mprofile

library0.0.15pypypi✓ verified 85d ago

mprofile is a low-overhead sampling memory profiler for Python, derived from heapprof, with an interface similar to tracemalloc. It attempts to give results comparable to tracemalloc, but uses statistical sampling to lower memory and CPU overhead. The sampling algorithm is the one used by tcmalloc and Golang heap profilers. The current version is 0.0.15, and it is compatible with Python >= 3.4.

observability

pip install mprofile

github ↗package ↗

INSTALL

IMPORT

SIG · MPROFILE

mprofile

observabilitypythonv0.0.15

Install

1.7s avg

Import

—

Disk

20MB

Pass rate

4/ 10

Env Coverage4 / 10

glibc

3.9–3.13

musl

3.9–3.13

Install & Compatibility

Where this runs

tested against v0.0.15 · pip install

no network on importno background threads

Install × environment matrix

Each cell = how many times install + import succeeded across repeated harness runs. Partial = flaky.
glibc = Debian/Ubuntu slim · musl = Alpine Linux

musl

glibc

py 3.10

✕ build_error

✓ 1.78s

py 3.11

✕ build_error

✓ 1.7s

py 3.12

✕ build_error

✓ 1.63s

py 3.13

✕ build_error

py 3.9

✕ build_error

✓ 1.85s

20MB installed

● package 20MB

Code

Verified usage

Verified import paths — ran on the pinned version, not inferred.

mprofile

✓ import mprofile

This quickstart demonstrates how to initialize `mprofile`, simulate some memory allocation, take a snapshot of the current memory usage, and print the top memory-consuming lines. The `sample_rate` is set to the recommended 128KB for a balance between overhead and precision.

import mprofile import os # Start profiling with a recommended sample rate (128KB) for low overhead mprofile.start(sample_rate=128 * 1024) # Simulate some memory allocation data = [] for i in range(100_000): data.append(os.urandom(100)) # Allocate 100 bytes per iteration # Take a snapshot of memory usage snapshot = mprofile.take_snapshot() # Print top 5 memory consuming lines and their statistics print("Top 5 memory consuming lines:") for stat in snapshot.statistics(key_type='lineno')[:5]: print(stat) # Stop profiling mprofile.stop()

mprofile --version

Debug

Known issues

gotchamprofile is compatible with Python >= 3.4. Using it with earlier versions of Python (< 3.4) requires building CPython from source and manually applying `pytracemalloc` patches, which is a complex setup.

fix

Use Python 3.4 or newer, or follow the complex manual build process for older Python versions.

affects: < 3.4

gotchamprofile uses statistical sampling for memory profiling, not comprehensive tracing like `tracemalloc`. This design choice prioritizes low overhead, meaning the reported memory usage is an estimate and may not be an exact, byte-for-byte measurement. Interpret results with this in mind.

fix

Understand that mprofile provides sampled estimates, which are generally sufficient for identifying memory hotspots but may not be suitable for precise memory accounting.

affects: All versions

deprecatedVersions of mprofile prior to 0.0.13 caused a `DeprecationWarning` in Python 3.8+ due to changes in the `collections.abc` module.

fix

Upgrade to mprofile version 0.0.13 or newer (`pip install --upgrade mprofile`).

affects: < 0.0.13 (on Python 3.8+)

gotchaVersions of mprofile prior to 0.0.12 were known to cause segmentation faults when used on Ubuntu 20.04.

fix

Upgrade to mprofile version 0.0.12 or newer (`pip install --upgrade mprofile`).

affects: < 0.0.12 (on Ubuntu 20.04)

Errors

Common errors & fixes

DeprecationWarning: Using or importing the ABCs from 'collections' instead of from 'collections.abc' is deprecated

Running mprofile on Python 3.8+ with a version of mprofile older than 0.0.13.

fix

Upgrade mprofile to version 0.0.13 or newer: `pip install --upgrade mprofile`.

Segmentation fault (core dumped)

This error specifically occurred on Ubuntu 20.04 with mprofile versions older than 0.0.12.

fix

Upgrade mprofile to version 0.0.12 or newer: `pip install --upgrade mprofile`.

ModuleNotFoundError: No module named 'mprofile'

The mprofile package is not installed in the current Python environment.

fix

Install the package using pip: `pip install mprofile`.

Upgrade

Version history

0.0.15latest on PyPI · released Jan 2, 2023

Audit

Dependencies

No dependency data recorded yet.

Agent activity

14 hits · last 30 days

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OpenAI (training)

Resources

githubhttp://github.com/timpalpant/mprofile ↗

packagehttps://pypi.org/project/mprofile/ ↗