# joblib-progress
A contextmanager to track progress of [`joblib`](https://joblib.readthedocs.io) execution using [`rich.progress`](https://rich.readthedocs.io).
[](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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