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

In this lesson, you'll learn writing _iterators_ faster using fewer lines of code.

# Simplified iterators
[Previously](https://www.educative.io/courses/mastering-the-art-of-programming-in-python-3/iterators-in-python#iterator-from-scratch), we implemented a basic iterator from scratch. This is what the class looks like in its simplified version:
```python3
class Counter:
  def __init__(self):
    self.n =1

  def __iter__(self):
    return self  # Returning an iterator object
 
  def __next__(self):
      if self.n <= 10:
        x = self.n
        self.n += 1
        return x  # Returning next item in the sequence
      else:
        raise StopIteration
        return
```
Believe it or not, that's still a lot of code. We can lessen the length of the code by using Python's _generators_.

## What is a generator?

A function that is defined like a regular function, but generates the value using the `yield` keyword instead of `return`, is called a __generator__.

How about rewriting the above class using a _generator_?
```python3
def Counter():
    a = 1
    while a <= 10:
        yield a
        a += 1
```
See how the code's length shrinks to _five_ lines only! 

Generator functions return a generator object. Generator objects are used either by:
+ Calling the `__next__()` method on the generator object
+ Using the generator object in a `for-in` loop

> ⚙️ For Python 2.x,  the `next()` method is applicable. 

Let's implement a program to design a generator object.

Learn how generators iterate a sequence 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

Generators in Python

Simplified iterators