Metadata-Version: 2.1
Name: joblib-progress
Version: 1.0.3
Summary: A contextmanager to track progress of joblib execution
Home-page: https://github.com/jonghwanhyeon/joblib-progress
Author: Jonghwan Hyeon
Author-email: jonghwanhyeon93@gmail.com
License: MIT
Keywords: joblib,progress,rich
Classifier: Development Status :: 4 - Beta
Classifier: License :: OSI Approved :: MIT License
Classifier: Programming Language :: Python :: 3
Classifier: Programming Language :: Python :: 3 :: Only
Requires-Python: >=3.7
Description-Content-Type: text/markdown
License-File: LICENSE

# 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-progreess
```

## 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
