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!