Book Image

Python Fundamentals

By : Ryan Marvin, Mark Nganga, Amos Omondi
Book Image

Python Fundamentals

By: Ryan Marvin, Mark Nganga, Amos Omondi

Overview of this book

After a brief history of Python and key differences between Python 2 and Python 3, you'll understand how Python has been used in applications such as YouTube and Google App Engine. As you work with the language, you'll learn about control statements, delve into controlling program flow and gradually work on more structured programs via functions. As you settle into the Python ecosystem, you'll learn about data structures and study ways to correctly store and represent information. By working through specific examples, you'll learn how Python implements object-oriented programming (OOP) concepts of abstraction, encapsulation of data, inheritance, and polymorphism. You'll be given an overview of how imports, modules, and packages work in Python, how you can handle errors to prevent apps from crashing, as well as file manipulation. By the end of this book, you'll have built up an impressive portfolio of projects and armed yourself with the skills you need to tackle Python projects in the real world.

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Table of Contents (12 chapters)
Python Fundamentals
Python Fundamentals
Preface
Preface
Free Chapter
1
Introducing Python
Introducing Python
Introduction
Working with the Python Interactive Shell
Writing and Running Simple Scripts
Python Syntax
Variables
User Input, Comments, and Indentations
Summary
2
Data Types
Data Types
Introduction
Numerical Data
Strings
Lists
Booleans
Summary
3
Control Statements
Control Statements
Introduction
Control Statements
The if Statement
The while Statement
while Versus if
Loops
The for Loop
The range Function
Nesting Loops
Breaking Out of Loops
Summary
4
Functions
Functions
Introduction
Built-In Functions
User-Defined Functions
Function Arguments
Anonymous Functions
Summary
5
Lists and Tuples
Lists and Tuples
Introduction
List Syntax
List Methods
List Comprehensions
Tuple Syntax
Accessing Tuple Elements
Accessing Tuple Elements
Tuple Methods
Summary
6
Dictionaries and Sets
Dictionaries and Sets
Introduction
Working with Dictionaries
Additional Dictionary Attributes
Ordered Dictionaries
The Basics of Sets
Set Operations
Frozen Sets
Summary
7
Object-Oriented Programming
Object-Oriented Programming
Introduction
A First Look at OOP
OOP in Python
Methods in a Class
Class Versus Instance Attributes
Class Versus Instance Methods
Class Inheritance
Multiple Inheritance
Summary
8
Modules, Packages, and File Operations
Modules, Packages, and File Operations
Introduction
Defining Modules
Imports and Import Statements
Modules and Packages
File Operations
The file Object
Reading and Writing to Files
Handling Structured Data
Summary
9
Error Handling
Error Handling
Introduction
Built-In Exceptions
Handling Errors and Exceptions
Custom Exceptions
Summary
Appendix A
Appendix A
Chapter 1: Introducing Python
Chapter 2: Data Types
Chapter 3: Control Statements
Chapter 4: Functions
Chapter 5: Lists and Tuples
Chapter 6: Dictionaries and Sets
Chapter 7: Object-Oriented Programming
Chapter 8: Modules, Packages, and File Operations
Chapter 9: Error Handling

Handling Errors and Exceptions

Handling errors and exceptions starts long before you get to running your code. Right from the planning phase, you should have contingencies in place to avoid running into errors, especially logical errors that may be harder to catch in some cases.

Practices such as defensive programming can help mitigate future errors in some cases.

According to Wikipedia:

"Defensive programming is a form of defensive design intended to ensure the continuing function of a piece of software under unforeseen circumstances. Defensive programming practices are often used where high availability, safety, or security is needed."

Defensive programming is an approach that's used to improve software and source code, in terms of the following:

  • General quality—by reducing the number of software bugs and problems.

  • Making the source code comprehensible—the source code should be readable and understandable, so that it is approved in a code audit.

  • Making the software behave in a predictable manner...

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