splotrs

splotrs fits the yields and shared shape parameters of normalized component probability-density functions, then calculates per-event sWeights. The numerical core is written in Rust and uses Ganesh; the Python API accepts vectorized NumPy callbacks.

The library is intended for unbinned mixture fits where a discriminating variable separates components and the resulting sWeights are used to study another, component-independent variable. It supports signed input event weights and exposes both the sPlot yield covariance and the full joint fit covariance.

Features

Joint extended maximum-likelihood fits of component yields and shared PDF shape parameters.
Vectorized Python PDF callbacks with runtime validation of their output type and shape.
A native Rust API for allocation-conscious fitting without Python.
Per-event sWeights in the same row order as the input data.
Signed input event weights.
Fit diagnostics, uncertainties, and covariance matrices.

Installation

Install the Python package from PyPI:

python -m pip install splotrs

Or add the Rust crate from crates.io:

cargo add splotrs

Python 3.10 or newer is required.

Python quick start

Each component PDF must be callable as pdf(events: NDArray[np.float64], parameters: dict[str, float]) -> NDArray[np.float64]. It receives the complete two-dimensional event array and must return one finite, nonnegative float64 density per event.

from collections.abc import Callable

import numpy as np
from numpy.typing import NDArray

from splotrs import ShapeParameter, splot

Pdf = Callable[
    [NDArray[np.float64], dict[str, float]],
    NDArray[np.float64],
]


def signal(events: NDArray[np.float64], parameters: dict[str, float]) -> NDArray[np.float64]:
    mean = parameters['mean']
    residual = events[:, 0] - mean
    return np.exp(-0.5 * residual**2) / np.sqrt(2.0 * np.pi)


def background(
    events: NDArray[np.float64], _parameters: dict[str, float]
) -> NDArray[np.float64]:
    residual = (events[:, 0] - 2.5) / 0.7
    return np.exp(-0.5 * residual**2) / (0.7 * np.sqrt(2.0 * np.pi))


data = np.array([[-1.2], [-0.3], [0.2], [2.1], [2.8]], dtype=np.float64)
pdfs: list[Pdf] = [signal, background]

result = splot(
    data,
    pdfs,
    shape_parameters=[ShapeParameter('mean', 0.0, -5.0, 5.0)],
)

print(result.yields)
print(result.shape_parameters)
print(result.sweights)  # (n_events, n_components)

shape_parameters are fitted jointly with the yields. Every PDF receives the complete parameter dictionary, so multiple components can share the same parameter.

Inputs

data: finite values with shape (n_events, n_features).
pdfs: one callable per mixture component, in output-column order.
shape_parameters: optional ShapeParameter objects with initial values and bounds.
initial_yields: optional nonnegative starting yields, one per PDF.
weights: optional signed event weights with shape (n_events,).
max_steps and tolerance: optimizer controls.

Result

splot returns an immutable SPlotResult containing:

yields and yield_errors;
sweights with shape (n_events, n_components);
covariance, the event-summed sPlot yield covariance;
shape_parameters and shape_errors keyed by parameter name;
fit_covariance, the full joint yield-and-shape covariance;
convergence status, message, minimum negative log-likelihood, and evaluation counts.

Invalid inputs and callback contracts raise ValueError. Numerical PDF, optimizer, and covariance failures raise SPlotError. Exceptions raised inside a PDF callback are preserved.

Complete example

The included example fits a Gaussian bump over a quadratic background and uses sWeights to recover the component distributions of a control variable:

just examples

It writes the resulting plot to target/examples/bump.png.

Rust usage

Implement ParametricPdf or use compatible closures, then call splot with event rows, PDFs, shape parameters, and an SPlotConfig:

use splotrs::{ParametricPdf, SPlotConfig, ShapeParameter, ShapeParameters, splot};

let data = vec![vec![-1.2], vec![-0.3], vec![0.2], vec![2.1], vec![2.8]];
let signal = |event: &[f64], parameters: &ShapeParameters| {
    let residual = event[0] - parameters["mean"];
    (-0.5 * residual * residual).exp() / std::f64::consts::TAU.sqrt()
};
let background = |event: &[f64], _parameters: &ShapeParameters| {
    let residual = (event[0] - 2.5) / 0.7;
    (-0.5 * residual * residual).exp() / (0.7 * std::f64::consts::TAU.sqrt())
};
let pdfs: [&dyn ParametricPdf; 2] = [&signal, &background];
let shapes = [ShapeParameter::new("mean", 0.0)?.with_bounds(-5.0, 5.0)?];

let result = splot(&data, &pdfs, &shapes, SPlotConfig::default())?;
println!("yields: {:?}", result.yields);
# Ok::<(), splotrs::SPlotError>(())

Statistical assumptions

Component PDFs must be normalized over the fitted discriminating variables.
Components must be identifiable; linearly dependent PDFs produce a singular covariance error.
A variable studied with sWeights should be independent of the discriminating variables within each component.
Signed input weights are supported, but some weighted datasets can produce an indefinite or singular information matrix.

