The primary purpose of this project is to serve as a resource for myself and others with understanding different concepts in Python with the use of examples.

In computer programming, classes are a great way to organize attributes (variables) and methods (functions) so that they are easy to reuse and extend later. In this notebook, we walk through how to build a basic class in python. Specifically, we discuss the example of implementing a class that represents company employees.

In this simple example from our Objects and Classes notebook, we have created an Employee class, then used the __init__() method to define attributes name and income automatically as we instantiate our employee1 and employee2 objects.

class Employee: def __init__(self, name, income): self.name=name self.income=income employee1=Employee('Matt',50000) print(employee1.name) print(employee1.income) employee2=Employee('Penelope',90000) print(employee2.name) print(employee2.income) # OUTPUT Matt 50000 Penelope 90000 

Python generators are a simple way of creating iterators. All the work we mentioned above are automatically handled by generators in Python. Simply speaking, a generator is a function that returns an object (iterator) which we can iterate over (one value at a time).

In this simple example from our Generators notebook, here we create a generator function to produce odd numbers

def get_odds_generator(): n=1 n+=2 yield n n+=2 yield n n+=2 yield n numbers=get_odds_generator() print(next(numbers)) print(next(numbers)) print(next(numbers)) 

In comparison to a simple class-based iterator:

class get_odds: def __init__(self, max): self.n=3 self.max=max def __iter__(self): return self def __next__(self): if self.n <= self.max: result = self.n self.n += 2 return result else: raise StopIteration numbers = get_odds(10) print(next(numbers)) print(next(numbers)) print(next(numbers)) 

Generator functions are much easier and simpler to understand!