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https://github.com/rusmux/ipython-memory-magics
IPython magic commands for tracking memory usage
https://github.com/rusmux/ipython-memory-magics
ipython-magic jupyter-notebook memory-profiler
Last synced: 19 days ago
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IPython magic commands for tracking memory usage
- Host: GitHub
- URL: https://github.com/rusmux/ipython-memory-magics
- Owner: rusmux
- License: mit
- Created: 2022-10-22T21:22:42.000Z (about 2 years ago)
- Default Branch: main
- Last Pushed: 2024-08-05T23:04:25.000Z (3 months ago)
- Last Synced: 2024-10-07T06:55:08.934Z (about 1 month ago)
- Topics: ipython-magic, jupyter-notebook, memory-profiler
- Language: Python
- Homepage: https://pypi.org/project/ipython-memory-magics
- Size: 67.4 KB
- Stars: 2
- Watchers: 1
- Forks: 0
- Open Issues: 2
-
Metadata Files:
- Readme: README.md
- License: LICENSE
Awesome Lists containing this project
README
# IPython memory magic commands
[](https://pypi.org/project/ipython-memory-magics/)
[](https://codecov.io/gh/rusmux/ipython-memory-magics)
[](https://wemake-python-styleguide.readthedocs.io/en/latest/)
[](https://github.com/pre-commit/pre-commit)
[](https://results.pre-commit.ci/latest/github/rusmux/ipython-memory-magics/main)
Simple tool to trace memory usage of a Python statement or expression execution.
Memory equivalent of IPython
built-in [time magics](https://github.com/ipython/ipython/blob/66aeb3fc55c8ac04242e566172af5de5cc6fe71e/IPython/core/magics/execution.py#L1193).
Existing tools like [memory-profiler](https://github.com/pythonprofilers/memory_profiler)
or [ipython-memory-usage](https://github.com/ianozsvald/ipython_memory_usage) mainly use psutil package to measure
memory usage, which may give inaccurate results. This package
uses [tracemalloc](https://docs.python.org/3/library/tracemalloc.html) 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:
```python
%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:
```python
%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:
```python
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 `: If present, show current notebook memory usage
`-j `: If present, show current jupyter memory usage
`-i `: Interval in milliseconds for updating memory usage information
`-t `: If present, print statistics in a table
`-q `: If present, do not return the output