Development

Enter the reproducible Nix development shell:

nix develop

The shell supplies Rust, Cargo, Clippy, rustfmt, Python, uv, and Just. It synchronizes the locked Python development environment on entry. Run just to list all recipes; the main workflows are:

just build       # Build the Rust crate and Python distributions
just test        # Run Rust and Python tests
just lint        # Run Clippy, rustfmt, Ruff, ty, and Yamloom checks
just fmt         # Format Rust and Python sources
just examples    # Run the complete plotting example
just clean       # Remove generated build and test artifacts

Without Nix, install uv, Rust, and Just, then run uv sync before using the same recipes.

Before publishing, inspect both artifacts locally:

cargo publish --dry-run
uv build

License

Licensed under either of the following, at your option:

Apache License, Version 2.0 (LICENSE-APACHE)
MIT License (LICENSE-MIT)

Metadata

Release files for splotrs 0.1.5

For a detailed explanation of source distributions (sdists) and built distributions (wheels), please see the package formats documentation.

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Source distribution for splotrs 0.1.5
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Tags	CPython 3.14 CPython 3.14 free-threading Linux musl 1.2+ x86-32
SHA-256 checksum How to use checksums	`ad547310a8e3a75157cd0ae9e34faf851e36f91300a8b83dbe7594fb534e31a1`
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Release files / splotrs-0.1.5-cp314-cp314t-musllinux_1_2_armv7l.whl

Download URL	splotrs-0.1.5-cp314-cp314t-musllinux_1_2_armv7l.whl
Size	716.9 kB
Tags	CPython 3.14 CPython 3.14 free-threading Linux musl 1.2+ ARMv7l
SHA-256 checksum How to use checksums	`7cd86f9d565583a012e28694a070375adf2564064802c93da7ce8b07fc79fa47`
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Release files / splotrs-0.1.5-cp314-cp314t-musllinux_1_2_aarch64.whl

Download URL	splotrs-0.1.5-cp314-cp314t-musllinux_1_2_aarch64.whl
Size	620.7 kB
Tags	CPython 3.14 CPython 3.14 free-threading Linux musl 1.2+ ARM64
SHA-256 checksum How to use checksums	`cd8f6a7d5675a5b80a401efacce19e6a3db715f390100e5952edfd7d9b30e1dc`
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Release files / splotrs-0.1.5-cp314-cp314t-manylinux_2_17_x86_64.manylinux2014_x86_64.whl

Download URL	splotrs-0.1.5-cp314-cp314t-manylinux_2_17_x86_64.manylinux2014_x86_64.whl
Size	484.8 kB
Tags	CPython 3.14 CPython 3.14 free-threading Linux glibc 2.17+ x86-64
SHA-256 checksum How to use checksums	`f312940a62af75ddf6c5fc8bf5ca1a0e1ff996a28a10d5416d117854b9d84d8c`
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Release files / splotrs-0.1.5-cp314-cp314t-manylinux_2_17_s390x.manylinux2014_s390x.whl

Download URL	splotrs-0.1.5-cp314-cp314t-manylinux_2_17_s390x.manylinux2014_s390x.whl
Size	483.4 kB
Tags	CPython 3.14 CPython 3.14 free-threading Linux glibc 2.17+ IBM System/390x
SHA-256 checksum How to use checksums	`53707bc1d962da47a529c636a97328d78387d090a0a41fa7c0a5bf6e62dc1fd3`
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Release files / splotrs-0.1.5-cp314-cp314t-manylinux_2_17_ppc64le.manylinux2014_ppc64le.whl

Download URL	splotrs-0.1.5-cp314-cp314t-manylinux_2_17_ppc64le.manylinux2014_ppc64le.whl
Size	615.3 kB
Tags	CPython 3.14 CPython 3.14 free-threading Linux glibc 2.17+ PowerPC 64-le
SHA-256 checksum How to use checksums	`983e01ee345d7a31be0c31feaf9fb2e9610a323d6d3d0c79a4cab59fad9dd7a0`
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Release files / splotrs-0.1.5-cp314-cp314t-manylinux_2_17_i686.manylinux2014_i686.whl

Download URL	splotrs-0.1.5-cp314-cp314t-manylinux_2_17_i686.manylinux2014_i686.whl
Size	502.0 kB
Tags	CPython 3.14 CPython 3.14 free-threading Linux glibc 2.17+ x86-32
SHA-256 checksum How to use checksums	`63a769d9f7767757a7c429aaec3b5156a0323b14fd583a3a750dd7951510298b`
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Release files / splotrs-0.1.5-cp314-cp314t-manylinux_2_17_armv7l.manylinux2014_armv7l.whl

