Parallel Processing in Python

Speed up data processing by parallelizing tasks using concurrent.futures:

python
from concurrent.futures import ProcessPoolExecutor
 
def square(x):
    return x * x
 
with ProcessPoolExecutor() as executor:
    results = list(executor.map(square, range(10)))
 
print(results)

This will calculate the square of numbers in parallel, speeding up the process for larger datasets.