{"id":220,"date":"2024-01-25T16:22:31","date_gmt":"2024-01-25T16:22:31","guid":{"rendered":"https:\/\/learnpython.elegantwallp.com\/?p=220"},"modified":"2024-01-25T16:22:44","modified_gmt":"2024-01-25T16:22:44","slug":"python-dataclass","status":"publish","type":"post","link":"https:\/\/learnpython.elegantwallp.com\/2024\/01\/25\/python-dataclass\/","title":{"rendered":"Python dataclass"},"content":{"rendered":"\n

Summary<\/strong>: in this tutorial, you\u2019ll learn about the Python dataclass decorator and how to use it effectively.<\/p>\n\n\n\n

Introduction to the Python dataclass<\/h2>\n\n\n\n

Python introduced the dataclass in version 3.7 (PEP 557). The dataclass allows you to define\u00a0classes\u00a0with less code and more functionality out of the box.<\/p>\n\n\n\n

The following defines a regular\u00a0Person<\/code>\u00a0class with two instance attributes\u00a0name<\/code>\u00a0and\u00a0age<\/code>:<\/p>\n\n\n\n

class Person: def __init__(self, name, age): self.name = name self.age = age <\/code>Code language: Python (python)<\/small><\/code><\/pre>\n\n\n\n
This Person<\/code> class has the __init__<\/code> method that initializes the name<\/code> and age<\/code> attributes.<\/p>\n\n\n\n
If you want to have a string representation of the\u00a0Person<\/code>\u00a0object, you need to implement the\u00a0__str__<\/code>\u00a0or\u00a0__repr__<\/code>\u00a0method. Also, if you want to compare two instances of the\u00a0Person<\/code>\u00a0class by an attribute, you need to implement the\u00a0__eq__<\/code>\u00a0method.<\/p>\n\n\n\n
However, if you use the dataclass, you\u2019ll have all of these features (and even more) without implementing these dunder methods.<\/p>\n\n\n\n
To make the Person<\/code> class a data class, you follow these steps:<\/p>\n\n\n\n
First, import the dataclass<\/code> decorator from the dataclasses<\/code> module:from dataclasses import dataclass<\/code>Code language: Python (python)<\/small><\/p>\n\n\n\n
Second, decorate the\u00a0Person<\/code>\u00a0class with the\u00a0dataclass<\/code>\u00a0decorator and declare the attributes:<\/p>\n\n\n\n
@dataclass class Person: name: str age: int<\/code>Code language: Python (python)<\/small><\/code><\/pre>\n\n\n\n
In this example, the\u00a0Person<\/code>\u00a0class has two attributes\u00a0name<\/code>\u00a0with the type\u00a0str<\/code>\u00a0and\u00a0age<\/code>\u00a0with the type\u00a0int<\/code>. By doing this, the @dataclass decorator implicitly creates the\u00a0__init__<\/code>\u00a0method like this:<\/p>\n\n\n\n
def __init__(name: str, age: int)<\/code>Code language: Python (python)<\/small><\/code><\/pre>\n\n\n\n
Note that the order of the attributes declared in the class will determine the orders of the parameters in the __init__<\/code> method.<\/p>\n\n\n\n
And you can create the\u00a0Person<\/code>\u2018s object:<\/p>\n\n\n\n
p1 = Person('John', 25)<\/code>Code language: Python (python)<\/small><\/code><\/pre>\n\n\n\n
When printing out the\u00a0Person<\/code>\u2018s object, you\u2019ll get a readable format:<\/p>\n\n\n\n
print(p1)<\/code>Code language: Python (python)<\/small><\/code><\/pre>\n\n\n\n
Output:<\/p>\n\n\n\n
Person(name='John', age=25)<\/code>Code language: Python (python)<\/small><\/code><\/pre>\n\n\n\n
Also, if you compare two\u00a0Person<\/code>\u2018s objects with the same attribute value, it\u2019ll return\u00a0True<\/code>. For example:<\/p>\n\n\n\n
p1 = Person('John', 25) p2 = Person('John', 25) print(p1 == p2)<\/code>Code language: Python (python)<\/small><\/code><\/pre>\n\n\n\n
Output:<\/p>\n\n\n\n
