Python has grown in both significance and popularity in the last years, especially in the field of high performance computing and machine learning. When it comes to performance, there are numerous ways of profiling and measuring code performance—with each analysis tool having its own strengths and weaknesses. In this talk, we will introduce a rich GUI application (Intel® VTune™ Amplifier) which can be used to analyze the runtime performance of one’s Python application, and fully understand where the performance bottlenecks are in one’s code. With this application, one may also analyze the call-stacks and get quick visual clues where one’s Python application is spending time or wasting CPU cycles.