SeraML
Machine learning library built on the Sera Framework — a low-level Rust core shared with SeraPlot and the upcoming SeraDFrame.
SeraML is a drop-in replacement for Scikit-learn, 2–686× faster, with a single pip install and zero C/Fortran dependencies.
pip install seraml
Quick example
from seraml.linear_model import LinearRegression
from seraml.model_selection import train_test_split
from seraml.metrics import r2_score
X = [[1], [2], [3], [4], [5]]
y = [2.1, 4.0, 5.9, 8.1, 10.0]
X_train, X_test, y_train, y_test = train_test_split(X, y, test_size=0.2)
model = LinearRegression()
model.fit(X_train, y_train)
score = r2_score(y_test, model.predict(X_test))
print(f"R² = {score:.4f}")
Scikit-learn compatibility
SeraML mirrors the Scikit-learn API — .fit(), .predict(), .transform(), .score(). Pipelines work the same way.
Submodules
| Module | Contents |
|---|---|
seraml.linear_model |
LinearRegression, Ridge, Lasso, ElasticNet, LogisticRegression, SGDClassifier, SGDRegressor, RidgeClassifier |
seraml.tree |
DecisionTreeClassifier, DecisionTreeRegressor |
seraml.ensemble |
RandomForestClassifier, RandomForestRegressor, GradientBoostingClassifier, GradientBoostingRegressor, AdaBoostClassifier, AdaBoostRegressor |
seraml.cluster |
KMeans, DBSCAN |
seraml.neighbors |
KNeighborsClassifier, KNeighborsRegressor, NearestCentroid |
seraml.naive_bayes |
GaussianNB, MultinomialNB, BernoulliNB |
seraml.svm |
LinearSVC, LinearSVR |
seraml.preprocessing |
StandardScaler, MinMaxScaler, RobustScaler, MaxAbsScaler, Normalizer, LabelEncoder, OneHotEncoder, OrdinalEncoder, SimpleImputer, PolynomialFeatures, KBinsDiscretizer, PowerTransformer, QuantileTransformer |
seraml.decomposition |
PCA, TruncatedSVD |
seraml.model_selection |
GridSearchCV, RandomizedSearchCV, HalvingGridSearchCV, HalvingRandomSearchCV, StratifiedKFold, train_test_split, cross_val_score |
seraml.metrics |
Full classification, regression, clustering metric suite |
The Sera Framework
SeraML is one of three products built on Sera — a low-level Rust framework:
- SeraPlot — 60+ chart types, zero dependencies (pypi.org/project/seraplot)
- SeraML — drop-in Scikit-learn replacement (this package)
- SeraDFrame — Pandas/Polars alternative (Q4 2027)
The Rust core provides CPU/GPU optimisation, memory arenas, parallel threads (rayon), and a compile-time macro registry — natively inherited by every method.
License
MIT
1 maintainer
Metadata
1 maintainer
Release files for seraml 1.0.0
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Built distribution (wheel)
| File | Interpreter | ABI | Platform | Reset |
|---|---|---|---|---|
| seraml-1.0.0-cp311-cp311-win_amd64.whl | CPython 3.11 | CPython 3.11 | Windows x86-64 | Details |
Release files / seraml-1.0.0-cp311-cp311-win_amd64.whl
| Download URL | seraml-1.0.0-cp311-cp311-win_amd64.whl |
|---|---|
| Size | 8.5 MB |
| Tags | CPython 3.11 Windows x86-64 |
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