Registry / data / numpy-minmax

numpy-minmax

library0.6.0pypypi✓ verified 21d ago

numpy-minmax is a fast Python library designed to efficiently find both the minimum and maximum values within a NumPy array. It achieves significant speedups (roughly 2.3x faster than calling `numpy.amin` and `numpy.amax` separately) by leveraging C implementations and SIMD instructions (AVX/AVX512). The library is actively maintained with frequent releases, with version 0.5.0 being the latest stable release as of June 2025.

data

pip install numpy-minmax

github ↗package ↗

INSTALL

IMPORT

SIG · NUMPY-MINMAX

numpy-minmax

datapythonv0.6.0

Install

3.7s avg

Import

251ms

Disk

89MB

Pass rate

8/ 10

Env Coverage8 / 10

glibc

3.9–3.13

musl

3.9–3.13

Install & Compatibility

Where this runs

tested against v0.6.0 · pip install

no network on importno background threads

Install × environment matrix

Each cell = how many times install + import succeeded across repeated harness runs. Partial = flaky.
glibc = Debian/Ubuntu slim · musl = Alpine Linux

musl

glibc

py 3.10

✓ —

✓ 3.8s

py 3.11

✓ —

✓ 3.6s

py 3.12

✓ —

✓ 3.5s

py 3.13

✓ —

✓ 4s

py 3.9

✕ build_error

89MB installed

● package 89MB

Code

Verified usage

Verified import paths — ran on the pinned version, not inferred.

minmax

✓ from numpy_minmax import minmax

Initialize a NumPy array and use `numpy_minmax.minmax()` to quickly get both the minimum and maximum values. The function returns a tuple `(min_value, max_value)`.

import numpy as np from numpy_minmax import minmax arr = np.arange(1337, dtype=np.float32) min_val, max_val = minmax(arr) print(f"Min value: {min_val}") print(f"Max value: {max_val}") # Expected output: Min value: 0.0, Max value: 1336.0

Debug

Known issues

gotchaPerformance benefits of `numpy-minmax` are primarily realized for `float32` and `int16` arrays that are C-contiguous, F-contiguous, or 1D strided. For other data types or strided arrays with `ndim >= 2`, the function falls back to `numpy.amin` and `numpy.amax`, negating any performance gain.

fix

Ensure input arrays are `float32` or `int16` and are C-contiguous, F-contiguous, or 1D strided when optimal performance is critical.

affects: All versions

breakingThe library has a history of adjusting Python version support with minor releases. For example, version 0.5.0 added Python 3.13 support, while the upcoming 0.6.0 will remove Python 3.9 support. Users should consult the `CHANGELOG.md` on GitHub or PyPI for supported Python versions to ensure compatibility.

fix

Always check the `CHANGELOG.md` or PyPI metadata for the `requires_python` field before upgrading or deploying to new Python environments.

affects: 0.1.0 - 0.5.0 (and future versions)

Errors

Common errors & fixes

ModuleNotFoundError: No module named 'numpy_minmax'

The `numpy-minmax` library has not been installed in your Python environment or the environment where you are running your script.

fix

Ensure the library is installed using pip: `pip install numpy-minmax`

AttributeError: module 'numpy_minmax' has no attribute 'min_max'

You are attempting to call a function named `min_max` (with an underscore) which does not exist. The correct function name is `minmax` (without an underscore).

fix

Change the function call from `numpy_minmax.min_max(arr)` to `numpy_minmax.minmax(arr)`.

ValueError: zero-size array to reduction operation minmax which has no identity

The `numpy_minmax.minmax` function was called with an empty NumPy array, which does not have a defined minimum or maximum value without an identity element.

fix

Before calling `numpy_minmax.minmax`, ensure the array is not empty. You can add a check like `if arr.size > 0: min_val, max_val = numpy_minmax.minmax(arr)`.

TypeError: 'list' object cannot be interpreted as an array

The `numpy_minmax.minmax` function expects a NumPy array as input, but a standard Python list was provided instead.

fix

Convert the Python list to a NumPy array before passing it to the function: `import numpy as np; my_list = [1, 2, 3]; my_array = np.array(my_list); min_val, max_val = numpy_minmax.minmax(my_array)`.

Upgrade

Version history

0.6.0latest on PyPI · released Jun 26, 2026

Audit

Dependencies

numpyrequiredCore functionality relies on NumPy arrays; compatible with numpy >=1.21,<2 for version 0.3.0 and later.

Agent activity

3 hits · last 30 days

node

Resources

githubhttps://github.com/nomonosound/numpy-minmax ↗

packagehttps://pypi.org/project/numpy-minmax/ ↗