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Given the following text description, write Python code to implement the functionality described below step by step
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Description:
 SAISOFT PYT-PR
Step1:  Continue to "doodle and daydream" as you find the time.  Think of ways to describe your day as a Python program.  Remember the story of The Car that Would Not Start.
Run this a few times to see the different possible workflows.
Step3:  We also learned about decorator syntax.  Using a decorator, we're able to use a callable as an input to an object that provides a proxy output, likewise callable by the same name.
Step4:  @wraps forwards the __doctstring__ and __name__ of the incoming f argument to the proxy being wrapped.
LAB
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Python Code:
lessons = {
    "1": "Python is part of a bigger ecosystem (example: Jupyter Notebooks).",
    "2": "Batteries Included refers to the well-stocked standard library.",
    "3": "Built-ins inside __builtins__ include the basic types such as...",
    "4": "__ribs__ == special names == magic methods (but not all are methods).",
    "5": "3rd Party Python is where a lot of the action is!",
    "6": "'Python fits your brain' means it gets out of your way once you learn it."
}
important_types = [{'Numeric': ["int", "float", "Decimal", "Fraction", "complex"],
                    'Collections': [{"Sequences": ["list", "range", "tuple"],
                                      "Mappings": ['dict', 'set']}],
                    'Descriptors': ['property']}, 
                   {'Other types': ['function', 'class', 'generator']}]
for key, value in lessons.items():  # dict method to return all key:value pairs
    print("{}.: {}".format(key, value), file=None) # this could be HTML to a file
    if key == "3":
        print()
        for the_type in important_types[0]['Numeric']:
            print(the_type)
        for the_type in important_types[0]['Collections'][0]['Sequences']:
            print(the_type)  
        for the_type in important_types[0]['Collections'][0]['Mappings']:
            print(the_type)
        print()
Explanation: SAISOFT PYT-PR:  Session 10
What Have We Learned?
End of explanation
import random
class BatteryDead(Exception):
    pass
class IgnitionKeyBroken(Exception):
    pass
class Car:
    
    def start(self):
        as_luck_would_have_it = random.randint(0,10)
        if as_luck_would_have_it == 10:
            raise BatteryDead
        elif as_luck_would_have_it == 0:
            raise IgnitionKeyBroken
        print("Car starts!")
try:
    # might not work
    my_car = Car()
    my_car.start()
except BatteryDead:
    print("Oops, need to charge battery")
except IgnitionKeyBroken:
    print("Oops, your key just snapped") 
Explanation: Continue to "doodle and daydream" as you find the time.  Think of ways to describe your day as a Python program.  Remember the story of The Car that Would Not Start.
Run this a few times to see the different possible workflows.
End of explanation
from functools import wraps
def decorator(f):
    @wraps(f)
    def proxy(x):
        # proxy
        print("Look at me!")
        return f(x)
    return proxy
@decorator
def Sqr(x):
    Square Dancer
    return x * x
Sqr(10)
Explanation: We also learned about decorator syntax.  Using a decorator, we're able to use a callable as an input to an object that provides a proxy output, likewise callable by the same name.
End of explanation
help(Sqr)
Explanation: @wraps forwards the __doctstring__ and __name__ of the incoming f argument to the proxy being wrapped.
LAB:
Try commenting out the line with @wraps on it and checking the __doctstring__ and __name__ of Sqr again.
Comment out @wraps
re-run the cell containing the two function definitions
re-run the cell below, and not changes
change it back
End of explanation
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