True<\/code>Code language: Python (python)<\/small><\/code><\/pre>\n\n\n\n
The following discusses other functions that a data class provides.<\/p>\n\n\n\n
Default values<\/h2>\n\n\n\n
When using a regular class, you can define default values for attributes. For example, the following\u00a0Person<\/code>\u00a0class has the\u00a0iq<\/code>\u00a0parameter with the default value of\u00a0100<\/code>.<\/p>\n\n\n\n
class Person: def __init__(self, name, age, iq=100): self.name = name self.age = age self.iq = iq<\/code>Code language: Python (python)<\/small><\/code><\/pre>\n\n\n\n
To define a default value for an attribute in the dataclass, you assign it to the attribute like this:<\/p>\n\n\n\n
from dataclasses import dataclass @dataclass class Person: name: str age: int iq: int = 100 print(Person('John Doe', 25))<\/code>Code language: Python (python)<\/small><\/code><\/pre>\n\n\n\n
Like the parameter rules, the attributes with the default values must appear after the ones without default values. Therefore, the following code will not work:<\/p>\n\n\n\n
from dataclasses import dataclass @dataclass class Person: iq: int = 100 name: str age: int<\/code>Code language: Python (python)<\/small><\/code><\/pre>\n\n\n\n
Convert to a tuple or a dictionary<\/h2>\n\n\n\n
The\u00a0dataclasses<\/code>\u00a0module has the\u00a0astuple()<\/code>\u00a0and\u00a0asdict()<\/code>\u00a0functions that convert an instance of the dataclass to a\u00a0tuple\u00a0and a\u00a0dictionary. For example:<\/p>\n\n\n\n
from dataclasses import dataclass, astuple, asdict @dataclass class Person: name: str age: int iq: int = 100 p = Person('John Doe', 25) print(astuple(p)) print(asdict(p))<\/code>Code language: Python (python)<\/small><\/code><\/pre>\n\n\n\n
Output:<\/p>\n\n\n\n
('John Doe', 25, 100) {'name': 'John Doe', 'age': 25, 'iq': 100}<\/code>Code language: Python (python)<\/small><\/code><\/pre>\n\n\n\n
Create immutable objects<\/h2>\n\n\n\n
To create readonly objects from a dataclass, you can set the frozen argument of the dataclass decorator to\u00a0True<\/code>. For example:<\/p>\n\n\n\n
from dataclasses import dataclass, astuple, asdict @dataclass(frozen=True) class Person: name: str age: int iq: int = 100<\/code>Code language: Python (python)<\/small><\/code><\/pre>\n\n\n\n
If you attempt to change the attributes of the object after it is created, you\u2019ll get an error. For example:<\/p>\n\n\n\n
p = Person('Jane Doe', 25) p.iq = 120<\/code>Code language: Python (python)<\/small><\/code><\/pre>\n\n\n\n
Error:<\/p>\n\n\n\n
dataclasses.FrozenInstanceError: cannot assign to field 'iq'<\/code>Code language: Python (python)<\/small><\/code><\/pre>\n\n\n\n
Customize attribute behaviors<\/h2>\n\n\n\n
If don\u2019t want to initialize an attribute in the __init__ method, you can use the field()<\/code> function from the dataclasses<\/code> module.<\/p>\n\n\n\n
The following example defines the\u00a0can_vote<\/code>\u00a0attribute that is initialized using the\u00a0__init__<\/code>\u00a0method:<\/p>\n\n\n\n
from dataclasses import dataclass, field class Person: name: str age: int iq: int = 100 can_vote: bool = field(init=False)<\/code>Code language: Python (python)<\/small><\/code><\/pre>\n\n\n\n
The field()<\/code> function has multiple interesting parameters such as repr<\/code>, hash<\/code>, compare<\/code>, and metadata<\/code>.<\/p>\n\n\n\n
If you want to initialize an attribute that depends on the value of another attribute, you can use the __post_init__<\/code> method. As its name implies, Python calls the __post_init__<\/code> method after the __init__<\/code> method.<\/p>\n\n\n\n
