This repository keeps some utilities and testing scripts to measure and display(visualize) the performance of Python operations in concurrent and distributed scenarios (e.g. multithreading vs. multiprocessing) in CPU intensive scenarios.

Script to measure the performance differences in executing CPU intensive tasks (thread- vs. process-pools) due to the well known cPython GIL issue.

Measuring the performance in distributed scenarios by having a control-node and many worker nodes.

In this example the controller is not able to distribute tasks and collect results in the same time. This can for example be solved by initiating two sockets (send, receive) in two threads and for example having them talk via a threadsafe implementation of a queue.

Based on Python 3.4/3.5 coroutines the publisher is implemented in a non-blocking way.