Chapter 1, Getting Started, addresses installing or upgrading Python. We explore Python's Read-Evaluate-Print Loop (REPL) as a way to interact with the language. We'll use this interactive Python mode as a way to explore most of the language features.

Chapter 2, Simple Data Types, introduces a few features concerning numbers and some simple collections. We'll look at Python's Unicode strings as well as byte strings, including some of the conversions between strings and numbers.

Chapter 3, Expressions and Output, provides more details on Python expression syntax and how the various numeric types relate to each other. We'll look at the coercion rules and the numeric tower. We'll look at the print() function, which is a common tool for looking at output.

Chapter 4, Variables, Assignment and Scoping Rules, shows how we assign names to objects. We look at a number of different assignment statements available in Python. We also explore the input() function, which parallels the print() function.

Chapter 5, Logic, Comparisons, and Conditions, shows the logical operators and literals that Python uses. We'll look at the comparison operators and how we use them. We'll look closely at the if statement.

Chapter 6, More Complex Data Types, shows the core features of the list, set, and dict built-in types. We use the for statement to work with these collections. We also use functions such as sum(), map(), and filter().

Chapter 7, Basic Function Definitions, introduces the syntax for the def statement as well as the return statement. Python offers a wide variety of ways to provide argument values to functions; we show a few of the alternatives.

Chapter 8, More Advanced Functions, extends the basic function definitions to include the yield statement. This allows us to write generator functions that will iterate over a sequence of data values. We look at a few functional programming features available via built-in functions as well as the modules in the Python Standard Library.

Chapter 9, Exceptions, shows how we handle and raise exceptions. This allows us to write programs which are considerably more flexible. A simple "happy path" can handle the bulk of the processing, and exception clauses can handle rare or unexpected alternative paths.

Chapter 10, Files, Databases, Networks, and Contexts, will introduce a number of features related to persistent storage. We'll look at Python's use of files and file-like objects. We'll also extend the concept of persistence to include some database features available in the Python Standard Library. This chapter will also include a review of the with statement for context management.

Chapter 11, Class Definitions, demonstrates the class statement and the essentials of object-oriented programming. We look at the basics of inheritance and how to define class-level (static) methods.

Chapter 12, Scripts, Modules, Packages, Libraries, and Applications, shows different ways in which we can create Python code files. We'll look at the formal structures of script, module, and package. We'll also look at informal concepts such as application, library, and framework.

Chapter 13, Metaprogramming and Decorators, introduces two concepts that can help us write Python code that manipulates Python code. Python makes metaprogramming relatively simple; we can leverage this to simplify certain types of programming where a common aspect doesn't fit neatly into a class hierarchy or library of functions.

Chapter 14, Fit and Finish – Unit Testing, Packaging, and Documentation, moves beyond the Python language into the idea of creating a complete, polished product. Any well-written program should include test cases and documentation. We show common ways to make sure this is done properly.

Chapter 15, Next Steps, will demonstrate four simple kinds of applications. We'll look at the command-line interface (CLI), graphic user interface (GUI), simple Web frameworks, as well as MapReduce applications.

We're going to focus on Python 3, exclusively. Many computers will have Python 2 already installed, which means an upgrade is required. Some computers don't have Python installed at all, which means that a fresh installation of Python 3 will be necessary. The details are the subject of Chapter 1, Getting Started.

It's important to note that Python 2 can't easily be used to run all of the examples. Python 2 may work for many of the examples, but it's not our focus.

In order to install software, you'll generally need administrative rights on the computer you intend to use. For a home computer, this is generally true. For computers supplied through work or school, administrative passwords may be required.

You may also want to have a proper programmer's text editor. Default text editing applications such as Windows Notepad or Mac OS X TextEdit can be used, but aren't ideal. There are numerous free text editors available: feel free to download several to locate the one that feels most comfortable for you.

This book is for programmers who want to learn Python quickly. It shows key features of Python, assuming a background in programming. The focus is on essential features: the approach is broad but relatively shallow. We'll provide pointers and direction for additional study and research, assuming that the reader is willing and able to follow those pointers.

In many data-intensive industries, a great deal of big data analysis is done with Python and toolsets such as Apache Hadoop. In this case, the users of Python will be statisticians, data scientists, or analysts. Their interest isn't in Python itself, but in using Python to process collections of data. This book is designed to provide language fundamentals for data scientists.

This book can be used by students who are learning Python. Since this book doesn't cover the computer science foundations of programming, an additional text would be helpful.

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've built an ArgumentParser method using all of the default parameters."

A block of code is set as follows:

def prod(sequence):
    p= 1
    for item in sequence:
        p *= item
    return p

When we wish to draw your attention to a particular part of a code block, the relevant lines or items are set in bold:

def prod(sequence):
    p= 1
    for item in sequence:
        p *= item
    return

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

MacBookPro-SLott:Code slott$ python3 -m test_all

New terms and important words are shown in bold. Words that you see on the screen, for example, in menus or dialog boxes, appear in the text like this: "Clicking on Continue will step through the Read Me, License, Destination Select, and Installation Type windows."

Feedback from our readers is always welcome. Let us know what you think about this book—what you liked or disliked. Reader feedback is important for us as it helps us develop titles that you will really get the most out of.

To send us general feedback, simply e-mail <[email protected]>, and mention the book's title in the subject of your message.

If there is a topic that you have expertise in and you are interested in either writing or contributing to a book, see our author guide at www.packtpub.com/authors.

Now that you are the proud owner of a Packt book, we have a number of things to help you to get the most from your purchase.