memprofiler 0.1.9

A simple IPython extension for monitoring memory usage of Jupyter notebook cells.

memprofiler

memprofiler is a simple extension for monitoring memory usage of Jupyter notebook cells.

Installation

It can be installed as a typical Python source package from PyPi using pip:

pip install memprofiler

Usage

A basic example of how to use this extension can be found in this interactive Jupyter notebook.

Reference

mprof_run

%mprof_run [-q] [-i INTERVAL] [-p] [profile_id]

Run memory profiler during cell execution. (cell_magic)

• positional arguments:

  • profile_id
    Profile label. You can specify up to two keywords by separating them with :: (keyword0::keyword1). Only profile_ids with two keywords can be used in plot-related functions.

• optional arguments:

  • -q, --quiet
    Suppress verbosity.

  • -i INTERVAL, --interval INTERVAL
    Sampling period (in seconds), default 0.01.

  • -p, --plot
    Plot the memory profile.

mprof_plot

%mprof_plot [-t TITLE] [--groupby {0,1}] profile_ids [profile_ids ...]

Plot detailed memory profiler results. (line_magic)

• positional arguments:

  • profile_ids
    Profile identifiers made by mprof_run. Supports regex.

• optional arguments:

  • -t TITLE, --title TITLE
    String shown as plot title.

  • --groupby <{0,1}>
    Identifier number used to group the results, default 1.

mprof_barplot

%mprof_barplot [-t TITLE] [--variable {time,memory}] [--barmode {group,stack}] [--groupby {0,1}] profile_ids [profile_ids ...]

Plot only-memory or only-time results in a bar chart. (line_magic)

• positional arguments:

  • profile_ids
    Profile labels made by mprof_run. Supports regex.

• optional arguments:

  • -t TITLE, --title TITLE
    String shown as plot title.

  • --variable <{time,memory}>
    Variable to plot, default 'memory'.

  • --barmode <{group,stack}>
    Bar char mode, default 'group'.

  • --groupby <{0,1}>
    Identifier number used to group the results, default 1.

Contributing

Contributions are what make the open source community such an amazing place to be learn, inspire, and create. Any contributions you make are greatly appreciated!

1. Fork the Project
2. Create your Feature Branch (git checkout -b feature/AmazingFeature)
3. Commit your Changes (git commit -m 'Add some AmazingFeature')
4. Push to the Branch (git push origin feature/AmazingFeature)
5. Open a Pull Request

License

Distributed under the BSD 3-Clause License. See LICENSE for more information.

Acknowledgements

• @FrancescAlted