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whylogs

Profile and monitor your ML data pipeline end-to-end

With conditionsPyPI Artificial IntelligenceReleased Dec 2024172.1K downloads / moApache-2.0Pure Python

Decision gist · record as of 2026-08-14

pure-Python wheel — whylogs-1.6.4-py3-none-any.whl
v1.6.4 · released 2024-12-03 · Python <4,>=3.7.1 · 8 runtime deps: backoff, importlib-metadata, platformdirs, protobuf, requests, typing-extensions, whylabs-client, whylogs-sketching

Yes, if you need data profiling and drift detection for a stable ML pipeline and can tolerate dormant maintenance. The low install friction, permissive license, and absence of known vulnerabilities make it safe to adopt. However, the 619-day gap since the last release means no active support for new Python versions, dependency updates, or bug fixes—verify compatibility with your current environment before relying on it for production.AI-flagged interpretation of the facts on this page — verify before relying

Before you install

  • Low install friction with a pure-Python wheel and eight runtime dependencies including protobuf, requests, and whylabs-client.
  • Maintenance is dormant—no release in 619 days—so expect no active bug fixes or feature updates.

License · maintenance · safety

Apache-2.0 (permissive) — Licensed under Apache-2.0 (permissive), allowing commercial and private use with minimal restrictions; attribution required.

last release 2024-12-03 (619 days)

0 known vulnerabilities (OSV.dev, 2026-08-14) · 172,055 downloads/mo, #10,348 on PyPI

Verify before relying

pip install whylogs

import whylogs as why

results = why.log(data)
  • Whether dormant status (619 days since last release) affects compatibility with recent versions of runtime dependencies
  • Whether whylabs-client dependency requires API credentials or can function offline
  • Performance characteristics on very large datasets
Same gist for agents: .md · .json

What it is and what it does

whylogs is a data profiling library that generates statistical summaries (called profiles) of datasets to enable monitoring and validation in machine learning workflows. It depends on protobuf for serialization, requests for HTTP communication, and whylabs-client for integration with WhyLabs services. The core use case is creating profiles from data, then using those profiles to track data distributions over time, detect anomalies, and validate that incoming data meets expected constraints.

The library supports Python 3.7.1 through 3.11 and is designed for data scientists, ML engineers, and data engineers working on data quality, drift detection, and pipeline monitoring. However, maintenance is dormant—the last release was 619 days ago—so the package receives no active updates, bug fixes, or compatibility maintenance.

Use it for

  • Detect data drift in model input features by comparing profiles across time periods
  • Validate data quality constraints in a data pipeline before feeding data to models
  • Perform exploratory data analysis of large datasets by generating summary statistics
  • Track training-serving skew by profiling training data and comparing to production data
  • Enable data auditing and governance by logging dataset profiles for compliance

Worth the install?

AI-flagged interpretation of the facts on this page. Verify before relying on it.

With conditions

Yes, if you need data profiling and drift detection for a stable ML pipeline and can tolerate dormant maintenance.

The low install friction, permissive license, and absence of known vulnerabilities make it safe to adopt. However, the 619-day gap since the last release means no active support for new Python versions, dependency updates, or bug fixes—verify compatibility with your current environment before relying on it for production.

Install

whylogs on PyPI

Before you install

Low install friction with a pure-Python wheel and eight runtime dependencies including protobuf, requests, and whylabs-client. Maintenance is dormant—no release in 619 days—so expect no active bug fixes or feature updates.

License in practice

Licensed under Apache-2.0 (permissive), allowing commercial and private use with minimal restrictions; attribution required.

Quickstart

pip install whylogs

import whylogs as why

results = why.log(data)

Verify before relying

  • Whether dormant status (619 days since last release) affects compatibility with recent versions of runtime dependencies
  • Whether whylabs-client dependency requires API credentials or can function offline
  • Performance characteristics on very large datasets

Package facts

LicenseApache-2.0 permissive
Python supportSupports the current Python release <4,>=3.7.1
Install frictionLow. Pure-Python wheel
Runtime dependencies
8 packages
backoffimportlib-metadataplatformdirsprotobufrequeststyping-extensionswhylabs-clientwhylogs-sketching
MaintenanceDormant 619 days since the last release
First released
Downloads172,055 / month, #10,348 on PyPI 30-day window, as of 2026-08-14
Known vulnerabilitiesNone known OSV.dev, checked 2026-08-14
Classifiers
License :: OSI Approved :: Apache Software LicenseProgramming Language :: Python :: 3Programming Language :: Python :: 3.10Programming Language :: Python :: 3.11Programming Language :: Python :: 3.8Programming Language :: Python :: 3.9

Evidence: whylogs-1.6.4-py3-none-any.whl

Tags

Capabilities
data profiling and monitoringdetect data driftdata quality validationml data pipeline monitoringdataset statistics loggingtraining serving skew detectiondata distribution tracking
Topics
data-profilingml-monitoringdrift-detection

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