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Learning Python Application Development

Learning Python Application Development

By : Ninad Sathaye
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Learning Python Application Development

Learning Python Application Development

5 (2)
By: Ninad Sathaye

Overview of this book

Python is one of the most widely used dynamic programming languages, supported by a rich set of libraries and frameworks that enable rapid development. But fast paced development often comes with its own baggage that could bring down the quality, performance, and extensibility of an application. This book will show you ways to handle such problems and write better Python applications. From the basics of simple command-line applications, develop your skills all the way to designing efficient and advanced Python apps. Guided by a light-hearted fantasy learning theme, overcome the real-world problems of complex Python development with practical solutions. Beginning with a focus on robustness, packaging, and releasing application code, you’ll move on to focus on improving application lifetime by making code extensible, reusable, and readable. Get to grips with Python refactoring, design patterns and best practices. Techniques to identify the bottlenecks and improve performance are covered in a series of chapters devoted to performance, before closing with a look at developing Python GUIs.
Table of Contents (12 chapters)
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11
Index

Further reading


In the series of the three chapters on performance, we covered several important aspects. The things learned here will help you with the majority of common application performance enhancement tasks. Where do we go from here? There are some other important topics that you can explore, among those are JIT compilers and Graphics Processing Unit (GPU) programming. This section aims at providing some basic information on these two topics. You can follow the links provided here for further understanding.

JIT compilers

Python is an interpreted language. In simple terms, it means that the code is parsed and executed directly without involving any code compilation. Although this offers a great deal of flexibility, the program typically runs slower.

In high-level programming languages such as C++, the code is compiled ahead of time or before the execution. Generally speaking, a compiled program (C++) runs faster compared to the equivalent interpreted program (Python).

Thus, we have an...

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Learning Python Application Development
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