Memray

Profile the memory usage of a Python script using memray and visualize a temporal flamegraph in the browser. Use when the user wants to investigate memory consumption, find leaks, or understand allocation patterns.

scverse 94f2fea 1.3 KB Updated

File contents

Steps

  1. Ask the user which script to profile (full or relative path).

  2. Run the script under memray:

    pixi run -e profiling memray-run script.py
    

    This produces a binary file named memray-script.py.<pid>.bin in the current directory.

  3. Generate the flamegraph HTML report from the .bin file:

    pixi run -e profiling memray-flame memray-script.py.<pid>.bin
    

    Replace <pid> with the actual PID shown in the filename. This writes memray-flamegraph-script.py.<pid>.html.

  4. Open the report in the browser:

    • macOS: open memray-flamegraph-script.py.<pid>.html
    • Linux: xdg-open memray-flamegraph-script.py.<pid>.html
    • Either: python -m webbrowser memray-flamegraph-script.py.<pid>.html

Notes

  • The --temporal flag (included in memray-flame) shows memory over time, not just peak — use this to spot leaks and allocation bursts.
  • To find the .bin file if unsure of the name: ls memray-*.bin
  • To compare runs, save the previous report: cp memray-flamegraph-script.py.<pid>.html memray-flamegraph-before.html

scverse/spatialdata/tree/main/.claude/skills/memray commit 94f2feaedc

Frequently asked questions

npx skillmds@latest add scverse/memray