Parallel Processing with joblib

Speed up computationally intensive tasks by distributing work across multiple CPU cores.

Basic Usage

from joblib import Parallel, delayed

def process_item(x):
    """Process a single item."""
    return x ** 2

# Sequential
results = [process_item(x) for x in range(100)]