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.

All you need to follow through the examples in this book is a computer running any recent version of Python. While the examples all use Python 3, they can be adapted to work with Python 2 only a few changes.

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

In this book, you will find a number of text styles that distinguish between different kinds of information. Here are some examples of these styles and an explanation of their meaning.

Code words in text, database table names, folder names, filenames, file extensions, pathnames, dummy URLs, user input, and Twitter handles are shown as follows: "We can include other contexts through the use of the include directive."

A block of code is set as follows:

    if distance is None:
        distance = rate * time
    elif rate is None:
        rate = distance / time
    elif time is None:
        time = distance / rate

Any command-line input or output is written as follows:

>>> circumference_diameter_ratio = 355/113
>>> target_color_name = 'FireBrick'
>>> target_color_rgb = (178, 34, 34)

New terms and important words are shown in bold.

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