Download URL	splotrs-0.1.5-cp314-cp314t-manylinux_2_17_armv7l.manylinux2014_armv7l.whl
Size	443.3 kB
Tags	CPython 3.14 CPython 3.14 free-threading Linux glibc 2.17+ ARMv7l
SHA-256 checksum How to use checksums	`eff7e01c3ff62f445e5971f73c9ab33adf406444310d5c24c2b28456fc6ccd69`
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Release files / splotrs-0.1.5-cp314-cp314t-manylinux_2_17_aarch64.manylinux2014_aarch64.whl

Download URL	splotrs-0.1.5-cp314-cp314t-manylinux_2_17_aarch64.manylinux2014_aarch64.whl
Size	443.8 kB
Tags	CPython 3.14 CPython 3.14 free-threading Linux glibc 2.17+ ARM64
SHA-256 checksum How to use checksums	`dbc18a54e0416527a6fa23b660dff192a1b41b91882fb762ed413d490efa0365`
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Release files / splotrs-0.1.5-cp314-cp314t-macosx_11_0_arm64.whl

Download URL	splotrs-0.1.5-cp314-cp314t-macosx_11_0_arm64.whl
Size	410.1 kB
Tags	CPython 3.14 CPython 3.14 free-threading macOS 11.0+ ARM64
SHA-256 checksum How to use checksums	`eaa74102b20887f01540cb58b553b12edc392a97b4898c09bc97fccda6c40095`
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Release files / splotrs-0.1.5-cp314-cp314t-macosx_10_12_x86_64.whl

Download URL	splotrs-0.1.5-cp314-cp314t-macosx_10_12_x86_64.whl
Size	437.9 kB
Tags	CPython 3.14 CPython 3.14 free-threading macOS 10.12+ x86-64
SHA-256 checksum How to use checksums	`aa061d66e6aa98597a72ae192380276b61db2ec6765adb46d6bc46e7e9d4b0ba`
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Release files / splotrs-0.1.5-cp314-cp314-win_arm64.whl

Download URL	splotrs-0.1.5-cp314-cp314-win_arm64.whl
Size	284.7 kB
Tags	CPython 3.14 Windows ARM64
SHA-256 checksum How to use checksums	`d188cb80825173276388186d56c60e30e973081f6046ae1397ffd19ee67cf533`
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Release files / splotrs-0.1.5-cp314-cp314-musllinux_1_2_x86_64.whl

Download URL	splotrs-0.1.5-cp314-cp314-musllinux_1_2_x86_64.whl
Size	682.5 kB
Tags	CPython 3.14 Linux musl 1.2+ x86-64
SHA-256 checksum How to use checksums	`c6310288866913b687d1b0d32eaf49bd2d9133559b863f889074e50e95031bda`
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Release files / splotrs-0.1.5-cp314-cp314-musllinux_1_2_i686.whl

Download URL	splotrs-0.1.5-cp314-cp314-musllinux_1_2_i686.whl
Size	713.5 kB
Tags	CPython 3.14 Linux musl 1.2+ x86-32
SHA-256 checksum How to use checksums	`e1257fdaa7d854ec9a42c0dea19d254874e4c52e84b47d3ec7a1d9334ceba90e`
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Release files / splotrs-0.1.5-cp314-cp314-musllinux_1_2_armv7l.whl

Download URL	splotrs-0.1.5-cp314-cp314-musllinux_1_2_armv7l.whl
Size	719.3 kB
Tags	CPython 3.14 Linux musl 1.2+ ARMv7l
SHA-256 checksum How to use checksums	`b126bfa272be3c04941273b17d953a18bec8058dd7ca3da7c31fb0c110c6796d`
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Release files / splotrs-0.1.5-cp314-cp314-musllinux_1_2_aarch64.whl

Download URL	splotrs-0.1.5-cp314-cp314-musllinux_1_2_aarch64.whl
Size	621.2 kB
Tags	CPython 3.14 Linux musl 1.2+ ARM64
SHA-256 checksum How to use checksums	`7882bba89a00080ab47a74cf01caf943366da63a07decc8951f31fa819a381b7`
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Release files / splotrs-0.1.5-cp314-cp314-manylinux_2_17_x86_64.manylinux2014_x86_64.whl

Download URL	splotrs-0.1.5-cp314-cp314-manylinux_2_17_x86_64.manylinux2014_x86_64.whl
Size	484.2 kB
Tags	CPython 3.14 Linux glibc 2.17+ x86-64
SHA-256 checksum How to use checksums	`e5cbc542bc7d3442c927424225b0b55891ebf529bf2f56c35dc50a04db760bab`
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Release files / splotrs-0.1.5-cp314-cp314-manylinux_2_17_s390x.manylinux2014_s390x.whl

