9.5. Methods and Attributes¶

9.5.1. Rationale¶

Methods are functions in the class

First argument is always instance (self)

While calling function you never pass self

Prevents copy-paste code

Improves readability

Improves refactoring

Decomposes bigger problem into smaller chunks

method: Function inside the class which takes self as a first argument.

Listing 9.26. Syntax¶

class MyClass:
    def __init__(self)
        self.myfield = 'some value'

    def mymethod(self):
        print(self.myfield)


my = MyClass()
my.mymethod()
# 'some value'

9.5.2. Methods Accessing Fields¶

Listing 9.27. Methods Accessing Fields¶

class Astronaut:
    def __init__(self, name):
        self.name = name

    def say_hello(self):
        print(f'My name... {self.name}')


jose = Astronaut('José Jiménez')
jose.say_hello()
# My name... José Jiménez

Listing 9.28. self.name must be defined before accessing.¶

class Astronaut:
    def say_hello(self):
        print(f'My name... {self.name}')


jose = Astronaut()
jose.say_hello()
# AttributeError: 'Astronaut' object has no attribute 'name'

9.5.3. Methods Calling Other Methods¶

Listing 9.29. Methods Calling Other Methods¶

class Astronaut:
    def get_name(self):
        return 'José Jiménez'

    def say_hello(self):
        name = self.get_name()
        print(f'My name... {name}')


jose = Astronaut()
jose.say_hello()
# My name... José Jiménez

Listing 9.30. Methods calling other methods¶

class Iris:
    def __init__(self):
        self.sepal_length = 5.1
        self.sepal_width = 3.5
        self.petal_length = 1.4
        self.petal_width = 0.2

    def sepal_area(self):
        return self.sepal_length * self.sepal_width

    def petal_area(self):
        return self.petal_length * self.petal_width

    def total_area(self):
        return self.sepal_area() + self.petal_area()


flower = Iris()
print(flower.total_area())
# Total area: 18.13

Listing 9.31. Since Python 3.7 there is a @dataclass decorator, which automatically generates __init__() arguments and fields. More information in OOP Dataclass.¶

from dataclasses import dataclass


@dataclass
class Iris:
    sepal_length: float = 5.8
    sepal_width: float = 2.7
    petal_length: float = 5.1
    petal_width: float = 1.9
    species: str = 'Iris'

    def sepal_area(self):
        return self.sepal_length * self.sepal_width

    def petal_area(self):
        return self.petal_length * self.petal_width

    def total_area(self):
        return self.sepal_area() + self.petal_area()


flower = Iris()
print(flower.total_area())
# Total area: 18.13

9.5.4. Examples¶

Documentation: https://atlassian-python-api.readthedocs.io
Source Code: https://github.com/atlassian-api/atlassian-python-api
Examples: https://github.com/atlassian-api/atlassian-python-api/tree/master/examples

$ pip install atlassian-python-api

from atlassian import Jira

jira = Jira(
    url='http://localhost:8080',
    username='admin',
    password='admin')

JQL = 'project = DEMO AND status IN ("To Do", "In Progress") ORDER BY issuekey'

result = jira.jql(JQL)
print(result)

from atlassian import Confluence

confluence = Confluence(
    url='http://localhost:8090',
    username='admin',
    password='admin')

result = confluence.create_page(
    space='DEMO',
    title='This is the title',
    body='This is the body. You can use <strong>HTML tags</strong>!')

print(result)

class Point:
    def __init__(self, x, y, z):
        self.x = x
        self.y = y
        self.z = z

    def get_coordinates(self):
        return self.x, self.y, self.z

    def show(self):
        print(f'Point(x={self.x}, y={self.y}, z={self.z})')


point = Point(x=1, y=2, z=3)

print(point.x)      # 1
print(point.y)      # 2
print(point.z)      # 3

point.get_coordinates()
# (1, 2, 3)

point.show()
# Point(x=1, y=2, z=3)

9.5.5. Assignments¶

9.5.5.1. OOP Method Sequence¶

Complexity level: easy
Lines of code to write: 18 lines
Estimated time of completion: 13 min
Solution: solution/oop_method_sequence.py

English

Use data from "Input" section (see below)
Create class Iris with features: List[float] and label: str attributes
For each row in DATA create Iris instance with row values
Set class attributes at the initialization from positional arguments
Create method which sums values of all features
Print species name and a sum method result
Compare result with "Output" section (see below)

Polish

Użyj danych z sekcji "Input" (patrz poniżej)
Stwórz klasę Iris z atrybutami features: List[float] i label: str
Dla każdego wiersza w DATA twórz instancję Iris z danymi z wiersza
Ustaw atrybuty klasy przy inicjalizacji z argumentów pozycyjnych
Stwórz metodę sumującą wartości wszystkich features
Wypisz nazwę gatunku i wynik metody sumującej
Porównaj wyniki z sekcją "Output" (patrz poniżej)

Input

DATA = [
    (4.7, 3.2, 1.3, 0.2, 'setosa'),
    (7.0, 3.2, 4.7, 1.4, 'versicolor'),
    (7.6, 3.0, 6.6, 2.1, 'virginica'),
]

Output

setosa 9.4
versicolor 16.299999999999997
virginica 19.3

9.5.5.2. OOP Method Nested¶

Complexity level: medium
Lines of code to write: 15 lines
Estimated time of completion: 21 min
Solution: solution/oop_method_nested.py

English

Use data from "Input" section (see below)
Define class Iris
Iris has:
- "Sepal length" type float
- "Sepal width" type float
- "Petal length" type float
- "Petal width" type float
- "Species" type str
Iris can:
- Return number of float type attributes
- Return list of all float type attributes
- Return sum of values of all float type attributes
- Return mean of all float type attributes
Use self.__dict__ iteration to return values of numeric fields
Create setosa object with attributes set at the initialization
Create virginica object with attributes set at the initialization
Print sum, mean and species name of each objects
Do not use @dataclass
Compare result with "Output" section (see below)

Polish

Użyj danych z sekcji "Input" (patrz poniżej)
Zdefiniuj klasę Iris
Iris ma:
- "Sepal length" typu float
- "Sepal width" typu float
- "Petal length" typu float
- "Petal width" typu float
- "Species" typu str
Iris może:
- Zwrócić liczbę pól typu float
- Zwrócić listę wartości wszystkich pól typu float
- Zwrócić sumę wartości pól typu float
- Zwrócić średnią arytmetyczną wartość pól typu float
Użyj iterowania po self.__dict__ do zwrócenia wartości pól numerycznych
Stwórz obiekt setosa z atrybutami ustawionymi przy inicjalizacji
Stwórz obiekt virginica z atrybutami ustawionymi przy inicjalizacji
Wypisz sumę, średnią oraz nazwę gatunku każdego z obiektów
Nie używaj @dataclass
Porównaj wyniki z sekcją "Output" (patrz poniżej)

Input

class Iris:
    def __init__(self, sepal_length, sepal_width,
                petal_length, petal_width, species):

        self.sepal_length = sepal_length
        self.sepal_width = sepal_width
        self.petal_length = petal_length
        self.petal_width = petal_width
        self.species = species


setosa = Iris(5.1, 3.5, 1.4, 0.2, 'setosa')
virginica = Iris(5.8, 2.7, 5.1, 1.9, 'virginica')

print(setosa.show())
print(virginica.show())

Output

total=10.20 mean=2.55 setosa
total=15.50 mean=3.88 virginica

Hint

isinstance(value, float)