memray - Memory profiler for Python applications
usage: memray [-h] [-v] [-V]
- {run,flamegraph,table,live,tree,parse,summary,stats,transform,attach,detach}
...
Memory profiler for Python applications
Run `memray run` to generate a memory profile report, then use a
reporter command such as `memray flamegraph` or `memray table` to convert
the results into HTML.
Example:
- $ python3 -m memray run -o output.bin my_script.py
$ python3 -m memray flamegraph output.bin
- {run,flamegraph,table,live,tree,parse,summary,stats,transform,attach,detach}
- Mode of operation
- run
- Run the specified application and track memory usage
- flamegraph
- Generate an HTML flame graph for peak memory usage
- table
- Generate an HTML table with all records in the peak memory usage
- live
- Remotely monitor allocations in a text-based interface
- tree
- Generate a tree view in the terminal for peak memory usage
- parse
- Debug a results file by parsing and printing each record in it
- summary
- Generate a terminal-based summary report of the functions that allocate
most memory
- stats
- Generate high level stats of the memory usage in the terminal
- transform
- Generate reports files in different formats
- attach
- Begin tracking allocations in an already-started process
- detach
- End the tracking started by a previous ``memray attach`` call
- -h, --help
- show this help message and exit
- -v, --verbose
- Increase verbosity. Option is additive and can be specified up to 3
times
- -V, --version
- Displays the current version of Memray
Please submit feedback, ideas, and bug reports by filing a new
issue at https://github.com/bloomberg/memray/issues
The full documentation for memray is maintained as a
Texinfo manual. If the info and memray programs are properly
installed at your site, the command
- info memray
should give you access to the complete manual.