joblib-progress

Name	joblib-progress JSON
Version	1.0.5 JSON
	download
home_page	https://github.com/jonghwanhyeon/joblib-progress
Summary	A contextmanager to track progress of joblib execution
upload_time	2024-02-18 07:42:27
maintainer
docs_url	None
author	Jonghwan Hyeon
requires_python	>=3.7
license	MIT
keywords	joblib progress rich
VCS
bugtrack_url
requirements	No requirements were recorded.
Travis-CI	No Travis.
coveralls test coverage	No coveralls.

            # joblib-progress
A contextmanager to track progress of [`joblib`](https://joblib.readthedocs.io) execution using [`rich.progress`](https://rich.readthedocs.io).
[![joblib-progress](https://asciinema.org/a/Ufe9v8MKfxIzMuvlv2IwCk29l.svg)](https://asciinema.org/a/Ufe9v8MKfxIzMuvlv2IwCk29l)

## Why
The vanilla `multiprocessing` does not work when an object to multiprocess is not `pickle-able`. The `joblib` solves this, but then its progress is not tracked nicely. This library solves that tracking issue with `joblib`.

## Install
```bash
> pip install joblib-progress
```

## Usage
### If you know the number of items
```python
import time

from joblib import Parallel, delayed
from joblib_progress import joblib_progress


def slow_square(i):
    time.sleep(i / 2)
    return i ** 2

with joblib_progress("Calculating square...", total=10):
    Parallel(n_jobs=4)(delayed(slow_square)(number) for number in range(10))
```

### If you don't know the number of items
```python
with joblib_progress("Calculating square..."):
    Parallel(n_jobs=4)(delayed(slow_square)(number) for number in range(10))
```

# Acknowledgments
The idea of using `joblib.parallel.BatchCompletionCallBack` is referenced from https://stackoverflow.com/a/58936697/5133167

            

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