That is how to effectively create arrays in Python. However, there are other options for arrays too. One example is to create a CSV file, which you can learn to do in our quick guide .

It is possible to use generic Python objects as the dtype for a NumPy array, but if you do this, you’ll get no better performance with NumPy than you would with Python generally.

The best parallel processing libraries for Python. Ray: Parallelizes and distributes AI and machine learning workloads across CPUs, machines, and GPUs.; Dask: Parallelizes Python data science ...