Gain insights into advanced Python 3, learn the Pythonic Way, explore data structures, functional and object-oriented paradigms, and master iterables, generators, and coroutines through practical projects.

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This highly interactive and advanced course will give you insight into the most common Python tricks and tips. This course is for practicing Python programmers who are aiming for proficiency in Python 3. If you want to switch from Python 2 to Python 3, this is your go-to course. 

This course will help you learn the Pythonic Way of writing code and leveraging advanced robust features to become more proficient than the average developer. You’ll start by covering Python’s built-in data structures, and then you’ll move on to different programming paradigms like functional programming and object-oriented programming. 

In the latter half of the course, you’ll focus on iterables, generators, and coroutines. You’ll also have the opportunity to work on two projects to help strengthen what you learn. In all, this course is perfect for anyone who wants to become a confident and competent Pythonista by picking up the idioms and practical tips.

Mastering the Art of Programming in Python 3

This lesson lists different implementations of stack and queue provided by Python 3 and explains when to use which built-in support.

# Introduction

A __stack__ is a data structure that follows the __LIFO__ (**L**ast **I**n **F**irst **O**ut) order for _push_ (insertion) and _pop_ (deletion) functions. 

A __queue__ is a data structure that follows the __FIFO__ (**F**irst **I**n **F**irst **O**ut) order for _enqueue_ (insertion) and _dequeue_ (deletion) functions.

# Stack and queue implementation

## Using `list` 
As you know, `list` is one of the basic built-in data structures in Python. It allows random access in $O(1)$ time using the indexing `[]` operator. 
> 💡 __Note__: Randomly accessing an element means that instead of traversing through an entire data structure, we jump to a position and directly pick an item.

Its two functions `append()` and `pop()` (you must be familiar with them) just work like _push_ and _pop_ operations. 

The `list` type does make a good stack, because `append()` adds an element at the end and `pop()` deletes an element from the end, in amortized time of $O(1)$.

But the `list` is a terrible choice to make a queue because inserting at and deleting from the beginning requires shifting all the elements by one, requiring $O(n)$ time.

Learn how stack and queues work in Python.

Introduction

Built-in Data Structures

Functional Programming

Project I: Data Science with Data Structures

Data science with Data Structures

Project I Review

Object-Oriented Idioms

Iterables and Generators

Coroutines

Project II: Build Your Own Matrix Module

Build Your Own Matrix Library

Project II Review

Meta-Programming

The End

Stacks and Queues

Introduction

Stack and queue implementation

Using `list`

Data science with Data Structures

Build Your Own Matrix Library

Stacks and Queues

Introduction

Stack and queue implementation

Using list

Using `list`