Modern Python Cookbook Second Edition

133 recipes to develop flawless and expressive programs in Python 3.8

Steven F. Lott 지음

Packt(GCO Science) 2020년 07월 31일 출간

작품소개

책소개

Complete recipes spread across 15 chapters to help you overcome commonly faced issues by Python for everybody across the globe. Each recipe takes a problem-solution approach to resolve for effective Python.

▶Book Description
Python is the preferred choice of developers, engineers, data scientists, and hobbyists everywhere. It is a great language that can power your applications and provide great speed, safety, and scalability. It can be used for simple scripting or sophisticated web applications. By exposing Python as a series of simple recipes, this book gives you insight into specific language features in a particular context. Having a tangible context helps make the language or a given standard library feature easier to understand.

This book comes with 133 recipes on the latest version of Python 3.8. The recipes will benefit everyone, from beginners just starting out with Python to experts. You'll not only learn Python programming concepts but also how to build complex applications.

The recipes will touch upon all necessary Python concepts related to data structures, object oriented programming, functional programming, and statistical programming. You will get acquainted with the nuances of Python syntax and how to effectively take advantage of it.

By the end of this Python book, you will be equipped with knowledge of testing, web services, configuration, and application integration tips and tricks. You will be armed with the knowledge of how to create applications with flexible logging, powerful configuration, command-line options, automated unit tests, and good documentation.

▶What You Will Learn
？See the intricate details of the Python syntax and how to use it to your advantage
？Improve your coding with Python readability through functions
？Manipulate data effectively using built-in data structures
？Get acquainted with advanced programming techniques in Python
？Equip yourself with functional and statistical programming features
？Write proper tests to be sure a program works as advertised
？Integrate application software using Python

▶Key Features
？Develop expressive and effective Python programs
？Best practices and common idioms through carefully explained recipes
？Discover new ways to apply Python for data-focused development
？Make use of Python's optional type annotations

▶Who This Book Is For
The Python book is for web developers, programmers, enterprise programmers, engineers, and big data scientists. If you are a beginner, this book will get you started. If you are experienced, it will expand your knowledge base. A basic knowledge of programming would help.

목차

▶TABLE of CONTENTS
？Chapter 1. Numbers, Strings, and Tuples
？Chapter 2. Statements and Syntax
？Chapter 3. Function Definitions
？Chapter 4. Built-In Data Structures Part 1: Lists and Sets
？Chapter 5. Built-In Data Structures Part 2: Dictionaries
？Chapter 6. User Inputs and Outputs
？Chapter 7. Basics of Classes and Objects
？Chapter 8. More Advanced Class Design
？Chapter 9. Functional Programming Features
？Chapter 10. Input/Output, Physical Format, and Logical Layout
？Chapter 11. Testing
？Chapter 12. Web Services
？Chapter 13. Application Integration: Configuration
？Chapter 14. Application Integration: Combination
？Chapter 15. Statistical Programming and Linear Regression

책 속으로

▶What this book covers
？ Chapter 1, Numbers, Strings, and Tuples, will look at the different kinds of numbers, work with strings, use tuples, and use the essential built-in types in Python. We will also exploit the full power of the unicode character set.

？ Chapter 2, Statements and Syntax, will cover some basics of creating script files first. Then we'll move on to looking at some of the complex statements, including if, while, for, try, with, and raise.

？ Chapter 3, Function Definitions, will look at a number of function definition techniques. We'll also look at the Python 3.5 typing module and see how we can create more formal annotations for our functions.

？ Chapter 4, Built-In Data Structures Part 1 ？ Lists and Sets, will look at an overview of the various structures that are available and what problems they solve. From there, we can look at lists and sets in detail.

？ Chapter 5, Built-In Data Structures Part 2 ？ Dictionaries, will continue examining the builtin data structures, looking at dictionaries in detail. This chapter will also look at some more advanced topics related to how Python handles references to objects.

？ Chapter 6, User Inputs and Outputs, will explain how to use the different features of the print() function. We'll also look at the different functions used to provide user input.

？ Chapter 7, Basics of Classes and Objects, will create classes that implement a number of statistical formulae.

？ Chapter 8, More Advanced Class Design, will dive a little more deeply into Python classes. We will combine some features we have previously learned about to create more sophisticated objects.

？ Chapter 9, Functional Programming Features, will examine ways Python can be used for functional programming. This will emphasize function definitions and stateless, immutable objects.

？ Chapter 10, Input/Output, Physical Format, and Logical Layout, will work with different file formats such as JSON, XML, and HTML.

？ Chapter 11, Testing, will give us a detailed description of the different testing frameworks used in Python.

？ Chapter 12, Web Services, will look at a number of recipes for creating RESTful web services and also serving static or dynamic content.

？ Chapter 13, Application Integration: Configuration, will start looking at ways that we can design applications that can be composed to create larger, more sophisticated composite applications.

？ Chapter 14, Application Integration: Combination, will look at ways that complications that can arise from composite applications and the need to centralize some features, such as command-line parsing.

？ Chapter 15, Statistical Programming and Linear Regression, will look at some basic statistical calculations that we can do with Python's built-in libraries and data structures. We'll look at the questions of correlation, randomness, and the null hypothesis.

출판사 서평

▶ Preface
Python is the preferred choice of developers, engineers, data scientists, and hobbyists everywhere. It is a great scripting language that can power your applications and provide great speed, safety, and scalability. By exposing Python as a series of simple recipes, you can gain insights into specific language features in a particular context. Having a tangible context helps make the language or standard library feature easier to understand.

This book takes a recipe-based approach, where each recipe addresses specific problems and issues.

▷ What you need for this book

All you need to follow through the examples in this book is a computer running any Python 3.8.5 or newer. Some of the examples can be adapted to work with Python 3 versions prior to 3.8. A number of examples are specific to Python 3.8 features.

It's often easiest to install a fresh copy of Python. This can be downloaded from https:// www.python.org/downloads/. An alternative is to start with Miniconda (https:// docs.conda.io/en/latest/miniconda.html) and use the conda tool to create a Python 3.8 (or newer) environment.

Python 2 cannot easily be used any more. Some Linux distributions and older macOS releases included a version of Python 2. It should be thought of as part of the operating system, and not a general software development tool.

작가정보

저자(글) Steven F. Lott

Steven F. Lott has been programming since the 70s, when computers were large, expensive, and rare. As a contract software developer and architect, he has worked on hundreds of projects, from very small to very large. He's been using Python to solve business problems for almost 20 years.He's currently leveraging Python to implement cloud management tools. His other titles with Packt Publishing include Python Essentials, Mastering Object-Oriented Python, Functional Python Programming, and Python for Secret Agents.Steven is currently a technomad who lives in various places on the east coast of the U.S.