Book Image

Python: Journey from Novice to Expert

By : Fabrizio Romano, Dusty Phillips, Rick van Hattem
Book Image

Python: Journey from Novice to Expert

By: Fabrizio Romano, Dusty Phillips, Rick van Hattem

Overview of this book

Python is a dynamic and powerful programming language, having its application in a wide range of domains. It has an easy-to-use, simple syntax, and a powerful library, which includes hundreds of modules to provide routines for a wide range of applications, thus making it a popular language among programing enthusiasts.This course will take you on a journey from basic programming practices to high-end tools and techniques giving you an edge over your peers. It follows an interesting learning path, divided into three modules. As you complete each one, you’ll have gained key skills and get ready for the material in the next module.The first module will begin with exploring all the essentials of Python programming in an easy-to-understand way. This will lay a good foundation for those who are interested in digging deeper. It has a practical and example-oriented approach through which both the introductory and the advanced topics are explained. Starting with the fundamentals of programming and Python, it ends by exploring topics, like GUIs, web apps, and data science.In the second module you will learn about object oriented programming techniques in Python. Starting with a detailed analysis of object-oriented technique and design, you will use the Python programming language to clearly grasp key concepts from the object-oriented paradigm. This module fully explains classes, data encapsulation, inheritance, polymorphism, abstraction, and exceptions with an emphasis on when you can use each principle to develop well-designed software.With a good foundation of Python you will move onto the third module which is a comprehensive tutorial covering advanced features of the Python language. Start by creating a project-specific environment using venv. This will introduce you to various Pythonic syntax and common pitfalls before moving onto functional features and advanced concepts, thereby gaining an expert level knowledge in programming and teaching how to script highest quality Python programs.

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Python: Journey from Novice to Expert
Fabrizio Romano | Dusty Phillips | Rick van Hattem
Aug, 2016 | 21 hours 51 minutes
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Table of Contents (6 chapters)
Preface
Preface
What this learning path covers
What you need for this learning path
Who this learning path is for
Reader feedback
Customer support
Free Chapter
1
1. Module 1
1. Module 1
1. Introduction and First Steps – Take a Deep Breath
2. Built-in Data Types
3. Iterating and Making Decisions
4. Functions, the Building Blocks of Code
5. Saving Time and Memory
6. Advanced Concepts – OOP, Decorators, and Iterators
7. Testing, Profiling, and Dealing with Exceptions
8. The Edges – GUIs and Scripts
9. Data Science
10. Web Development Done Right
11. Debugging and Troubleshooting
12. Summing Up – A Complete Example
2
2. Module 2
2. Module 2
1. Object-oriented Design
2. Objects in Python
3. When Objects Are Alike
4. Expecting the Unexpected
5. When to Use Object-oriented Programming
6. Python Data Structures
7. Python Object-oriented Shortcuts
8. Strings and Serialization
9. The Iterator Pattern
10. Python Design Patterns I
11. Python Design Patterns II
12. Testing Object-oriented Programs
13. Concurrency
3
3. Module 3
3. Module 3
1. Getting Started – One Environment per Project
2. Pythonic Syntax, Common Pitfalls, and Style Guide
3. Containers and Collections – Storing Data the Right Way
4. Functional Programming – Readability Versus Brevity
5. Decorators – Enabling Code Reuse by Decorating
6. Generators and Coroutines – Infinity, One Step at a Time
7. Async IO – Multithreading without Threads
8. Metaclasses – Making Classes (Not Instances) Smarter
9. Documentation – How to Use Sphinx and reStructuredText
10. Testing and Logging – Preparing for Bugs
11. Debugging – Solving the Bugs
12. Performance – Tracking and Reducing Your Memory and CPU Usage
13. Multiprocessing – When a Single CPU Core Is Not Enough
14. Extensions in C/C++, System Calls, and C/C++ Libraries
15. Packaging – Creating Your Own Libraries or Applications
4
A. Bibliography
A. Bibliography
5
Index
Index

Chapter 3. Containers and Collections – Storing Data the Right Way

Python comes bundled with several very useful collections, a few of which are basic Python collection data types. The rest are advanced combinations of these types. In this chapter, we will explain some of these collections, how to use them, and the pros and cons of each of them.

Before we can properly discuss data structures and the related performance, a basic understanding of time complexity (and specifically the big O notation) is required. No need to worry! The concept is really simple, but without it, we cannot easily explain the performance characteristics of operations.

Once the big O notation is clear, we will discuss the basic data structures:

  • list
  • dict
  • set
  • tuple

Building on the basic data structures, we will continue with more advanced collections, such as the following:

  • Dictionary-like types:
    • ChainMap
    • Counter
    • Defaultdict
    • OrderedDict
  • List types:
    • Deque
    • Heapq
  • Tuple types:
    • NamedTuple
  • Other types:
    • Enum

Time complexity...

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