/usr/share/apache-beam/bin/memray3.11

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

positional arguments:
  {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

options:
  -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