Book Image

Expert Python Programming - Fourth Edition

By : Michał Jaworski, Tarek Ziadé
Book Image

Expert Python Programming - Fourth Edition

By: Michał Jaworski, Tarek Ziadé

Overview of this book

This new edition of Expert Python Programming provides you with a thorough understanding of the process of building and maintaining Python apps. Complete with best practices, useful tools, and standards implemented by professional Python developers, this fourth edition has been extensively updated. Throughout this book, you’ll get acquainted with the latest Python improvements, syntax elements, and interesting tools to boost your development efficiency. The initial few chapters will allow experienced programmers coming from different languages to transition to the Python ecosystem. You will explore common software design patterns and various programming methodologies, such as event-driven programming, concurrency, and metaprogramming. You will also go through complex code examples and try to solve meaningful problems by bridging Python with C and C++, writing extensions that benefit from the strengths of multiple languages. Finally, you will understand the complete lifetime of any application after it goes live, including packaging and testing automation. By the end of this book, you will have gained actionable Python programming insights that will help you effectively solve challenging problems.
Table of Contents (16 chapters)
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Code profiling

Knowing what can potentially go wrong allows you to make hypotheses and bets on what are the performance issue culprits and how can you fix them. But profiling is the only way to verify these hypotheses. You should usually avoid optimization attempts without profiling your application first.

Experience helps, so there is of course nothing wrong with doing a small code overview and experiments before profiling. Also, some profiling techniques require the incorporation of additional code instrumentation or the writing of performance tests. It means that often you will have to read it thoroughly anyway. If you perform some small experiments along the way (for instance, in the form of debugging sessions), you may spot something obvious.

Low-hanging fruit happens, but don't rely on it. A good ratio between freeform experiments and classic profiling is around 1:9. My favorite way of organizing the profiling and optimization process is as follows:

  1. Decide...