Python Advanced Course - part I.pdf for Python

Python Advanced Course
Part I
Stefano Alberto Russo

Stefano Alberto Russo - @stefanoarusso - sarusso.github.io
● Part I: Object Oriented Programming
○ What is OOP?
○ Logical Example
○ Attributes and methods
○ Why to use objects
○ Deﬁning objects
● Part II: Improving your code
○ Extending objects
○ Lambdas
○ Comprehensions
○ Iterables
○ Properties
Outline
● Part III: Exceptions
○ What are exceptions?
○ Handling exceptions
○ Raising exceptions
○ Creating custom exceptions
● Part IV: logging and testing
○ The Python logging module
○ Basics about testing
○ The Python unit-testing module
○ Test-driven development

It is a programming paradigm. Things change quite a lot form “classic”
programming. Objects are “entities” which model the world around us.
Objects are deﬁned as classes
Object Oriented Programming
→ What is it?

Living organisms
Reptiles
Mammals
Bipeds Quadrupeds
→ What is it?

Glasses
Alcoholic Content
Alcohol Free
Content
Wine Liquor
White
Red
Coffee Beverages
Espresso American
→ What is it?

Glasses
Glass Plastic
Coloured Transparent
Painted
Compound
Recyclable
Not
Recyclable
→ What is it?

It is a programming paradigm. Things change quite a lot form “classic”
programming. Objects are “entities” which model the world around us.
Objects are deﬁned as classes.
To use objects, we need to create an instance of their class.
Objects can have:
- attributes (variables)
- methods (functions)
→ What is it?

Person Class
- name
- say_hi()
print('Hello!')
Person Class instance
- name = Mario
- say_hi()
print('Hello!')
Instantiation*
→ Logical Example
*Also known as construction or initialization

Person Class
- name
- say_hi()
print('Hello!')
- name = Mario
- say_hi()
print('Hello!')
- name = Lucia
- say_hi()
print('Hello!')
→ Logical Example

Person Class
- name
- say_hi()
print('Hello!')
- name = Mario
- say_hi()
print('Hello!')
- name = Lucia
- say_hi()
print('Hello!')
Attribute (variabile)
Funcion (method)
→ Logical Example

→ Class / instance attributes and methods
Person Class
- name
- say_hi()
print('Hello!')
By default, attributes and methods depend on the instance of the the class: they
behave differently for each instance.
However, if they don’t have to, then they can be
deﬁned as class or static.
For example, the say_hi() function can be be
deﬁned as a class method, as it produce the same
result regardless of the instance. If instead we
wanted to make the say_hi() function to include
the name of the person, then we couldn’t.

We use object for mainly two reasons:
- The allow to represent vey well hierarchies (and to exploit common
characteristics between them)
- Once instantiated, the allow to easily hold the status (without having to
rely on external support data structures)
→ Why to use objects

In Python there is a well deﬁned styling convention:
- lowercase characters and underscores for variables and the object instances
- CamelCase for the class names
Moreover, double underscores before and after the name of a method mean that
that method is exclusively for internal (private) use, as for the string representation
(__str__) or the initiator of the object (__init__).
→ They are commonly called “magic methods”.
→ Conventions

→ In Python everything is an object

examples.py examples.py
→ In Python everything is an object

examples.py examples.py
Operation (function, method) which
when executed returns a result
Operation (function, method) which when executed
changes the object, does not return anything!
→ Parenthesis: in-place operations

objects.py
→ Deﬁning objects

objects.py
instantiation

objects.py
“self” means “myself”, “myself class
instance”. It is mandatory in every
instance method, even if not used.
→ Deﬁning objects The “init” function is responsible for
initializing the object. If it is not defined, the
default one is used, which does nothing.

- To define class methods, use the @classmethod decorator. They have
the “cls” as first argument instead of the “self”
- To define static methods, use the @staticmethod decorator. They do
not have any special argument (no “self” nor “cls”).
→ A decorator is something placed above a function which “wraps”
the function and tells it to behave in a particular way
- To define static/class attributes, define them in the body of the class

objects.py
The “init” function is a magic method.

objects.py
→ Magic methods

objects.py
The __str__ funcion is a magic
method as well, and it is responsible
for the string representation of the
object (i.e. when you print it)
→ Magic methods

objects.py

objects.py
Instance method (function)

End of part I
→ Questions?
Next: exercise 1

Exercise 1
We want to write a predictive model for monthly shampoo sales.

Exercise 1
We want to write a predictive model for monthly shampoo sales.
Our model is extremely simple:
- given a window of n
- the sales at t+1 are given by:
- the average increment computed over the previous n months
- summed to the last point (t) of the window

Let’s chose to use 3 months for the prediction (n=3) and say that we want to
predict the sales for December (t+1).
We know that sales for September (t-2), October (t-1) and November (t) have
been, respectively, of 50, e 52 e 60 units.
Month Step Sales
September t-2 50
October t-1 52
November t (now) 60
December t+1 ?
Exercise 1
→ Example

Let’s chose to use 3 months for the prediction (n=3) and say that we want to
predict the sales for December (t+1).
We know that sales for September (t-2), October (t-1) and November (t) have
been, respectively, of 50, e 52 e 60 units.
Month Step Sales
September t-2 50
October t-1 52
November t (now) 60
December t+1 (2+8)/2 + 60 = 65
Exercise 1
→ Example

Exercise 1
The IncrementModel() class must have a fit() method (which does nothing)
and a predict() method. Both methods must take a “data” argument.
class IncrementModel():
def __init__(self, window)
self.window = window
def fit(self, data):
# Not implemented
pass
def predict(self, data):
# Compute and return the prediction
prediction = ...
return prediction
excercise.py

Python Advanced Course - part I.pdf for Python

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