Python is a beautiful language for fast prototyping and and sketching ideas quickly. People often struggle to get their code into production though for various reasons. Besides of all security and safety concerns that usually are not addressed from the very beginning when playing around with an algorithmic idea, performance concerns are quite frequently a reason for not taking the Python code to the next level.
We will look at the "missing performance" worries using a simple numerical problem and how to speed the corresponding Python code up to top notch performance.
Affiliation: ROSEN Creation GmbH
A physicist who has filled a variety of roles in a leading service company in the oil and gas industry, currently tackling the development of embedded devices based on the Raspberry Pi, LinuX and Python with a Python history going back to version 1.4.