---
id: pympler
version: "1.1"
license: Apache License, Version 2.0
license_treatment: permissive
maintenance: aging
---

# Pympler — A development tool to measure, monitor and analyze the memory behavior of Python objects.

License: permissive · Maintenance: aging · Downloads: 6.2M/mo

## What it is and what it does

Pympler is a memory profiling and analysis tool for Python applications. It combines three integrated subsystems—asizeof for object size measurement, muppy for online application monitoring, and a class tracker for offline lifetime analysis—along with a web frontend for visualizing process statistics and garbage collection behavior. The tool is written entirely in Python and requires no external dependencies on Linux and macOS; Windows users need pywin32.

Developers use Pympler to diagnose memory issues in running applications: identifying which objects consume the most memory, tracking how object lifetimes correlate with memory growth, and spotting unexpected memory bloat. It's particularly useful during development and debugging phases when memory behavior is unclear or suspected to be problematic.

Use it for:

- Identify which Python objects are consuming the most memory in a long-running application.
- Track the lifetime and growth patterns of specific classes to detect memory leaks or unexpected retention.
- Monitor memory behavior of a running application in real time using muppy's online profiling.
- Analyze garbage collection and heap statistics through the web profiling frontend.
- Diagnose memory bloat during development before deploying to production.

## Worth the install?

AI-flagged interpretation of the facts above — verify before relying.

Pympler measures, monitors, and analyzes memory behavior of Python objects in running applications, helping identify memory bloat and unexpected runtime issues through size profiling, online monitoring, and lifetime analysis.

Yes, if you need to diagnose memory behavior in Python applications. Pympler is well-established, permissively licensed, has low install friction, and carries no known vulnerabilities. The aging maintenance status (777 days since release) is a minor concern but not a blocker—recent commits show active stewardship. Install it when memory profiling is part of your development workflow.

## Install

pip install pympler
uv add pympler
poetry add pympler

## Installing Pympler

Before you install: Low install friction with a pure-Python implementation on Linux and macOS; Windows requires pywin32. The package is aging (777 days since last release) but remains actively maintained with recent commits and a stable repository.

License in practice: Apache License 2.0 is permissive, allowing commercial and private use with minimal restrictions—suitable for most development and production scenarios.

Quickstart:

pip install Pympler

from pympler import asizeof
print(asizeof.asizeof([1, 2, 3]))

On Windows, pywin32 must be installed as a dependency; on Linux and macOS, no external dependencies beyond Python standard library.

Verify before relying:

- Whether the aging maintenance status (777 days since release) affects compatibility with Python versions beyond 3.12.
- Real-world performance impact when profiling large, long-running applications with many objects.

## Package facts

- License: Apache License, Version 2.0 (permissive)
- Python support: supports_current
- Install friction: low
- Maintenance: aging
- Downloads: 6.2M/month (top 5,000 on PyPI)
- Known vulnerabilities: none known

## Tags

memory profiling python, object size analysis, memory leak detection, python memory monitoring, heap analysis tool, memory behavior tracking, python memory debugging, memory-profiling, debugging, performance-analysis

[View on SkillFed](https://skillfed.io/packages/pympler) · [View on PyPI](https://pypi.org/project/pympler/)