Modern Python Cookbook

<Modern Python Cookbook> ▶Book Description
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 insight 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 comes with over 100 recipes on the latest version of Python. The recipes will benefit everyone ranging from beginner to an expert. The book is broken down into 13 chapters that build from simple language concepts to more complex applications of the language.
The recipes will touch upon all the necessary Python concepts related to data structures, OOP, functional programming, as well as statistical programming. You will get acquainted with the nuances of Python syntax and how to effectively use the advantages that it offers. You will end the book equipped with the knowledge of testing, web services, and configuration and application integration tips and tricks.
The recipes take a problem-solution approach to resolve issues commonly faced by Python programmers across the globe. You will be armed with the knowledge of creating applications with flexible logging, powerful configuration, and 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 code readability through functions in Python
⦁ 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 succinct, expressive programs in Python
⦁ Learn the best practices and common idioms through carefully explained and structured recipes
⦁ Discover new ways to apply Python for the new age of development

▶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 –list, set, dict, will look at an overview of the various structures that are available and what problems they solve. From there, we can look at lists, dictionaries, and sets in detail, and also look at some more advanced topics related to how Python handles references to objects.
⦁ Chapter 5, 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 6, Basics of Classes and Objects, will create classes that implement a number of statistical formulae.
⦁ Chapter 7, 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 8, Functional and Reactive Programming Features, provides us with methods to writing small, expressive functions that perform the required data transformations. Moving ahead, you will learn about the idea of reactive programming, that is, having processing rules that are evaluated when the inputs become available or change.
⦁ Chapter 9, Input/Output, Physical Format, Logical Layout, will work with different file formats such as JSON, XML, and HTML.
⦁ Chapter 10, 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.
⦁ 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, will look at ways that we can design applications that can be composed to create larger, more sophisticated composite applications. We’ll also look at the complications that can arise from composite applications and the need to centralize some features, such as command-line parsing.