4.4. Dataclass Define Nested¶
4.4.1. SetUp¶
>>> from dataclasses import dataclass
>>> from typing import Self
4.4.2. Relation to Objects¶
>>> @dataclass
... class Group:
... gid: int
... name: str
>>>
>>>
>>> @dataclass
... class User:
... firstname: str
... lastname: str
... groups: list[Group]
Usage:
>>> mark = User('Mark', 'Watney', groups=[
... Group(gid=1, name='users'),
... Group(gid=2, name='staff'),
... Group(gid=3, name='admins')])
4.4.3. Relation to Self¶
Note, that there are
Nonedefault friendsUsing an empty list
[]as a default value will not workSelfis available since Python 3.11We will cover this topic later
Import:
>>> from typing import Self
Define class:
>>> @dataclass
... class User:
... firstname: str
... lastname: str
... friends: list[Self] = None
Use:
>>> mark = User('Mark', 'Watney', friends=[
... User('Melissa', 'Lewis'),
... User('Rick', 'Martinez'),
... User('Beth', 'Johanssen'),
... User('Chris', 'Beck'),
... User('Alex', 'Vogel')])
4.4.4. Assignments¶
"""
* Assignment: Dataclass DefineRelations Syntax
* Complexity: easy
* Lines of code: 16 lines
* Time: 5 min
English:
1. You received input data in JSON format from the API
2. Using `dataclass` model `DATA`:
a. Create class `Pet`
b. Create class `Category`
c. Create class `Tags`
3. Model relations between classes
4. Run doctests - all must succeed
Polish:
1. Otrzymałeś z API dane wejściowe w formacie JSON
2. Wykorzystując `dataclass` zamodeluj `DATA`:
a. Stwórz klasę `Pet`
b. Stwórz klasę `Category`
c. Stwórz klasę `Tags`
3. Zamodeluj relacje między klasami
4. Uruchom doctesty - wszystkie muszą się powieść
References:
[1]: https://petstore.swagger.io/#/pet/getPetById
Tests:
>>> import sys; sys.tracebacklimit = 0
>>> from inspect import isclass
>>> from dataclasses import is_dataclass
>>> import json
>>> assert isclass(Pet)
>>> assert isclass(Category)
>>> assert isclass(Tag)
>>> assert is_dataclass(Pet)
>>> assert is_dataclass(Category)
>>> assert is_dataclass(Tag)
>>> fields = {'id', 'category', 'name', 'photoUrls', 'tags', 'status'}
>>> assert set(Pet.__dataclass_fields__.keys()) == fields, \
f'Invalid fields, your fields should be: {fields}'
>>> data = json.loads(DATA)
>>> result = Pet(**data)
>>> result.category = Category(**result.category)
>>> result.tags = [Tag(**tag) for tag in result.tags]
>>> result # doctest: +NORMALIZE_WHITESPACE
Pet(id=0, category=Category(id=0, name='dogs'), name='doggie',
photoUrls=['img/dogs/0.png'], tags=[Tag(id=0, name='dog'),
Tag(id=1, name='hot-dog')],
status='available')
"""
from dataclasses import dataclass
DATA = """
{
"id": 0,
"category": {
"id": 0,
"name": "dogs"
},
"name": "doggie",
"photoUrls": [
"img/dogs/0.png"
],
"tags": [
{
"id": 0,
"name": "dog"
},
{
"id": 1,
"name": "hot-dog"
}
],
"status": "available"
}
"""
# Using `dataclass` model `DATA`, create class `Category`
# type: type
@dataclass
class Category:
...
# Using `dataclass` model `DATA`, create class `Tag`
# type: type
@dataclass
class Tag:
...
# Using `dataclass` model `DATA`, create class `Pet`
# type: type
@dataclass
class Pet:
...
