The Pythonic Way: An Architect’s Guide to Conventions and Best Practices for the Design,Development,Testing,and Management of Enterprise Python Code


The Pythonic Way: An Architect’s Guide to Conventions and Best Practices for the Design,Development,Testing,and Management of Enterprise Python Code (English Edition)
Author: Sonal Raj
Publisher Finelybook 出版社: BPB Publications (September 9,2021)
Language 语言: English
pages 页数: 512 pages
ISBN-10 书号: 9391030122
ISBN-13 书号: 9789391030124


Book Description
Learn to build and manage better software with clean,intuitive,scalable,maintainable,and high-performance Python code.

Key Features
Comparative analysis of regular and Pythonic coding constructs.
Illustrates application design paradigms for Python projects.
Detailed pointers on optimal data processing and application design.
Highlights accepted conventions for testing and managing production code.
‘The Pythonic Way’ acquaints you with Python’s capabilities beyond basic syntax. This book will help you understand widely accepted Pythonic constructs and procedures,thus enabling you to write reliable,optimized,and modular applications.
You’ll learn about Pythonic data structures,class and object creation,and more. The book then delves into some of Python’s lesser-known but incredibly powerful functionalities such as meta-programming,decorators,context managers,generators,and iterators. Additionally,you’ll learn how to accelerate computations Author: using Pandas Series and Dataframes. You will be introduced to various design patterns that work well with Python applications. Finally,we’ll discuss testing frameworks and best practices for testing,packaging,launching,and publishing applications in production environments.

What you will learn
Understand common practices for writing scalable and legible Python code.
Create robust and maintainable production codebases for time and space performant applications.
Master effective data processing practices and features like generators and decorators to improve complex computations on large datasets.
Get familiar with Pythonic design patterns for secure,large-scale applications.


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