Download URL	splotrs-0.1.5-cp314-cp314-manylinux_2_17_s390x.manylinux2014_s390x.whl
Size	485.2 kB
Tags	CPython 3.14 Linux glibc 2.17+ IBM System/390x
SHA-256 checksum How to use checksums	`86d1dd79d4adb22514ee421959c3fa145c6aaabaed140608922b60e93882c94c`
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Release files / splotrs-0.1.5-cp314-cp314-manylinux_2_17_ppc64le.manylinux2014_ppc64le.whl

Download URL	splotrs-0.1.5-cp314-cp314-manylinux_2_17_ppc64le.manylinux2014_ppc64le.whl
Size	617.2 kB
Tags	CPython 3.14 Linux glibc 2.17+ PowerPC 64-le
SHA-256 checksum How to use checksums	`e115f2726a35fc030f66ba6dfa1cd19202d66a2549d76cb2d29e9232c8b5ca02`
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Release files / splotrs-0.1.5-cp314-cp314-manylinux_2_17_i686.manylinux2014_i686.whl

Download URL	splotrs-0.1.5-cp314-cp314-manylinux_2_17_i686.manylinux2014_i686.whl
Size	504.2 kB
Tags	CPython 3.14 Linux glibc 2.17+ x86-32
SHA-256 checksum How to use checksums	`de953b50d5bf439532ef531a3d439f4132ae3eb3107e633ea35e6a7eca34fd85`
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Release files / splotrs-0.1.5-cp314-cp314-manylinux_2_17_armv7l.manylinux2014_armv7l.whl

Download URL	splotrs-0.1.5-cp314-cp314-manylinux_2_17_armv7l.manylinux2014_armv7l.whl
Size	445.0 kB
Tags	CPython 3.14 Linux glibc 2.17+ ARMv7l
SHA-256 checksum How to use checksums	`b029ed4fc240209f08eb558de8afe9bec232055b1e8e64b80c124345ef52ad29`
BLAKE2b-256 checksum How to use checksums	`2c1668386d2f51e282b42a261bf9fae30fb993176eb0114cc80634fa46c37b59`
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Release files / splotrs-0.1.5-cp314-cp314-manylinux_2_17_aarch64.manylinux2014_aarch64.whl

Download URL	splotrs-0.1.5-cp314-cp314-manylinux_2_17_aarch64.manylinux2014_aarch64.whl
Size	444.4 kB
Tags	CPython 3.14 Linux glibc 2.17+ ARM64
SHA-256 checksum How to use checksums	`c49346d6c5243c5df71a766b77ad183433d0545d907802def6d7fbc9f04043fa`
BLAKE2b-256 checksum How to use checksums	`8665415dc7ee4becb5064d893ff256369e59eb7da4de87e1de92b50f8b01fcfa`
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Release files / splotrs-0.1.5-cp314-cp314-macosx_11_0_arm64.whl

Download URL	splotrs-0.1.5-cp314-cp314-macosx_11_0_arm64.whl
Size	412.0 kB
Tags	CPython 3.14 macOS 11.0+ ARM64
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Release files / splotrs-0.1.5-cp314-cp314-macosx_10_12_x86_64.whl

Download URL	splotrs-0.1.5-cp314-cp314-macosx_10_12_x86_64.whl
Size	439.5 kB
Tags	CPython 3.14 macOS 10.12+ x86-64
SHA-256 checksum How to use checksums	`986433f6d6d5ac75c249df010f9dfda807841966348f832489e8d4ece5bc3c55`
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Release files / splotrs-0.1.5-cp313-cp313-win_arm64.whl

Download URL	splotrs-0.1.5-cp313-cp313-win_arm64.whl
Size	284.7 kB
Tags	CPython 3.13 Windows ARM64
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Release files / splotrs-0.1.5-cp313-cp313-win_amd64.whl

Download URL	splotrs-0.1.5-cp313-cp313-win_amd64.whl
Size	318.4 kB
Tags	CPython 3.13 Windows x86-64
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Release files / splotrs-0.1.5-cp313-cp313-win32.whl

Download URL	splotrs-0.1.5-cp313-cp313-win32.whl
Size	294.5 kB
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Release files / splotrs-0.1.5-cp313-cp313-musllinux_1_2_x86_64.whl

Download URL	splotrs-0.1.5-cp313-cp313-musllinux_1_2_x86_64.whl
Size	681.9 kB
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Release files / splotrs-0.1.5-cp313-cp313-musllinux_1_2_i686.whl

Download URL	splotrs-0.1.5-cp313-cp313-musllinux_1_2_i686.whl
Size	711.1 kB
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Release files / splotrs-0.1.5-cp313-cp313-musllinux_1_2_armv7l.whl

Download URL	splotrs-0.1.5-cp313-cp313-musllinux_1_2_armv7l.whl
Size	716.6 kB
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Release files / splotrs-0.1.5-cp313-cp313-musllinux_1_2_aarch64.whl

