Arrays in Python give you a huge amount of flexibility for storing, organizing, and accessing data. This is crucial, not least because of Python’s popularity for use in data science. But what ...

Tired of out-of-memory errors derailing your data analysis? There's a better way to handle huge arrays in Python.

NumPy is known for being fast, but could it go even faster? Here’s how to use Cython to accelerate array iterations in NumPy. NumPy gives Python users a wickedly fast library for working with data in ...

But in many cases, it doesn’t have to be an either/or proposition. Properly optimized, Python applications can run with surprising speed—perhaps not as fast as Java or C, but fast enough for web ...