Book Image

Learn Python Programming - Second Edition

By : Fabrizio Romano
4.5 (2)
Book Image

Learn Python Programming - Second Edition

4.5 (2)
By: Fabrizio Romano

Overview of this book

Learn Python Programming is a quick, thorough, and practical introduction to Python - an extremely flexible and powerful programming language that can be applied to many disciplines. Unlike other books, it doesn't bore you with elaborate explanations of the basics but gets you up-and-running, using the language. You will begin by learning the fundamentals of Python so that you have a rock-solid foundation to build upon. You will explore the foundations of Python programming and learn how Python can be manipulated to achieve results. Explore different programming paradigms and find the best approach to a situation; understand how to carry out performance optimization and effective debugging; control the flow of a program; and utilize an interchange format to exchange data. You'll also walk through cryptographic services in Python and understand secure tokens. Learn Python Programming will give you a thorough understanding of the Python language. You'll learn how to write programs, build websites, and work with data by harnessing Python's renowned data science libraries. Filled with real-world examples and projects, the book covers various types of applications, and concludes by building real-world projects based on the concepts you have learned.

Related Content you might be interested in

Current Title:

Small book image
Learn Python Programming - Second Edition
Fabrizio Romano
Jun, 2018 | 508 pages
Small book image
The Python Apprentice
Austin Bingham | Robert Smallshire
Jun, 2017 | 352 pages
Small book image
Python 3 Object-Oriented Programming
Dusty Phillips
Oct, 2018 | 466 pages
Small book image
Secret Recipes of the Python Ninja
Cody Jackson
May, 2018 | 380 pages
Table of Contents (16 chapters)
Preface
Preface
Who this book is for
What this book covers
To get the most out of this book
Get in touch
Free Chapter
1
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 you can run a Python program
How is Python code organized?
Python's execution model
Guidelines on how to write good code
The Python culture
A note on IDEs
Summary
2
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
The collections module
Enums
Final considerations
Summary
3
Iterating and Making Decisions
Iterating and Making Decisions
Conditional programming
Looping
Putting all this together
A quick peek at the itertools module
Summary
4
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
One final example
Documenting your code
Importing objects
Summary
5
Saving Time and Memory
Saving Time and Memory
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
6
OOP, Decorators, and Iterators
OOP, Decorators, and Iterators
Decorators
Object-oriented programming (OOP)
Writing a custom iterator
Summary
7
Files and Data Persistence
Files and Data Persistence
Working with files and directories
Data interchange formats
IO, streams, and requests
Persisting data on disk
Summary
8
Testing, Profiling, and Dealing with Exceptions
Testing, Profiling, and Dealing with Exceptions
Testing your application
Test-driven development
Exceptions
Profiling Python
Summary
9
Cryptography and Tokens
Cryptography and Tokens
The need for cryptography
Hashlib
Secrets
HMAC
JSON Web Tokens
Useful references
Summary
10
Concurrent Execution
Concurrent Execution
Concurrency versus parallelism
Threads and processes – an overview
Concurrent execution in Python
Case examples
Summary
11
Debugging and Troubleshooting
Debugging and Troubleshooting
Debugging techniques
Troubleshooting guidelines
Summary
12
GUIs and Scripts
GUIs and Scripts
First approach – scripting
Second approach – a GUI application
Where do we go from here?
Summary
13
Data Science
Data Science
IPython and Jupyter Notebook
Dealing with data
Where do we go from here?
Summary
14
Web Development
Web Development
What is the web?
How does the web work?
The Django web framework
A regex website
The future of web development
Summary
Farewell
15
Other Books You May Enjoy
Other Books You May Enjoy
Leave a review - let other readers know what you think

Concurrent execution in Python

Let's start by exploring the basics of Python multithreading and multiprocessing with some simple examples.

Keep in mind that several of the following examples will produce an output that depends on a particular run. When dealing with threads, things can get non-deterministic, as I mentioned earlier. So, if you experience different results, it is absolutely fine. You will probably notice that some of your results will vary from run to run too.

Starting a thread

First things first, let's start a thread:

# start.py
import threading

def sum_and_product(a, b):
    s, p = a + b, a * b
    print(f'{a}+{b}={s}, {a}*{b}={p}')

t = threading.Thread(
    target=sum_and_product, name=&apos...
Previous Section
End of Section 4
Next Section