Download URL	splotrs-0.1.5-cp313-cp313-musllinux_1_2_aarch64.whl
Size	620.2 kB
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SHA-256 checksum How to use checksums	`ea93e88060e17a95c7adfafe16b1fa87954e44fbc40b056671019d33ac6810bb`
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Release files / splotrs-0.1.5-cp313-cp313-manylinux_2_17_x86_64.manylinux2014_x86_64.whl

Download URL	splotrs-0.1.5-cp313-cp313-manylinux_2_17_x86_64.manylinux2014_x86_64.whl
Size	483.1 kB
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SHA-256 checksum How to use checksums	`caec969d26fd58f65ab36535136789195a2324e578eac3b377294ea0ca196d6b`
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Release files / splotrs-0.1.5-cp313-cp313-manylinux_2_17_s390x.manylinux2014_s390x.whl

Download URL	splotrs-0.1.5-cp313-cp313-manylinux_2_17_s390x.manylinux2014_s390x.whl
Size	482.9 kB
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Release files / splotrs-0.1.5-cp313-cp313-manylinux_2_17_ppc64le.manylinux2014_ppc64le.whl

Download URL	splotrs-0.1.5-cp313-cp313-manylinux_2_17_ppc64le.manylinux2014_ppc64le.whl
Size	615.2 kB
Tags	CPython 3.13 Linux glibc 2.17+ PowerPC 64-le
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Release files / splotrs-0.1.5-cp313-cp313-manylinux_2_17_i686.manylinux2014_i686.whl

Download URL	splotrs-0.1.5-cp313-cp313-manylinux_2_17_i686.manylinux2014_i686.whl
Size	501.5 kB
Tags	CPython 3.13 Linux glibc 2.17+ x86-32
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Release files / splotrs-0.1.5-cp313-cp313-manylinux_2_17_armv7l.manylinux2014_armv7l.whl

Download URL	splotrs-0.1.5-cp313-cp313-manylinux_2_17_armv7l.manylinux2014_armv7l.whl
Size	442.9 kB
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Release files / splotrs-0.1.5-cp313-cp313-manylinux_2_17_aarch64.manylinux2014_aarch64.whl

Download URL	splotrs-0.1.5-cp313-cp313-manylinux_2_17_aarch64.manylinux2014_aarch64.whl
Size	443.6 kB
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SHA-256 checksum How to use checksums	`8846fa10683985fa9ce5d128e79fa1302ffa71e5fb4a4985799155eb601ad05c`
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Release files / splotrs-0.1.5-cp313-cp313-macosx_11_0_arm64.whl

Download URL	splotrs-0.1.5-cp313-cp313-macosx_11_0_arm64.whl
Size	409.1 kB
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Release files / splotrs-0.1.5-cp313-cp313-macosx_10_12_x86_64.whl

Download URL	splotrs-0.1.5-cp313-cp313-macosx_10_12_x86_64.whl
Size	436.5 kB
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Release files / splotrs-0.1.5-cp312-cp312-win_arm64.whl

Download URL	splotrs-0.1.5-cp312-cp312-win_arm64.whl
Size	283.9 kB
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Release files / splotrs-0.1.5-cp312-cp312-win_amd64.whl

Download URL	splotrs-0.1.5-cp312-cp312-win_amd64.whl
Size	317.9 kB
Tags	CPython 3.12 Windows x86-64
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Release files / splotrs-0.1.5-cp312-cp312-win32.whl

Download URL	splotrs-0.1.5-cp312-cp312-win32.whl
Size	294.6 kB
Tags	CPython 3.12 Windows x86-32
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Release files / splotrs-0.1.5-cp312-cp312-musllinux_1_2_x86_64.whl

Download URL	splotrs-0.1.5-cp312-cp312-musllinux_1_2_x86_64.whl
Size	681.1 kB
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Release files / splotrs-0.1.5-cp312-cp312-musllinux_1_2_i686.whl

Download URL	splotrs-0.1.5-cp312-cp312-musllinux_1_2_i686.whl
Size	711.4 kB
Tags	CPython 3.12 Linux musl 1.2+ x86-32
SHA-256 checksum How to use checksums	`187654010629cbb78891df652866683c3de534180772d46bb2d1bcca01706ec7`
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Release files / splotrs-0.1.5-cp312-cp312-musllinux_1_2_armv7l.whl

Download URL	splotrs-0.1.5-cp312-cp312-musllinux_1_2_armv7l.whl
Size	717.1 kB
Tags	CPython 3.12 Linux musl 1.2+ ARMv7l
SHA-256 checksum How to use checksums	`68fd5a0ca9c23c893fcb831e2d3d49ffd2b66c9e48607e8848083ab2a561bff2`
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Release files / splotrs-0.1.5-cp312-cp312-musllinux_1_2_aarch64.whl

