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feat(python): add native distribution and release infrastructure

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- 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
This commit is contained in:
Leo Galambos
2026-08-10 22:34:32 +02:00
parent b45e143c84
commit 5e3d3c7c7d
139 changed files with 11420 additions and 747 deletions
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docs/benchmarks/languages/hungarian.md
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@@ -8,9 +8,9 @@ Radixor must not be read as simply "slower" when a narrow competitor has a lower
## Dictionary Corpus
| Model ID | Model version | Language | Dictionary rows | Complete quality tokens | Already-root tokens | Changed speed tokens |
| --- | --- | --- | ---: | ---: | ---: | ---: |
| `hu-hu-default` | `1.0.0` | `HU_HU` | 19,406 | 935,713 | 38,775 | 896,938 |
| Model ID | Model version | Language | Dictionary rows | Complete quality tokens | Already-root tokens | Changed tokens | JMH timing tokens |
| --- | --- | --- | ---: | ---: | ---: | ---: | ---: |
| `hu-hu-default` | `1.0.0` | `HU_HU` | 19,406 | 935,713 | 38,775 | 896,938 | 896,938 |
## Radixor Patch Command Distribution
@@ -30,13 +30,10 @@ Accuracy is computed from JMH auxiliary counters in the current report. The coun
| Stemmer | All exact | Changed exact | Root preserved | Note |
| --- | ---: | ---: | ---: | --- |
| Radixor | 99.222% | 99.537% | 91.948% | Full Radixor dictionary patch-command stemmer. |
| Radixor | 99.222% | 99.537% | 91.948% | Radixor dictionary-trained patch-command stemmer. |
| Lucene SnowballFilter | 66.445% | 66.938% | 55.043% | Lucene TokenFilter integration path around the Snowball algorithm. |
| Official Snowball direct | 66.445% | 66.938% | 55.043% | Official Snowball generated Java stemmer; rule-based suffix algorithm. |
| Lucene HungarianLightStemFilter | 14.748% | 14.777% | 14.086% | Light suffix stemmer; intentionally narrower than a dictionary-derived stemmer. |
| Lucene HungarianLightStemFilter | 14.748% | 14.777% | 14.086% | Light suffix stemmer; intentionally narrower than Radixor's dictionary-trained transformation model. |
## Speed
@@ -44,17 +41,14 @@ Speed uses JMH average time, 5 warmup iterations, 10 measurement iterations, 3 i
| Stemmer | Benchmark method | Score ms/op | Error ms | ns/token | Relative vs Radixor | Note |
| --- | --- | ---: | ---: | ---: | ---: | --- |
| Radixor | `hungarianRadixor` | 61.205 | 0.944 | 68.2 | 1.000 | Full Radixor dictionary patch-command stemmer. |
| Lucene HungarianLightStemFilter | `hungarianLuceneHungarianLightStemFilter` | 92.090 | 3.410 | 102.7 | 1.505 | Light Hungarian suffix stemmer. |
| Official Snowball direct | `snowballDirect[HUNGARIAN]` | 152.969 | 4.468 | 170.5 | 2.499 | Official Snowball generated Java stemmer; direct API. |
| Lucene SnowballFilter | `luceneSnowballFilter[HUNGARIAN]` | 188.807 | 5.290 | 210.5 | 3.085 | Lucene TokenFilter path around Snowball; includes TokenStream overhead. |
| Radixor | `hungarianRadixor` | 52.020 | 1.337 | 58.0 | 1.000 | Radixor dictionary-trained patch-command stemmer. |
| Lucene HungarianLightStemFilter | `hungarianLuceneHungarianLightStemFilter` | 87.362 | 3.444 | 97.4 | 1.679 | Light Hungarian suffix stemmer. |
| Official Snowball direct | `snowballDirect[HUNGARIAN]` | 158.081 | 9.757 | 176.2 | 3.039 | Official Snowball generated Java stemmer; direct API. |
| Lucene SnowballFilter | `luceneSnowballFilter[HUNGARIAN]` | 179.398 | 8.041 | 200.0 | 3.449 | Lucene TokenFilter path around Snowball; includes TokenStream overhead. |
## Interpretation Notes
- Radixor is a dictionary-derived patch-command stemmer. Its quality depends on the language resource used to train the compiled trie.
- Radixor is a dictionary-trained patch-command stemmer. Its learned transformations can generalize beyond the word forms listed in the training resource.
- Light, minimal, plural, and possessive filters are narrow baselines. They can be fast because they intentionally perform less linguistic work.
- Lucene TokenFilter rows include TokenStream, attribute, and required normalization overhead. Direct rows measure exposed direct APIs.
- Morfologik rows are dictionary-based and can emit multiple terms for one input token. Quality rows use the first returned term when no ranking weight is available.
@@ -322,7 +316,7 @@ Standard ARI, homogeneity, completeness, V-measure, and NMI are not calculated:
### Provenance
- Authoritative source: `docs/benchmarks/data/stemming-quality.csv`
- Source SHA-256: `edf16b07be8a535943ddf37caeb8807755c95e9e1fb13244145f28be74b491d8`
- Source SHA-256: `d34f325da320a2e040b54d8d8b5c216d70448f08cfb8659a423e99882aa1afb5`
- Evaluation command: `./gradlew stemmingQuality --no-daemon`
- Dictionary language: `HU_HU`
- Processing modes: `ALL_WORDS`, `LOWERCASE_GROUPS_ONLY`