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Learn Python Programming - Third Edition

By : Fabrizio Romano, Heinrich Kruger

4.2 (35)

Learn Python Programming

4.2 (35)

By: Fabrizio Romano, Heinrich Kruger

Overview of this book

Learn Python Programming, Third Edition is both a theoretical and practical introduction to Python, an extremely flexible and powerful programming language that can be applied to many disciplines. This book will make learning Python easy and give you a thorough understanding of the language. You'll learn how to write programs, build modern APIs, and work with data by using renowned Python data science libraries. This revised edition covers the latest updates on API management, packaging applications, and testing. There is also broader coverage of context managers and an updated data science chapter. The book empowers you to take ownership of writing your software and become independent in fetching the resources you need. You will have a clear idea of where to go and how to build on what you have learned from the book. Through examples, the book explores a wide range of applications and concludes by building real-world Python projects based on the concepts you have learned.

Preface

Preface

Who this book is for

What this book covers

To get the most out of this book

Get in touch

A Gentle Introduction to Python

A Gentle Introduction to Python

A proper introduction

Enter the Python

About Python

What are the drawbacks?

Who is using Python today?

Setting up the environment

Installing Python

How to run a Python program

How is Python code organized?

Python's execution model

Guidelines for writing good code

Python culture

A note on IDEs

Summary

Free Chapter

Built-In Data Types

Built-In Data Types

Everything is an object

Mutable or immutable? That is the question

Numbers

Immutable sequences

Mutable sequences

Set types

Mapping types: dictionaries

Data types

Final considerations

Summary

Conditionals and Iteration

Conditionals and Iteration

Conditional programming

Looping

Assignment expressions

Putting all this together

A quick peek at the itertools module

Summary

Functions, the Building Blocks of Code

Functions, the Building Blocks of Code

Why use functions?

Scopes and name resolution

Input parameters

Return values

A few useful tips

Recursive functions

Anonymous functions

Function attributes

Built-in functions

Documenting your code

Importing objects

One final example

Summary

Comprehensions and Generators

Comprehensions and Generators

The map, zip, and filter functions

Comprehensions

Generators

Some performance considerations

Don't overdo comprehensions and generators

Name localization

Generation behavior in built-ins

One last example

Summary

OOP, Decorators, and Iterators

OOP, Decorators, and Iterators

Decorators

Object-oriented programming (OOP)

Writing a custom iterator

Summary

Exceptions and Context Managers

Exceptions and Context Managers

Exceptions

Context managers

Summary

Files and Data Persistence

Files and Data Persistence

Working with files and directories

Data interchange formats

I/O, streams, and requests

Persisting data on disk

Summary

Cryptography and Tokens

Cryptography and Tokens

The need for cryptography

Hashlib

HMAC

Secrets

JSON Web Tokens

Useful references

Summary

Testing

Testing

Testing your application

Test-driven development

Summary

Debugging and Profiling

Debugging and Profiling

Debugging techniques

Troubleshooting guidelines

Profiling Python

Summary

GUIs and Scripting

GUIs and Scripting

First approach: scripting

Second approach: a GUI application

Where do we go from here?

Summary

Data Science in Brief

Data Science in Brief

IPython and Jupyter Notebook

Dealing with data

Where do we go from here?

Summary

Introduction to API Development

Introduction to API Development

What is the Web?

Type hinting: An overview

APIs: An introduction

The railway API

Consuming an API

Where do we go from here?

Summary

Packaging Python Applications

Packaging Python Applications

The Python Package Index

The train schedule project

Packaging with setuptools

Building and publishing packages

Advice for starting new projects

Alternative tools

Further reading

Summary

Other Books You May Enjoy

Other Books You May Enjoy

Index

Index

Scopes and name resolution

Do you remember when we talked about scopes and namespaces in Chapter 1, A Gentle Introduction to Python? We're going to expand on that concept now. Finally, we can talk in terms of functions, and this will make everything easier to understand. Let's start with a very simple example:

# scoping.level.1.py
def my_function():
    test = 1 # this is defined in the local scope of the function
    print('my_function:', test)
test = 0  # this is defined in the global scope
my_function()
print('global:', test)

We have defined the test name in two different places in the previous example—it is actually in two different scopes. One is the global scope (test = 0), and the other is the local scope of the my_function() function (test = 1). If we execute the code, we will see this:

$ python scoping.level.1.py
my_function: 1
global: 0

It's clear that test = 1 shadows the test = 0 assignment in my_function...

Visually different images

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Programming languages

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