Using Memray for Python Memory Profiling and Leak Detection

Memray is a robust Python memory analysis tool developed by CPython core contributors, designed to help developers locate memory leaks and high‑memory‑consumption hotspots by providing detailed allocation tracking and stack traces.

Installation: Install Memray via pip with pip install memray .

Command‑line usage: Run your script with memray run your_script.py to generate a .mprof file, then view the interactive report using memray show your_script.mprof , which displays allocation counts, sizes, and call stacks.

Programmatic usage: Import the Tracker class to profile specific code sections. Example:

from memray import Tracker

def main():

with Tracker("/path/to/output/file.mprof"):

# your code logic

pass

if __name__ == "__main__":

main()

Report contents: The Memray report includes cumulative allocations (which functions allocate how much memory and whether it is freed), peak memory usage, leak suspects (unreleased blocks), and an allocation summary grouped by type.

Advanced usage: You can filter and sort the report by size, count, or allocation time to quickly pinpoint issues, and merge reports from multiple processes or threads for a comprehensive view.

Memray is especially useful for deep analysis of Python programs' memory behavior, but it may introduce runtime overhead, so it is best employed during development and debugging rather than in production environments.