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
2) Generators
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!