"""
* Assignment: Dataclass Field Addressbook
* Complexity: easy
* Lines of code: 12 lines
* Time: 8 min
English:
1. Model `DATA` using `dataclasses`
2. Create class definition, fields and their types
3. Do not write code converting `DATA` to your classes
4. Run doctests - all must succeed
Polish:
1. Zamodeluj `DATA` wykorzystując `dataclass`
2. Stwórz definicję klas, pól i ich typów
3. Nie pisz kodu konwertującego `DATA` do Twoich klas
4. Uruchom doctesty - wszystkie muszą się powieść
Non-functional Requirements:
* Use Python 3.10 syntax for Optionals, ie: `str | None`
Tests:
>>> import sys; sys.tracebacklimit = 0
>>> from inspect import isclass
>>> from dataclasses import is_dataclass
>>> from typing import get_type_hints
>>> assert isclass(User)
>>> assert isclass(Address)
>>> assert is_dataclass(User)
>>> assert is_dataclass(Address)
>>> user = get_type_hints(User)
>>> address = get_type_hints(Address)
>>> assert 'firstname' in user, \
'Class User is missing field: firstname'
>>> assert 'lastname' in user, \
'Class User is missing field: lastname'
>>> assert 'addresses' in user, \
'Class User is missing field: addresses'
>>> assert 'street' in address, \
'Class Address is missing field: street'
>>> assert 'city' in address, \
'Class Address is missing field: city'
>>> assert 'post_code' in address, \
'Class Address is missing field: post_code'
>>> assert 'region' in address, \
'Class Address is missing field: region'
>>> assert 'country' in address, \
'Class Address is missing field: country'
>>> assert user['firstname'] is str, \
'User.firstname has invalid type annotation, expected: str'
>>> assert user['lastname'] is str, \
'User.lastname has invalid type annotation, expected: str'
>>> assert user['addresses'] == list[Address] | None, \
'User.addresses has invalid type annotation, expected: list[Address] | None'
>>> assert address['street'] == str | None, \
'Address.street has invalid type annotation, expected: str | None'
>>> assert address['city'] is str, \
'Address.city has invalid type annotation, expected: str'
>>> assert address['post_code'] is int, \
'Address.post_code has invalid type annotation, expected: int'
>>> assert address['region'] is str, \
'Address.region has invalid type annotation, expected: str'
>>> assert address['country'] is str, \
'Address.country has invalid type annotation, expected: str'
"""
from dataclasses import dataclass
DATA = [
{"firstname": "Mark", "lastname": "Watney", "addresses": [
{"street": "2101 E NASA Pkwy", "city": "Houston", "post_code": 77058,
"region": "Texas", "country": "USA"},
{"street": None, "city": "Kennedy Space Center", "post_code": 32899,
"region": "Florida", "country": "USA"}]},
{"firstname": "Melissa", "lastname": "Lewis", "addresses": [
{"street": "4800 Oak Grove Dr", "city": "Pasadena", "post_code": 91109,
"region": "California", "country": "USA"},
{"street": "2825 E Ave P", "city": "Palmdale", "post_code": 93550,
"region": "California", "country": "USA"}]},
{"firstname": "Rick", "lastname": "Martinez"},
{"firstname": "Alex", "lastname": "Vogel", "addresses": [
{"street": "Linder Hoehe", "city": "Cologne", "post_code": 51147,
"region": "North Rhine-Westphalia", "country": "Germany"}]}
]
# Model `DATA` using `dataclass`
# type: type
@dataclass
class Address:
...
# Model `DATA` using `dataclass`
# type: type
@dataclass
class User:
...
"""
* Assignment: Dataclass DefineBasic DatabaseDump
* Complexity: medium
* Lines of code: 13 lines
* Time: 13 min
English:
1. You received input data in JSON format from the API
a. `str` fields: firstname, lastname, role, username, password, email,
b. `date` field: birthday,
c. `datetime` field: last_login (optional),
d. `bool` fields: is_active, is_staff, is_superuser,
e. `list[dict]` field: user_permissions
2. Using `dataclass` model data as class `User`
3. Do not create additional classes to represent `permission` field,
leave it as `list[dict]`
4. Note, that fields order is important for tests to pass
5. Run doctests - all must succeed
Polish:
1. Otrzymałeś z API dane wejściowe w formacie JSON
a. pola `str`: firstname, lastname, role, username, password, email,
b. pole `date`: birthday,
c. pole `datetime`: last_login (opcjonalne),
d. pola `bool`: is_active, is_staff, is_superuser,
e. pola `list[dict]`: user_permissions
2. Wykorzystując `dataclass` zamodeluj dane za pomocą klasy `User`
3. Nie twórz dodatkowych klas do reprezentacji pola `permission`,
niech zostanie jako `list[dict]`
4. Zwróć uwagę, że kolejność pól ma znaczenie aby testy przechodziły
5. Uruchom doctesty - wszystkie muszą się powieść
Hints:
* `pk` - Primary Key (unique identifier, an ID in database)
* `model` - package name with name of a class
* `datetime | None`
* `date`
* `list[dict]`
Tests:
>>> import sys; sys.tracebacklimit = 0
>>> from inspect import isclass
>>> from dataclasses import is_dataclass
>>> from pprint import pprint
