ipython-memory-magics 0.3.7

IPython magic commands for tracking memory usage

IPython memory magic commands

Simple tool to trace memory usage of a Python statement or expression execution.

Memory equivalent of IPython built-in time magics.

Existing tools like memory-profiler or ipython-memory-usage mainly use psutil package to measure memory usage, which may give inaccurate results. This package uses tracemalloc module to trace Python memory allocations. Memory-profiler provides tracemalloc backend, but it does not allow to use it for magic commands. This packages offers line %memory and cell %%memory magic commands, which were intended to complement the %time and %%time magic commands.

Installation

Install from pip:

pip install ipython-memory-magics

Or install directly from github:

pip install git+https://github.com/rusmux/ipython-memory-magics.git

After the installation load the extension via:

%load_ext memory_magics

To activate it whenever you start IPython, edit the configuration file for your IPython profile ~/.ipython/profile_default/ipython_config.py. Register the extension like this:

c.InteractiveShellApp.extensions = [
    'memory_magics',
]

If the file does not already exist, run ipython profile create in a terminal.

Usage

Use %memory [options] statement to measure statement's memory consumption:

%memory -q list(range(10**6))

The output in the format current / peak will follow:

RAM usage: line: 34.33 MiB / 34.33 MiB

Here -q is the quiet flag set to suppress the output. You can use other options to get data on the notebook and jupyter memory usage, or to print the statistics in a table. For example, you can use -n or --notebook flag to get the information about the notebook current memory consumption:

%memory -n

RAM usage: notebook: 101.41 MiB

In the same way, -j or --jupyter flag will give you the information about the total Jupyter memory usage.

Put %%memory [options] on top of a cell to measure its memory consumption:

In [1]: %%memory -n -j -t
        sum(list(range(10**6)))

This will print:

RAM usage |   current   |     peak     |
----------------------------------------
 cell     | 2.62 KiB    | 34.33 MiB    |
 notebook | 123.08 MiB  | 155.53 MiB   |
 jupyter  | 170.19 MiB  | 202.55 MiB   |

Out [1]: 499999500000

Options

Five options are available in full and short versions:

-n <notebook>: If present, show current notebook memory usage

-j <jupyter>: If present, show current jupyter memory usage

-i <interval>: Interval in milliseconds for updating memory usage information

-t <table>: If present, print statistics in a table

-q <quiet>: If present, do not return the output