This is a cross listed blog post. I had posted this blog on my company’s blog and wanted to repost here as it is a topic that very few python developers understand. Python has a high memory footprint, understanding that is the key to writing very space efficient python programs.
Note there will be a follow up to this blog post to discuss memory footprint of data structures used by numpy. Numpy has its own set of data structures that can be more efficient depending on the use case. When it comes to scientific computation (matrices, numerical methods, …) and hence Machine Learning (NLP, AI, …) can be much more efficient.