>>> assert isclass(User)
>>> assert is_dataclass(User)
>>> attributes = User.__dataclass_fields__.keys()
>>> list(attributes) # doctest: +NORMALIZE_WHITESPACE
['firstname', 'lastname', 'role', 'username', 'password', 'email', 'birthday',
'last_login', 'is_active', 'is_staff', 'is_superuser', 'user_permissions']
>>> pprint(User.__annotations__, sort_dicts=False)
{'firstname': <class 'str'>,
'lastname': <class 'str'>,
'role': <class 'str'>,
'username': <class 'str'>,
'password': <class 'str'>,
'email': <class 'str'>,
'birthday': <class 'datetime.date'>,
'last_login': datetime.datetime | None,
'is_active': <class 'bool'>,
'is_staff': <class 'bool'>,
'is_superuser': <class 'bool'>,
'user_permissions': list[dict]}
>>> result = [User(**user['fields']) for user in json.loads(DATA)]
>>> pprint(result[0]) # doctest: +ELLIPSIS
User(firstname='Melissa',
lastname='Lewis',
role='commander',
username='mlewis',
password='pbkdf2_sha256$120000$gvEBNiCeTrYa0$5C+NiCeTrYsha1PHog...=',
email='mlewis@nasa.gov',
birthday='1995-07-15',
last_login='1970-01-01T00:00:00.000+00:00',
is_active=True,
is_staff=True,
is_superuser=False,
user_permissions=[{'eclss': ['add', 'modify', 'view']},
{'communication': ['add', 'modify', 'view']},
{'medical': ['add', 'modify', 'view']},
{'science': ['add', 'modify', 'view']}])
"""
import json
from dataclasses import dataclass
from datetime import date, datetime
DATA = ('[{"model":"authorization.user","pk":1,"fields":{"firstname":"Meli'
'ssa","lastname":"Lewis","role":"commander","username":"mlewis","p'
'assword":"pbkdf2_sha256$120000$gvEBNiCeTrYa0$5C+NiCeTrYsha1PHogqv'
'XNiCeTrY0CRSLYYAA90=","email":"mlewis@nasa.gov","birthday":"1995-'
'07-15","last_login":"1970-01-01T00:00:00.000+00:00","is_active":t'
'rue,"is_staff":true,"is_superuser":false,"user_permissions":[{"ec'
'lss":["add","modify","view"]},{"communication":["add","modify","v'
'iew"]},{"medical":["add","modify","view"]},{"science":["add","mod'
'ify","view"]}]}},{"model":"authorization.user","pk":2,"fields":{"'
'firstname":"Rick","lastname":"Martinez","role":"pilot","username"'
':"rmartinez","password":"pbkdf2_sha256$120000$aXNiCeTrY$UfCJrBh/q'
'hXohNiCeTrYH8nsdANiCeTrYnShs9M/c=","birthday":"1996-01-21","last_'
'login":null,"email":"rmartinez@nasa.gov","is_active":true,"is_sta'
'ff":true,"is_superuser":false,"user_permissions":[{"communication'
'":["add","view"]},{"eclss":["add","modify","view"]},{"science":["'
'add","modify","view"]}]}},{"model":"authorization.user","pk":3,"f'
'ields":{"firstname":"Alex","lastname":"Vogel","role":"chemist","u'
'sername":"avogel","password":"pbkdf2_sha256$120000$eUNiCeTrYHoh$X'
'32NiCeTrYZOWFdBcVT1l3NiCeTrY4WJVhr+cKg=","email":"avogel@esa.int"'
',"birthday":"1994-11-15","last_login":null,"is_active":true,"is_s'
'taff":true,"is_superuser":false,"user_permissions":[{"eclss":["ad'
'd","modify","view"]},{"communication":["add","modify","view"]},{"'
'medical":["add","modify","view"]},{"science":["add","modify","vie'
'w"]}]}},{"model":"authorization.user","pk":4,"fields":{"firstname'
'":"Chris","lastname":"Beck","role":"crew-medical-officer","userna'
'me":"cbeck","password":"pbkdf2_sha256$120000$3G0RNiCeTrYlaV1$mVb6'
'2WNiCeTrYQ9aYzTsSh74NiCeTrY2+c9/M=","email":"cbeck@nasa.gov","bir'
'thday":"1999-08-02","last_login":"1970-01-01T00:00:00.000+00:00",'
'"is_active":true,"is_staff":true,"is_superuser":false,"user_permi'
'ssions":[{"communication":["add","view"]},{"medical":["add","modi'
'fy","view"]},{"science":["add","modify","view"]}]}},{"model":"aut'
'horization.user","pk":5,"fields":{"firstname":"Beth","lastname":"'
'Johanssen","role":"sysop","username":"bjohanssen","password":"pbk'
'df2_sha256$120000$QmSNiCeTrYBv$Nt1jhVyacNiCeTrYSuKzJ//WdyjlNiCeTr'
'YYZ3sB1r0g=","email":"bjohanssen@nasa.gov","birthday":"2006-05-09'
'","last_login":null,"is_active":true,"is_staff":true,"is_superuse'
'r":false,"user_permissions":[{"communication":["add","view"]},{"s'
'cience":["add","modify","view"]}]}},{"model":"authorization.user"'
',"pk":6,"fields":{"firstname":"Mark","lastname":"Watney","role":"'
'botanist","username":"mwatney","password":"pbkdf2_sha256$120000$b'
'xS4dNiCeTrY1n$Y8NiCeTrYRMa5bNJhTFjNiCeTrYp5swZni2RQbs=","email":"'
'mwatney@nasa.gov","birthday":"1994-10-12","last_login":null,"is_a'
'ctive":true,"is_staff":true,"is_superuser":false,"user_permission'
's":[{"communication":["add","modify","view"]},{"science":["add","'
'modify","view"]}]}}]')
# Convert JSON to Python dict
data = json.loads(DATA)
# Using `dataclass` model data as class `User`
# a. `str` fields: firstname, lastname, role, username, password, email,
# b. `date` field: birthday,
# c. `datetime` field: last_login (optional),
# c. `bool` fields: is_active, is_staff, is_superuser,
# d. `list[dict]` field: user_permissions
# Leave `permission` attribute as `list[dict]`
# Note, that fields order is important for tests to pass
# type: type
class User:
...