pyinstrument
Call stack profiler for Python. Shows you why your code is slow!
Decision gist · record as of 2026-08-14
Yes. Pyinstrument is actively maintained, has no known vulnerabilities, carries a permissive license, and solves a real problem—finding performance bottlenecks—with a low-friction install and intuitive API. The medium install friction is offset by broad platform coverage and the value of its output formats. Recommended for any Python developer doing performance optimization.AI-flagged interpretation of the facts on this page — verify before relying
Before you install
- Requires Python 3.8 or later; profiling inside Docker containers may produce inaccurate results due to slow gettimeofday syscalls.
- Medium install friction due to compiled wheels for multiple platforms and Python versions (3.10–3.12 covered); active maintenance with a release 16 days ago and 8001 repository stars suggest reliable upkeep.
License · maintenance · safety
permissive license (permissive) — Permissive license (BSD) allows use in commercial and proprietary projects with minimal restrictions.
last release 2026-07-29 (16 days) · last repo commit 2026-08-04 · 8,001 stars
0 known vulnerabilities (OSV.dev, 2026-08-14) · 10,935,462 downloads/mo, #1,425 on PyPI
Alternatives
Verify before relying
pip install pyinstrument
from pyinstrument import Profiler
profiler = Profiler()
profiler.start()
# ... code to profile ...
profiler.stop()
print(profiler.output_text())- Whether the HTML renderer's interactive timeline and flat-list output modes are stable across all supported Python versions.
- Performance overhead of the timing thread option on systems with slow timers.
- Compatibility with pickle-serialized classes when using the CLI profiler.
What it is and what it does
Pyinstrument is a statistical profiler that periodically samples your Python program's call stack to measure where time is spent. Unlike deterministic profilers that instrument every function call, pyinstrument uses sampling to keep overhead low while still identifying the slowest parts of your code. It supports multiple output formats: a hierarchical text tree view for the terminal, an interactive HTML report with timeline and call-stack navigation, and integration with Jupyter notebooks via a magic command.
The package is designed for developers who need to optimize slow Python code but want a tool that's easy to use and doesn't require extensive instrumentation. It works with modern Python versions (3.8+) and includes integrations for Django, FastAPI, Litestar, and aiohttp. Recent versions added a context-manager and decorator API for profiling specific code blocks, plus lower-overhead timing options for environments like Docker where syscall-based timers are slow.
Use it for
- Profile a web application request to find which handler or middleware is causing latency.
- Identify the slowest function in a data-processing pipeline before optimizing it.
- Profile a Jupyter notebook cell to understand where computation time is spent during analysis.
- Integrate profiling into a Django or FastAPI application to capture production performance issues.
- Use the decorator API to profile individual functions or methods without modifying surrounding code.
- Export HTML reports to share performance analysis with team members or stakeholders.
Worth the install?
AI-flagged interpretation of the facts on this page. Verify before relying on it.
Yes.
Pyinstrument is actively maintained, has no known vulnerabilities, carries a permissive license, and solves a real problem—finding performance bottlenecks—with a low-friction install and intuitive API. The medium install friction is offset by broad platform coverage and the value of its output formats. Recommended for any Python developer doing performance optimization.
Install
pyinstrument on PyPI
Before you install
Medium install friction due to compiled wheels for multiple platforms and Python versions (3.10–3.12 covered); active maintenance with a release 16 days ago and 8001 repository stars suggest reliable upkeep.
Requires Python 3.8 or later; profiling inside Docker containers may produce inaccurate results due to slow gettimeofday syscalls.
License in practice
Permissive license (BSD) allows use in commercial and proprietary projects with minimal restrictions.
Quickstart
pip install pyinstrument
from pyinstrument import Profiler
profiler = Profiler()
profiler.start()
# ... code to profile ...
profiler.stop()
print(profiler.output_text())Verify before relying
- Whether the HTML renderer's interactive timeline and flat-list output modes are stable across all supported Python versions.
- Performance overhead of the timing thread option on systems with slow timers.
- Compatibility with pickle-serialized classes when using the CLI profiler.
Package facts
| License | permissive license permissive |
| Python support | Supports the current Python release >=3.8 |
| Install friction | Medium. Platform-specific wheel |
| Runtime dependencies | None |
| Maintenance | Actively maintained 16 days since the last release |
| Last repo commit | |
| First released | |
| Downloads | 10,935,462 / month, #1,425 on PyPI 30-day window, as of 2026-08-14 |
| Known vulnerabilities | None known OSV.dev, checked 2026-08-14 |
| Classifiers | Environment :: ConsoleEnvironment :: Web EnvironmentIntended Audience :: DevelopersLicense :: OSI Approved :: BSD LicenseOperating System :: MacOSOperating System :: Microsoft :: WindowsOperating System :: POSIXTopic :: Software Development :: DebuggersTopic :: Software Development :: Testing |
Evidence: pyinstrument-5.1.3-cp310-cp310-macosx_10_9_universal2.whl; pyinstrument-5.1.3-cp310-cp310-macosx_11_0_arm64.whl; pyinstrument-5.1.3-cp310-cp310-manylinux2014_aarch64.manylinux_2_17_aarch64.manylinux_2_28_aarch64.whl; pyinstrument-5.1.3-cp310-cp310-manylinux2014_x86_64.manylinux_2_17_x86_64.manylinux_2_28_x86_64.whl; pyinstrument-5.1.3-cp310-cp310-musllinux_1_2_aarch64.whl; pyinstrument-5.1.3-cp310-cp310-musllinux_1_2_x86_64.whl; pyinstrument-5.1.3-cp310-cp310-win32.whl; pyinstrument-5.1.3-cp310-cp310-win_amd64.whl; pyinstrument-5.1.3-cp311-cp311-macosx_10_9_universal2.whl; pyinstrument-5.1.3-cp311-cp311-macosx_11_0_arm64.whl; pyinstrument-5.1.3-cp311-cp311-manylinux2014_aarch64.manylinux_2_17_aarch64.manylinux_2_28_aarch64.whl; pyinstrument-5.1.3-cp311-cp311-manylinux2014_x86_64.manylinux_2_17_x86_64.manylinux_2_28_x86_64.whl; pyinstrument-5.1.3-cp311-cp311-musllinux_1_2_aarch64.whl; pyinstrument-5.1.3-cp311-cp311-musllinux_1_2_x86_64.whl; pyinstrument-5.1.3-cp311-cp311-win32.whl; pyinstrument-5.1.3-cp311-cp311-win_amd64.whl; pyinstrument-5.1.3-cp312-cp312-macosx_10_13_universal2.whl; pyinstrument-5.1.3-cp312-cp312-macosx_11_0_arm64.whl; pyinstrument-5.1.3-cp312-cp312-manylinux2014_aarch64.manylinux_2_17_aarch64.manylinux_2_28_aarch64.whl; pyinstrument-5.1.3-cp312-cp312-manylinux2014_x86_64.manylinux_2_17_x86_64.manylinux_2_28_x86_64.whl
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