pytest-memray

library1.10.0pypypi✓ verified 27d ago

pytest-memray is a pytest plugin for easy integration of memray, a powerful memory profiler for Python. It allows developers to analyze memory allocations, detect memory leaks, and identify memory-intensive hotspots directly within their pytest test suite. The current version, 1.8.0, supports Python 3.8 and higher, and is actively maintained with regular releases.

testing observability

pip install pytest-memray

github ↗package ↗docs ↗

INSTALL

IMPORT

SIG · PYTEST-MEMRAY

pytest-memray

testingpythonv1.10.0

Install

4.5s avg

Import

554ms

Disk

76MB

Pass rate

10/ 10

Env Coverage10 / 10

glibc

3.9–3.13

musl

3.9–3.13

Install & Compatibility

Where this runs

tested against v1.10.0 · 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

py 3.10–3.95 runs

installs and imports cleanly · install 0.0s · import 0.590s · 78.3MB

glibc

py 3.10–3.95 runs

installs and imports cleanly · install 4.5s · import 0.518s · 74MB

76MB installed

● package 76MB

Code

Verified usage

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

LeaksFilterFunction

✓ from pytest_memray import LeaksFilterFunction

✗ import pytest

marks

✓ from pytest_memray import marks

✗ import pytest

Stack

✓ from pytest_memray import Stack

✗ import pytest

To activate `pytest-memray` during a test run, simply add the `--memray` flag to your `pytest` command. For granular control and enforcement within tests, use markers like `@pytest.mark.limit_memory` to set a peak memory limit or `@pytest.mark.limit_leaks` to detect memory leaks. If a test exceeds its limit, `pytest` will report a failure.

import pytest @pytest.mark.limit_memory('24 MB') def test_foobar(): data = [i for i in range(1_000_000)] # Allocates ~8MB assert len(data) == 1_000_000 # To run this test with memory profiling: # pytest --memray your_test_file.py

Debug

Known issues

gotchaPython's internal object allocators, caches (e.g., `re`, `logging`), and pytest's output capturing can result in reported allocations that are not true application-level memory leaks. Interpreting memory reports requires understanding these internal behaviors.

fix

Account for Python and pytest internal allocations. Run tests in a loop or with `current_thread_only=True` in markers for clearer leak detection. Consider `memray`'s own documentation on 'false positives'.

affects: All versions

gotchaThe underlying `memray` library, which `pytest-memray` integrates with, primarily supports Linux and macOS. While the Python package can be installed elsewhere, full functionality and development might be limited or require a POSIX-compliant system, especially for native-level tracking.

fix

Run tests and profiling on Linux or macOS environments for optimal results and full feature access.

affects: All versions

gotchaPrior to version 1.3.2, `pytest-memray` had compatibility issues with `pytest-xdist` when running tests in parallel, potentially leading to incorrect or failed memory tracking. Users on older versions might experience instability.

fix

Upgrade to `pytest-memray` version 1.3.2 or newer to ensure proper compatibility with `pytest-xdist`.

affects: <1.3.2

gotchaUsing very long test names or file paths can lead to `OSError` exceptions due to file system limitations when `memray` attempts to write its binary capture files. This can prevent reports from being generated.

fix

Keep test file paths and test function names reasonably short, especially if encountering `OSError` related to filename length.

affects: All versions

breakingThe `limit_memory` and `limit_leaks` markers in versions prior to 1.6.0 tracked all memory allocations across all threads. Version 1.6.0 introduced a `current_thread_only=True` keyword argument to these markers, allowing more precise tracking of allocations solely within the test's thread. Existing tests on older versions might report higher memory usage if other threads were active.

fix

Upgrade to `pytest-memray` 1.6.0 or newer and consider adding `current_thread_only=True` to your markers for more focused memory tracking, if appropriate for your tests.

affects: <1.6.0

Upgrade

Version history

1.10.0latest on PyPI · released Aug 7, 2026

Audit

Dependencies

pytestrequiredRequired as it is a pytest plugin.

memrayrequiredThe core memory profiling library that pytest-memray integrates with.

Agent activity

22 hits · last 30 days

node

OpenAI (training)

Resources

githubhttps://github.com/bloomberg/pytest-memray ↗

packagehttps://pypi.org/project/pytest-memray/ ↗

docshttps://pytest-memray.readthedocs.io ↗