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guppy3

Guppy 3 -- Guppy-PE ported to Python 3

With conditionsPyPI DebuggersReleased May 20261.4M downloads / moMITPlatform wheel

Decision gist · record as of 2026-08-14

platform wheels — guppy3-3.1.7-cp310-cp310-macosx_10_9_x86_64.whl · guppy3-3.1.7-cp310-cp310-macosx_11_0_arm64.whl · guppy3-3.1.7-cp310-cp310-manylinux2014_aarch64.manylinux_2_17_aarch64.manylinux_2_28_aarch64.whl
v3.1.7 · released 2026-05-11 · Python >=3.10

Yes, if you need to debug Python memory issues or profile heap usage in CPython applications. The package is actively maintained, has no known vulnerabilities, and carries a permissive MIT license. Install friction is moderate due to compiled extensions, but pre-built wheels cover common platforms. Not suitable if you use PyPy, free-threaded CPython, or Python versions below 3.10.AI-flagged interpretation of the facts on this page — verify before relying

Before you install

  • Requires CPython 3.10, 3.11, 3.12, 3.13, or 3.14; PyPy and free-threaded CPython are not supported.
  • Tkinter is needed for the graphical browser.
  • Medium install friction due to compiled C extensions across multiple platforms and architectures.

License · maintenance · safety

MIT (permissive) — MIT license permits free use, modification, and redistribution with minimal restrictions, making it suitable for both open-source and commercial projects.

last release 2026-05-11 (95 days) · last repo commit 2026-05-18 · 431 stars

0 known vulnerabilities (OSV.dev, 2026-08-14) · 1,382,674 downloads/mo, #3,980 on PyPI

Verify before relying

pip install guppy3

from guppy import hpy
h = hpy()
h.heap()
h.iso(1, [], {})
  • Whether the graphical browser is actively used or primarily a legacy feature
  • Performance overhead and suitability for production vs. development-only use
  • Practical memory profiling workflow and typical use patterns in real applications
Same gist for agents: .md · .json

What it is and what it does

Guppy 3 is a heap analysis and memory profiling toolkit for CPython that lets you inspect live Python objects, understand memory allocation patterns, and track down memory leaks. It provides an interactive session interface where you create a heap analysis context, query the heap to see object counts and sizes grouped by type, and trace paths from the root to individual objects. The package includes submodules for bitsets implemented in C, a specification language, and support utilities.

The tool is designed for developers debugging memory issues in Python applications. It works by examining the live heap state and presenting partitions of objects with cumulative size analysis, making it practical for identifying which types consume the most memory. It requires CPython 3.10 or later and does not support PyPy or free-threaded CPython due to implementation constraints.

Use it for

  • Identify which object types consume the most memory in a running Python application.
  • Trace reference chains from the garbage collector root to specific large objects.
  • Profile memory usage in long-running services to detect unexpected growth patterns.
  • Debug memory issues in framework-based applications by inspecting heap state at runtime.
  • Analyze object allocation patterns during development to optimize memory-intensive code.

Worth the install?

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

With conditions

Yes, if you need to debug Python memory issues or profile heap usage in CPython applications.

The package is actively maintained, has no known vulnerabilities, and carries a permissive MIT license. Install friction is moderate due to compiled extensions, but pre-built wheels cover common platforms. Not suitable if you use PyPy, free-threaded CPython, or Python versions below 3.10.

Install

guppy3 on PyPI

Before you install

Medium install friction due to compiled C extensions across multiple platforms and architectures. The package is actively maintained with a recent release (95 days ago) and receives steady downloads, though it requires CPython 3.10 or later and does not support PyPy or free-threaded CPython.

Requires CPython 3.10, 3.11, 3.12, 3.13, or 3.14; PyPy and free-threaded CPython are not supported. Tkinter is needed for the graphical browser.

License in practice

MIT license permits free use, modification, and redistribution with minimal restrictions, making it suitable for both open-source and commercial projects.

Quickstart

pip install guppy3

from guppy import hpy
h = hpy()
h.heap()
h.iso(1, [], {})

Verify before relying

  • Whether the graphical browser is actively used or primarily a legacy feature
  • Performance overhead and suitability for production vs. development-only use
  • Practical memory profiling workflow and typical use patterns in real applications

Package facts

LicenseMIT permissive
Python supportSupports the current Python release >=3.10
Install frictionMedium. Platform-specific wheel
Runtime dependenciesNone
MaintenanceActively maintained 95 days since the last release
Last repo commit
First released
Downloads1,382,674 / month, #3,980 on PyPI 30-day window, as of 2026-08-14
Known vulnerabilitiesNone known OSV.dev, checked 2026-08-14
Classifiers
Development Status :: 4 - BetaEnvironment :: ConsoleIntended Audience :: DevelopersOperating System :: OS IndependentProgramming Language :: CProgramming Language :: Python :: 3Programming Language :: Python :: Implementation :: CPythonTopic :: Software Development :: Debuggers

Evidence: guppy3-3.1.7-cp310-cp310-macosx_10_9_x86_64.whl; guppy3-3.1.7-cp310-cp310-macosx_11_0_arm64.whl; guppy3-3.1.7-cp310-cp310-manylinux2014_aarch64.manylinux_2_17_aarch64.manylinux_2_28_aarch64.whl; guppy3-3.1.7-cp310-cp310-manylinux2014_armv7l.manylinux_2_17_armv7l.manylinux_2_31_armv7l.whl; guppy3-3.1.7-cp310-cp310-manylinux2014_ppc64le.manylinux_2_17_ppc64le.manylinux_2_28_ppc64le.whl; guppy3-3.1.7-cp310-cp310-manylinux2014_s390x.manylinux_2_17_s390x.manylinux_2_28_s390x.whl; guppy3-3.1.7-cp310-cp310-manylinux2014_x86_64.manylinux_2_17_x86_64.manylinux_2_28_x86_64.whl; guppy3-3.1.7-cp310-cp310-musllinux_1_2_aarch64.whl; guppy3-3.1.7-cp310-cp310-musllinux_1_2_armv7l.whl; guppy3-3.1.7-cp310-cp310-musllinux_1_2_ppc64le.whl; guppy3-3.1.7-cp310-cp310-musllinux_1_2_s390x.whl; guppy3-3.1.7-cp310-cp310-musllinux_1_2_x86_64.whl; guppy3-3.1.7-cp310-cp310-win32.whl; guppy3-3.1.7-cp310-cp310-win_amd64.whl; guppy3-3.1.7-cp310-cp310-win_arm64.whl; guppy3-3.1.7-cp311-cp311-macosx_10_9_x86_64.whl; guppy3-3.1.7-cp311-cp311-macosx_11_0_arm64.whl; guppy3-3.1.7-cp311-cp311-manylinux2014_aarch64.manylinux_2_17_aarch64.manylinux_2_28_aarch64.whl; guppy3-3.1.7-cp311-cp311-manylinux2014_armv7l.manylinux_2_17_armv7l.manylinux_2_31_armv7l.whl; guppy3-3.1.7-cp311-cp311-manylinux2014_ppc64le.manylinux_2_17_ppc64le.manylinux_2_28_ppc64le.whl

Tags

Capabilities
python memory profilingheap analysis toolmemory leak detectionobject allocation trackingpython memory debuggingheap introspectionmemory usage analysis
Topics
memory-profilingheap-analysisdebugging

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