Download URL	splotrs-0.1.5-cp312-cp312-musllinux_1_2_aarch64.whl
Size	620.0 kB
Tags	CPython 3.12 Linux musl 1.2+ ARM64
SHA-256 checksum How to use checksums	`ba993692a4eef1e79b5e4f6edcae9390b6d9de0c97c5be1c6db094c02d07de86`
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Release files / splotrs-0.1.5-cp312-cp312-manylinux_2_17_x86_64.manylinux2014_x86_64.whl

Download URL	splotrs-0.1.5-cp312-cp312-manylinux_2_17_x86_64.manylinux2014_x86_64.whl
Size	482.5 kB
Tags	CPython 3.12 Linux glibc 2.17+ x86-64
SHA-256 checksum How to use checksums	`bd610892018fa7ef80484fc983ff85cea12dc626218522cfb5646100c5eeafd6`
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Release files / splotrs-0.1.5-cp312-cp312-manylinux_2_17_s390x.manylinux2014_s390x.whl

Download URL	splotrs-0.1.5-cp312-cp312-manylinux_2_17_s390x.manylinux2014_s390x.whl
Size	482.1 kB
Tags	CPython 3.12 Linux glibc 2.17+ IBM System/390x
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Release files / splotrs-0.1.5-cp312-cp312-manylinux_2_17_ppc64le.manylinux2014_ppc64le.whl

Download URL	splotrs-0.1.5-cp312-cp312-manylinux_2_17_ppc64le.manylinux2014_ppc64le.whl
Size	615.2 kB
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Release files / splotrs-0.1.5-cp312-cp312-manylinux_2_17_i686.manylinux2014_i686.whl

Download URL	splotrs-0.1.5-cp312-cp312-manylinux_2_17_i686.manylinux2014_i686.whl
Size	501.9 kB
Tags	CPython 3.12 Linux glibc 2.17+ x86-32
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Release files / splotrs-0.1.5-cp312-cp312-manylinux_2_17_armv7l.manylinux2014_armv7l.whl

Download URL	splotrs-0.1.5-cp312-cp312-manylinux_2_17_armv7l.manylinux2014_armv7l.whl
Size	442.8 kB
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Release files / splotrs-0.1.5-cp312-cp312-manylinux_2_17_aarch64.manylinux2014_aarch64.whl

Download URL	splotrs-0.1.5-cp312-cp312-manylinux_2_17_aarch64.manylinux2014_aarch64.whl
Size	443.1 kB
Tags	CPython 3.12 Linux glibc 2.17+ ARM64
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Release files / splotrs-0.1.5-cp312-cp312-macosx_11_0_arm64.whl

Download URL	splotrs-0.1.5-cp312-cp312-macosx_11_0_arm64.whl
Size	408.9 kB
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Release files / splotrs-0.1.5-cp312-cp312-macosx_10_12_x86_64.whl

Download URL	splotrs-0.1.5-cp312-cp312-macosx_10_12_x86_64.whl
Size	436.4 kB
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Release files / splotrs-0.1.5-cp311-cp311-win_amd64.whl

Download URL	splotrs-0.1.5-cp311-cp311-win_amd64.whl
Size	320.0 kB
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Release files / splotrs-0.1.5-cp311-cp311-win32.whl

Download URL	splotrs-0.1.5-cp311-cp311-win32.whl
Size	297.2 kB
Tags	CPython 3.11 Windows x86-32
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Release files / splotrs-0.1.5-cp311-cp311-musllinux_1_2_x86_64.whl

Download URL	splotrs-0.1.5-cp311-cp311-musllinux_1_2_x86_64.whl
Size	686.0 kB
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Release files / splotrs-0.1.5-cp311-cp311-musllinux_1_2_i686.whl

Download URL	splotrs-0.1.5-cp311-cp311-musllinux_1_2_i686.whl
Size	716.9 kB
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Release files / splotrs-0.1.5-cp311-cp311-musllinux_1_2_armv7l.whl

Download URL	splotrs-0.1.5-cp311-cp311-musllinux_1_2_armv7l.whl
Size	721.8 kB
Tags	CPython 3.11 Linux musl 1.2+ ARMv7l
SHA-256 checksum How to use checksums	`ec9fd5bd7a8bbf0c80887c87f6eb7593d3021f4747515f9d256bf68ca243a2b3`
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Release files / splotrs-0.1.5-cp311-cp311-musllinux_1_2_aarch64.whl

Download URL	splotrs-0.1.5-cp311-cp311-musllinux_1_2_aarch64.whl
Size	623.7 kB
Tags	CPython 3.11 Linux musl 1.2+ ARM64
SHA-256 checksum How to use checksums	`a01eaa64af4c8de003d5ef44eb2d136d684503994fec62b0ec5dd128195b45da`
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Release files / splotrs-0.1.5-cp311-cp311-manylinux_2_17_x86_64.manylinux2014_x86_64.whl

