use the compatible method names:
stemmer.stemWord("running")
stemmer.stemWords(["running", "unknown_word"])
These methods return the original input whenever no patch command is found, so
their results are always strings rather than None.
Next
- Continue with the Python Quick Start for model selection, batch processing, custom compiled models, and deployment guidance.
- Use Python Usage and API as the method reference.
- Review the reproducible Python performance results.