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flxscalers

Data scalers with a compiled C++17 core and a thin, typed Python API. The numeric work happens in an extension module (flxscalers._core); the public Python layer only validates input and wraps the result.

Features

  • MinMaxScaler — linearly rescales every feature from its observed [min, max] span onto a configurable feature_range (default (0.0, 1.0)). Values outside the fitted span map outside the range rather than being clipped.
  • Familiar estimator APIfit, transform, fit_transform, and inverse_transform, matching the scikit-learn method names and semantics.
  • Compiled core — the per-feature statistics and the scaling pass run in C++17, not Python.
  • NumPy in, NumPy out — accepts any array-like of shape (n_samples, n_features); always returns a float64 ndarray.
  • Typed — ships py.typed and stubs, so MinMaxScaler is fully checkable under mypy/pyright.
  • Clear errors — calling transform before fit raises flxscalers.NotFittedError with an actionable message.

More scalers (e.g. StandardScaler) are planned.

Install

pip install .

NumPy is pulled in as a runtime dependency. No system CMake, Ninja, or compiler setup is required beyond a C++17 compiler — scikit-build-core fetches CMake and Ninja into an isolated build environment automatically.

Usage

import numpy as np
from flxscalers import MinMaxScaler

X = np.array([[0.0, 10.0],
              [5.0, 20.0],
              [10.0, 30.0]])

scaler = MinMaxScaler()
X_scaled = scaler.fit_transform(X)
# array([[0. , 0. ],
#        [0.5, 0.5],
#        [1. , 1. ]])

# Reuse the fitted range on new data; values beyond the fitted span
# extrapolate past feature_range instead of being clipped.
scaler.transform(np.array([[15.0, 40.0]]))
# array([[1.5, 1.5]])

# Round-trip back to the original units.
scaler.inverse_transform(X_scaled)
# array([[ 0., 10.],
#        [ 5., 20.],
#        [10., 30.]])

Scale onto a custom range by passing feature_range:

scaler = MinMaxScaler(feature_range=(-1.0, 1.0))
scaler.fit_transform(X)
# array([[-1., -1.],
#        [ 0.,  0.],
#        [ 1.,  1.]])

Using a method that needs fitted state before calling fit raises:

from flxscalers import MinMaxScaler, NotFittedError

try:
    MinMaxScaler().transform(X)
except NotFittedError as e:
    print(e)  # MinMaxScaler is not fitted yet. Call fit() first.

Development

python -m venv venv && source venv/bin/activate
pip install scikit-build-core pybind11 cmake ninja
pip install --no-build-isolation -e .

With the editable install, pyproject.toml sets editable.rebuild = true, so editing a .cpp/.hpp/CMakeLists.txt triggers a recompile on the next import flxscalers — no reinstall, just restart the Python process (or the notebook kernel).

Gotcha: editable rebuilds need a real, activated toolchain

editable.rebuild = true re-invokes cmake and ninja at import time. Two things must hold, or every import after the first fails:

  1. Install with --no-build-isolation (as above). A plain isolated pip install -e . records a path to CMake inside a temporary build environment (/tmp/pip-build-env-.../cmake); that directory is deleted after the install, so the rebuild step then fails with cmake: not found / returned non-zero exit status 127. Installing without isolation makes it use the cmake/ninja from the venv instead, which persist.

  2. Activate the venv (source venv/bin/activate) before running Python or starting the notebook kernel, so venv/bin is on PATH and the import-time rebuild can find cmake. Running venv/bin/python directly, without activation, is not enough. For a Jupyter kernel you cannot launch from an activated shell, add "env": {"PATH": "/abs/path/to/venv/bin:${PATH}"} to its kernel.json instead.

If an editable checkout gets into a broken state, rm -rf build and re-run the pip install --no-build-isolation -e . step.

Testing

C++ (Catch2). Kept out of the wheel build; enabled by the dev preset, which also skips the Python extension so no pybind11 needs to be in scope. Catch2 is fetched via FetchContent on the first configure.

cmake --preset dev
cmake --build --preset dev
ctest --preset dev

Without presets: cmake -S . -B build-test -DFLXSCALERS_BUILD_TESTS=ON -DFLXSCALERS_BUILD_PYTHON=OFF && cmake --build build-test && ctest --test-dir build-test --output-on-failure.