Download URL	splotrs-0.1.5-cp311-cp311-manylinux_2_17_x86_64.manylinux2014_x86_64.whl
Size	486.5 kB
Tags	CPython 3.11 Linux glibc 2.17+ x86-64
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Release files / splotrs-0.1.5-cp311-cp311-manylinux_2_17_s390x.manylinux2014_s390x.whl

Download URL	splotrs-0.1.5-cp311-cp311-manylinux_2_17_s390x.manylinux2014_s390x.whl
Size	484.7 kB
Tags	CPython 3.11 Linux glibc 2.17+ IBM System/390x
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Release files / splotrs-0.1.5-cp311-cp311-manylinux_2_17_ppc64le.manylinux2014_ppc64le.whl

Download URL	splotrs-0.1.5-cp311-cp311-manylinux_2_17_ppc64le.manylinux2014_ppc64le.whl
Size	618.7 kB
Tags	CPython 3.11 Linux glibc 2.17+ PowerPC 64-le
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Release files / splotrs-0.1.5-cp311-cp311-manylinux_2_17_i686.manylinux2014_i686.whl

Download URL	splotrs-0.1.5-cp311-cp311-manylinux_2_17_i686.manylinux2014_i686.whl
Size	508.4 kB
Tags	CPython 3.11 Linux glibc 2.17+ x86-32
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Release files / splotrs-0.1.5-cp311-cp311-manylinux_2_17_armv7l.manylinux2014_armv7l.whl

Download URL	splotrs-0.1.5-cp311-cp311-manylinux_2_17_armv7l.manylinux2014_armv7l.whl
Size	446.9 kB
Tags	CPython 3.11 Linux glibc 2.17+ ARMv7l
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Release files / splotrs-0.1.5-cp311-cp311-manylinux_2_17_aarch64.manylinux2014_aarch64.whl

Download URL	splotrs-0.1.5-cp311-cp311-manylinux_2_17_aarch64.manylinux2014_aarch64.whl
Size	446.9 kB
Tags	CPython 3.11 Linux glibc 2.17+ ARM64
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Release files / splotrs-0.1.5-cp311-cp311-macosx_11_0_arm64.whl

Download URL	splotrs-0.1.5-cp311-cp311-macosx_11_0_arm64.whl
Size	414.4 kB
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SHA-256 checksum How to use checksums	`2b430b405ed010618dcc029bd50cf6204b9f9594c36f312535c07761c3190d4f`
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Release files / splotrs-0.1.5-cp311-cp311-macosx_10_12_x86_64.whl

Download URL	splotrs-0.1.5-cp311-cp311-macosx_10_12_x86_64.whl
Size	436.2 kB
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Release files / splotrs-0.1.5-cp310-cp310-win_amd64.whl

Download URL	splotrs-0.1.5-cp310-cp310-win_amd64.whl
Size	320.9 kB
Tags	CPython 3.10 Windows x86-64
SHA-256 checksum How to use checksums	`c27a9c9a57ab95d5da925cba4dd29a0ec2c874b1a79311f8276a69d7fb0d13a5`
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Release files / splotrs-0.1.5-cp310-cp310-win32.whl

Download URL	splotrs-0.1.5-cp310-cp310-win32.whl
Size	297.8 kB
Tags	CPython 3.10 Windows x86-32
SHA-256 checksum How to use checksums	`bfce13824334c50c9fd1b4d0c1cb63e07fe97c5e8a6f061f6f188bdd296ce8a0`
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Release files / splotrs-0.1.5-cp310-cp310-musllinux_1_2_x86_64.whl

Download URL	splotrs-0.1.5-cp310-cp310-musllinux_1_2_x86_64.whl
Size	687.6 kB
Tags	CPython 3.10 Linux musl 1.2+ x86-64
SHA-256 checksum How to use checksums	`3353a36f32a7cd6805ba9dbc074a0b560499705f810215445fb0d49cdc3f7aa9`
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Release files / splotrs-0.1.5-cp310-cp310-musllinux_1_2_i686.whl

Download URL	splotrs-0.1.5-cp310-cp310-musllinux_1_2_i686.whl
Size	717.6 kB
Tags	CPython 3.10 Linux musl 1.2+ x86-32
SHA-256 checksum How to use checksums	`b77a7abf28195384d5f73e0cc45910c09738ec6e948523016288ee41e87d8c7e`
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Release files / splotrs-0.1.5-cp310-cp310-musllinux_1_2_armv7l.whl

Download URL	splotrs-0.1.5-cp310-cp310-musllinux_1_2_armv7l.whl
Size	722.0 kB
Tags	CPython 3.10 Linux musl 1.2+ ARMv7l
SHA-256 checksum How to use checksums	`48bc813cebbfab74e18ebdc9bb7db92da453b65f0b5bee213866d5ae14e110a2`
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Release files / splotrs-0.1.5-cp310-cp310-musllinux_1_2_aarch64.whl

