skillfed

whylogs-sketching

sketching library of whylogs

whylogs-sketching v3.4.1.dev3 107.5K downloads/30d#12,611 on PyPI0
Permissive license Apache License 2.0 DORMANT released

What it is and what it does

whylogs-sketching is a Python wrapper around Apache DataSketches' core C++ library, exposing sketching algorithms for efficient approximate computation on large or streaming datasets. The library implements algorithms that allow you to estimate cardinality, compute set operations, and summarize data distributions without storing the full dataset in memory.

The package is built as compiled wheels for multiple Python versions and platforms (macOS, Linux, Windows). It has no runtime dependencies and installs as a self-contained binary component. However, the package has been dormant since its latest release on 2022-09-01, with no recent maintenance activity, which may affect compatibility with newer Python releases or bug fixes.

Use it for:

  • Estimate cardinality of large datasets or streams without storing all elements in memory
  • Compute approximate set operations across distributed data sources
  • Monitor data quality and detect distribution shifts in streaming pipelines
  • Build efficient approximate frequency tables or quantile sketches for exploratory data analysis

Worth the install?

AI-flagged interpretation of the facts on this page — verify before relying

Provides Python bindings to Apache DataSketches' core C++ sketching algorithms for probabilistic data analysis and cardinality estimation.

Yes, if you need sketching algorithms and can tolerate dormant maintenance. The package is permissively licensed, has no runtime dependencies, and provides access to well-established Apache DataSketches algorithms. However, verify that version 3.4.1.dev3 works with your target Python version and that the lack of recent maintenance does not conflict with your stability requirements.

Install

whylogs-sketching on PyPI

pip

pip install whylogs-sketching

uv

uv add whylogs-sketching

poetry

poetry add whylogs-sketching

Installing whylogs-sketching

Before you install

Medium install friction due to compiled wheel distribution across multiple Python versions and platforms. Package is dormant—last release was 2022-09-01 with no commits since 2024-10-22, indicating no active maintenance.

License in practice

Licensed under Apache License 2.0 (permissive), allowing commercial use, modification, and distribution with minimal restrictions.

Quickstart

pip install whylogs-sketching

import whylogs_sketching
# Use sketching algorithms from the Apache DataSketches library

Requires a compatible Python version; check available wheels for your platform and Python version.

Verify before relying

  • Whether this package is still actively maintained or if whylogs has migrated to a different sketching implementation
  • Compatibility with Python versions newer than those with available wheels given the dev version and dormant status
  • Whether the C++11 requirement and compiled nature create deployment constraints in containerized environments

Package facts

License Apache License 2.0 (permissive)
Python support not specified
Install friction medium — platform-specific wheel
Runtime dependencies none
Maintenance dormant — 1,443 days since the last release
Last repo commit
First released
Downloads 107,523/month — #12,611 on PyPI (30-day window, as of 2026-08-14)
Known vulnerabilities none known (OSV.dev, checked 2026-08-14)

Evidence: whylogs_sketching-3.4.1.dev3-cp310-cp310-macosx_10_9_x86_64.whl; whylogs_sketching-3.4.1.dev3-cp310-cp310-macosx_11_0_arm64.whl; whylogs_sketching-3.4.1.dev3-cp310-cp310-manylinux_2_17_aarch64.manylinux2014_aarch64.whl; whylogs_sketching-3.4.1.dev3-cp310-cp310-manylinux_2_17_x86_64.manylinux2014_x86_64.whl; whylogs_sketching-3.4.1.dev3-cp310-cp310-musllinux_1_1_x86_64.whl; whylogs_sketching-3.4.1.dev3-cp310-cp310-win_amd64.whl; whylogs_sketching-3.4.1.dev3-cp311-cp311-macosx_10_9_x86_64.whl; whylogs_sketching-3.4.1.dev3-cp311-cp311-manylinux_2_17_x86_64.manylinux2014_x86_64.whl; whylogs_sketching-3.4.1.dev3-cp311-cp311-musllinux_1_1_x86_64.whl; whylogs_sketching-3.4.1.dev3-cp311-cp311-win_amd64.whl; whylogs_sketching-3.4.1.dev3-cp312-cp312-manylinux_2_17_aarch64.manylinux2014_aarch64.whl; whylogs_sketching-3.4.1.dev3-cp312-cp312-manylinux_2_17_x86_64.manylinux2014_x86_64.whl; whylogs_sketching-3.4.1.dev3-cp312-cp312-musllinux_1_2_aarch64.whl; whylogs_sketching-3.4.1.dev3-cp36-cp36m-macosx_10_9_x86_64.whl; whylogs_sketching-3.4.1.dev3-cp36-cp36m-manylinux_2_17_x86_64.manylinux2014_x86_64.whl; whylogs_sketching-3.4.1.dev3-cp36-cp36m-musllinux_1_1_x86_64.whl; whylogs_sketching-3.4.1.dev3-cp36-cp36m-win_amd64.whl; whylogs_sketching-3.4.1.dev3-cp37-cp37m-macosx_10_9_x86_64.whl; whylogs_sketching-3.4.1.dev3-cp37-cp37m-manylinux_2_17_x86_64.manylinux2014_x86_64.whl; whylogs_sketching-3.4.1.dev3-cp37-cp37m-musllinux_1_1_x86_64.whl

Tags

sketching algorithms pythoncardinality estimation libraryprobabilistic data structuresdatasketches python bindingsstreaming data summarizationapproximate countingdata sketches
sketching-algorithmsapproximate-computingdata-structures

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