Python (pytest).

pip install --no-build-isolation -e '.[test]'
pytest

Adding a scaler

  1. C++ coresrc/flxscalers/scalers/<name>.{hpp,cpp}; add the .cpp to the flxscalers_core source list in CMakeLists.txt.
  2. Bindingsrc/flxscalers/bindings/scalers/<name>.cpp defining register_<name>(pybind11::module_&); declare it in bindings/register.hpp, call it from bindings/_core.cpp, and add the .cpp to pybind11_add_module(_core ...).
  3. Pythonpython/flxscalers/scalers/_<name>.py wrapping flxscalers._core.<Name> by composition; re-export it from scalers/__init__.py and the top-level __init__.py, and add the class to _core.pyi.
  4. Teststests/cpp/scalers/test_<name>.cpp (add it to tests/cpp/CMakeLists.txt) and tests/python/scalers/test_<name>.py.

Release files for flxscalers 0.1.0

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Source distribution for flxscalers 0.1.0
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Table of built distributions (wheels) for flxscalers 0.1.0
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flxscalers-0.1.0-cp313-cp313-win_amd64.whl CPython 3.13 CPython 3.13 Windows x86-64 Details
flxscalers-0.1.0-cp313-cp313-manylinux_2_27_x86_64.manylinux_2_28_x86_64.whl CPython 3.13 CPython 3.13 Linux glibc 2.27+ x86-64, Linux glibc 2.28+ x86-64 Details
flxscalers-0.1.0-cp313-cp313-macosx_11_0_arm64.whl CPython 3.13 CPython 3.13 macOS 11.0+ ARM64 Details
flxscalers-0.1.0-cp313-cp313-macosx_10_13_x86_64.whl CPython 3.13 CPython 3.13 macOS 10.13+ x86-64 Details
flxscalers-0.1.0-cp312-cp312-win_amd64.whl CPython 3.12 CPython 3.12 Windows x86-64 Details
flxscalers-0.1.0-cp312-cp312-manylinux_2_27_x86_64.manylinux_2_28_x86_64.whl CPython 3.12 CPython 3.12 Linux glibc 2.28+ x86-64, Linux glibc 2.27+ x86-64 Details
flxscalers-0.1.0-cp312-cp312-macosx_11_0_arm64.whl CPython 3.12 CPython 3.12 macOS 11.0+ ARM64 Details
flxscalers-0.1.0-cp312-cp312-macosx_10_13_x86_64.whl CPython 3.12 CPython 3.12 macOS 10.13+ x86-64 Details
flxscalers-0.1.0-cp311-cp311-win_amd64.whl CPython 3.11 CPython 3.11 Windows x86-64 Details
flxscalers-0.1.0-cp311-cp311-manylinux_2_27_x86_64.manylinux_2_28_x86_64.whl CPython 3.11 CPython 3.11 Linux glibc 2.27+ x86-64, Linux glibc 2.28+ x86-64 Details
flxscalers-0.1.0-cp311-cp311-macosx_11_0_arm64.whl CPython 3.11 CPython 3.11 macOS 11.0+ ARM64 Details
flxscalers-0.1.0-cp311-cp311-macosx_10_9_x86_64.whl CPython 3.11 CPython 3.11 macOS 10.9+ x86-64 Details
flxscalers-0.1.0-cp310-cp310-win_amd64.whl CPython 3.10 CPython 3.10 Windows x86-64 Details
flxscalers-0.1.0-cp310-cp310-manylinux_2_27_x86_64.manylinux_2_28_x86_64.whl CPython 3.10 CPython 3.10 Linux glibc 2.27+ x86-64, Linux glibc 2.28+ x86-64 Details
flxscalers-0.1.0-cp310-cp310-macosx_11_0_arm64.whl CPython 3.10 CPython 3.10 macOS 11.0+ ARM64 Details
flxscalers-0.1.0-cp310-cp310-macosx_10_9_x86_64.whl CPython 3.10 CPython 3.10 macOS 10.9+ x86-64 Details
flxscalers-0.1.0-cp39-cp39-win_amd64.whl CPython 3.9 CPython 3.9 Windows x86-64 Details
flxscalers-0.1.0-cp39-cp39-manylinux_2_27_x86_64.manylinux_2_28_x86_64.whl CPython 3.9 CPython 3.9 Linux glibc 2.27+ x86-64, Linux glibc 2.28+ x86-64 Details
flxscalers-0.1.0-cp39-cp39-macosx_11_0_arm64.whl CPython 3.9 CPython 3.9 macOS 11.0+ ARM64 Details
flxscalers-0.1.0-cp39-cp39-macosx_10_9_x86_64.whl CPython 3.9 CPython 3.9 macOS 10.9+ x86-64 Details

Total release size: 2.9 MB

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0.2.0

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This release

0.1.0 This release

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