Download URL	splotrs-0.1.5-cp310-cp310-musllinux_1_2_aarch64.whl
Size	625.3 kB
Tags	CPython 3.10 Linux musl 1.2+ ARM64
SHA-256 checksum How to use checksums	`eaf2aa5bf56437c734229e64b664603e8a84e61832c86c96fa495760ea39d21e`
BLAKE2b-256 checksum How to use checksums	`696363390b0686025b3d09b6bc4ece5e7158a8ea0dd6386505ff5fb051647cb8`
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Release files / splotrs-0.1.5-cp310-cp310-manylinux_2_17_x86_64.manylinux2014_x86_64.whl

Download URL	splotrs-0.1.5-cp310-cp310-manylinux_2_17_x86_64.manylinux2014_x86_64.whl
Size	489.2 kB
Tags	CPython 3.10 Linux glibc 2.17+ x86-64
SHA-256 checksum How to use checksums	`3030153a012ca1b2fff427fefd377e94d9029bc474616471b4e28ed9ea49dd79`
BLAKE2b-256 checksum How to use checksums	`4ab8acbf8ea7a9c5840e9d076b280ee57827cf62ff9860cfa488ff7349564ef6`
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Release files / splotrs-0.1.5-cp310-cp310-manylinux_2_17_s390x.manylinux2014_s390x.whl

Download URL	splotrs-0.1.5-cp310-cp310-manylinux_2_17_s390x.manylinux2014_s390x.whl
Size	486.0 kB
Tags	CPython 3.10 Linux glibc 2.17+ IBM System/390x
SHA-256 checksum How to use checksums	`16d27adb067d494adc83f04407b11ddf045a00752e49c8e7701c40aa46b5ccb7`
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Release files / splotrs-0.1.5-cp310-cp310-manylinux_2_17_ppc64le.manylinux2014_ppc64le.whl

Download URL	splotrs-0.1.5-cp310-cp310-manylinux_2_17_ppc64le.manylinux2014_ppc64le.whl
Size	620.7 kB
Tags	CPython 3.10 Linux glibc 2.17+ PowerPC 64-le
SHA-256 checksum How to use checksums	`8e3d7cc1bdaec30c3014010dc7dfeb1a005dbecc72babe92056d6407a453d69f`
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Release files / splotrs-0.1.5-cp310-cp310-manylinux_2_17_i686.manylinux2014_i686.whl

Download URL	splotrs-0.1.5-cp310-cp310-manylinux_2_17_i686.manylinux2014_i686.whl
Size	508.3 kB
Tags	CPython 3.10 Linux glibc 2.17+ x86-32
SHA-256 checksum How to use checksums	`fd6a4d837be5c7c2cc9b208007a88182ed33c75dbe214148b77289a0bc807cfc`
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Release files / splotrs-0.1.5-cp310-cp310-manylinux_2_17_armv7l.manylinux2014_armv7l.whl

Download URL	splotrs-0.1.5-cp310-cp310-manylinux_2_17_armv7l.manylinux2014_armv7l.whl
Size	446.8 kB
Tags	CPython 3.10 Linux glibc 2.17+ ARMv7l
SHA-256 checksum How to use checksums	`21ff241a67da4049ed55202017fb2b23698a288085b3cb7d04db77766ccfcb78`
BLAKE2b-256 checksum How to use checksums	`be516cfe059bf836b767dde2b788c5337b762018956f1a831f6069497b0e5246`
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Release files / splotrs-0.1.5-cp310-cp310-manylinux_2_17_aarch64.manylinux2014_aarch64.whl

Download URL	splotrs-0.1.5-cp310-cp310-manylinux_2_17_aarch64.manylinux2014_aarch64.whl
Size	449.1 kB
Tags	CPython 3.10 Linux glibc 2.17+ ARM64
SHA-256 checksum How to use checksums	`a17ba8b12944530dd7d49f558f2ac444b33fb8122f3503aef330907a697d7d4d`
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Release files / splotrs-0.1.5-cp310-cp310-macosx_11_0_arm64.whl

Download URL	splotrs-0.1.5-cp310-cp310-macosx_11_0_arm64.whl
Size	414.9 kB
Tags	CPython 3.10 macOS 11.0+ ARM64
SHA-256 checksum How to use checksums	`e4ba030fc3a3f517e17a123e43392aaf53c9ea0bda34715ea3a8246e6dac793b`
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Release files / splotrs-0.1.5-cp310-cp310-macosx_10_12_x86_64.whl

Download URL	splotrs-0.1.5-cp310-cp310-macosx_10_12_x86_64.whl
Size	437.4 kB
Tags	CPython 3.10 macOS 10.12+ x86-64
SHA-256 checksum How to use checksums	`40c60f8c9bec627dfdf81fa095b2078b99e09198c2de749e1a6843c279edaeba`
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0.1.5 This release

Aug 5, 2026 99 release files No provenance

splotrs 0.1.5