How can I use NumPy for parallel computing?

How can I use NumPy for parallel computing?

You can use NumPy with libraries like Dask or Joblib to perform parallel computing. Would you like to see an example?

Yes, please provide an example using Dask.

Sure! First, install Dask using pip install dask. Then, you can use it like this:

import dask.array as da

# Create a large random array
x = da.random.random((10000, 10000), chunks=(1000, 1000))

# Perform a computation in parallel
result = (x + x.T).compute()

This will compute the sum of the array and its transpose in parallel.

What are the benefits of using Dask with NumPy?

Dask allows you to work with larger-than-memory datasets, parallelizes computations across multiple cores, and integrates seamlessly with NumPy, making it efficient for large-scale data processing.