Go ahead and run this script from your command line: Shell $ python efficiency_v1.py Execution time: 1.83 seconds The execution time is almost two seconds. Now consider the improved implementation below. ✅ Higher-quality code: Python efficiency_v2.py from time import perf_counter cache...
bonus Timing and profiling code In this chapter, you will learn how to gather and compare runtimes between different coding approaches. You'll practice using the line_profiler and memory_profiler packages to profile your code base and spot bottlenecks. Then, you'll put your learnings to practice...
The --name and --hostname parameters are optional but will allow you to find your container more easily using Docker’s command-line interface. Note: Don’t worry if you accidentally close your container, for example, by pressing Ctrl+D or typing the exit command. You can resume the ...
NOTE: one small defect is the diagonal line, that corresponds to a moment when the printing head travelled across the layer while not printing, but somehow still leaved a trail of PLA despite the “retraction” option in Cura. I will have to investigate how to fix this. + + And another...
Timing and Profiling Tools Configuration and Command -Line Interfaces Interactive Development Environments Conclusion and Community Tips 1. Start With Structure: Formatters and Linters (Not the kind on your shirt) The first step to better Python code is simple: make it readable. Formatters enforce co...
You can comfortably work with your IDE (such as Spyder or Visual Studio Code) or run Python on the command line. You are eager to learn the tips and tricks of Python as a tool for your project.This guide was written in the top-down and results-first style that you’re used to from...
11. Pandas Profiling for Quick Data Exploration Exploring datasets can be time-consuming, butpandas_profilingmakes it a breeze, as this library generates a detailed report with statistics, visualizations, and insights about your dataset in just one line of code: ...
You can comfortably work with your IDE (such as Spyder or Visual Studio Code) or run Python on the command line. You are eager to learn the tips and tricks of Python as a tool for your project.This guide was written in the top-down and results-first style that you’re used to from...
Chapter 12,Performance Tuning, Profiling, and Concurrency, gives hints on improving performance with profiling and Cythoning as key techniques. Relevant frameworks for multicore and distributed systems are also discussed. Appendix A,Key Concepts, gives key terms and their description. ...
In addition, Python and its environment are open-source and free of charge. An optimization should be applied through the following steps; however, they tend to be neglected, so we should keep them in mind [175]. 1. Profiling what occurs in the code, 2. Improve the slow parts of a ...