Python Projects for Beginners a ten-Week Bootcamp Approach to Python Programming

MONDAY EXERCISES

1. 
   . Reverse Iteration: Create an iterator that takes in a list, and when iterated over, it returns the information in a reverse order. Hint: When accepting arguments into an iterator, you need to use the init method, as well as iter and next. the following call should result in “5, 4, 3, 2, 1”.
   

>>> for i in RevIter( [ 1, 2, 3, 4, 5 ] ):

2. 
   . Squares: Create a generator that acts like the range function, except it yields a squared number every time. the result of the following call should be “0, 1, 4, 16”.
   

>>> for i in range(4):

today we were able to understand how to build our own range function, as well as how data collections can be iterated over. Generators are simplified version of iterators but use the yield keyword to return information. iterators must always be created by using the iter and next methods and are useful for creating our own sequence for iterating.
Tuesday: Decorators
If you want to learn about frameworks, or understand how to improve functions within Python, then you need to understand what a decorator is and how it works. It will help to simplify our code as well as reduce the lines necessary to improve our programs.
To follow along with this lesson, let’s continue from our previous notebook file
“Week_09” and simply add a markdown cell at the bottom that says “Decorators.”
What Are Decorators?
Decorators, also known as wrappers, are functions that give other functions extra capabilities without explicitly modifying them. They are denoted by the “@” symbol in front of the function name, which is written above a function declaration like the
following:
>>> @decorator >>> def normalFunc( ):
Decorators are useful when you want to perform some functionality before or after a function executes. For example, let’s imagine you wanted to restrict access to a function based on a user being logged in. Rather than writing the same conditional statement for every function you create, you could put the code into a decorator and apply the decorator onto all functions. Now, whenever a function is called, the conditional statement will still run, but you were able to save yourself several lines. This is a real-life example for the Flask framework, which restricts access to certain pages based on user authentication using decorators. We’ll see a minimal example of this later today.