The following use the\u00a0__post_init__<\/code>\u00a0method to initialize the\u00a0can_vote<\/code>\u00a0attribute based on the\u00a0age<\/code>\u00a0attribute:<\/p>\n\n\n\n
from dataclasses import dataclass, field @dataclass class Person: name: str age: int iq: int = 100 can_vote: bool = field(init=False) def __post_init__(self): print('called __post_init__ method') self.can_vote = 18 <= self.age <= 70 p = Person('Jane Doe', 25) print(p)<\/code>Code language: Python (python)<\/small><\/code><\/pre>\n\n\n\n
Output:<\/p>\n\n\n\n
called the __post_init__ method Person(name='Jane Doe', age=25, iq=100, can_vote=True)<\/code>Code language: Python (python)<\/small><\/code><\/pre>\n\n\n\n
Sort objects<\/h2>\n\n\n\n
By default, a dataclass implements the __eq__<\/code> method.<\/p>\n\n\n\n
To allow different types of comparisons like\u00a0__lt__<\/code>,\u00a0__lte__<\/code>,\u00a0__gt__<\/code>,\u00a0__gte__<\/code>, you can set the order argument of the\u00a0@dataclass<\/code>\u00a0decorator to True:<\/p>\n\n\n\n
@dataclass(order=True)<\/code>Code language: CSS (css)<\/small><\/code><\/pre>\n\n\n\n
By doing this, the dataclass will sort the objects by every field until it finds a value that\u2019s not equal.<\/p>\n\n\n\n
In practice, you often want to compare objects by a particular attribute, not all attributes. To do that, you need to define a field called sort_index<\/code> and set its value to the attribute that you want to sort.<\/p>\n\n\n\n
For example, suppose you have a list of\u00a0Person<\/code>\u2018s objects and want to sort them by age:<\/p>\n\n\n\n
members = [ Person('John', 25), Person('Bob', 35), Person('Alice', 30) ]<\/code>Code language: Python (python)<\/small><\/code><\/pre>\n\n\n\n
To do that, you need to:<\/p>\n\n\n\n
    \n
  • First, pass the order=True<\/code> parameter to the @dataclass<\/code> decorator.<\/li>\n\n\n\n
  • Second, define the sort_index<\/code> attribute and set its init<\/code> parameter to False<\/code>.<\/li>\n\n\n\n
  • Third, set the sort_index<\/code> to the age<\/code> attribute in the __post_init__<\/code> method to sort the Person<\/code>\u2018s object by age.<\/li>\n<\/ul>\n\n\n\n
    The following shows the code for sorting\u00a0Person<\/code>\u2018s objects by age:<\/p>\n\n\n\n
    from dataclasses import dataclass, field @dataclass(order=True) class Person: sort_index: int = field(init=False, repr=False) name: str age: int iq: int = 100 can_vote: bool = field(init=False) def __post_init__(self): self.can_vote = 18 <= self.age <= 70 # sort by age<\/em> self.sort_index = self.age members = [ Person(name='John', age=25), Person(name='Bob', age=35), Person(name='Alice', age=30) ] sorted_members = sorted(members) for member in sorted_members: print(f'{member.name}(age={member.age})')<\/code>Code language: Python (python)<\/small><\/code><\/pre>\n\n\n\n
    Output:<\/p>\n\n\n\n
    John(age=25) Alice(age=30) Bob(age=35)<\/code><\/code><\/pre>\n","protected":false},"excerpt":{"rendered":"
    Summary: in this tutorial, you\u2019ll learn about the Python dataclass decorator and how to use it effectively. Introduction to the Python dataclass Python introduced the dataclass in version 3.7 (PEP 557). The dataclass allows you to define\u00a0classes\u00a0with less code and more functionality out of the box. The following defines a regular\u00a0Person\u00a0class with two instance attributes\u00a0name\u00a0and\u00a0age: […]<\/p>\n","protected":false},"author":1,"featured_media":0,"comment_status":"open","ping_status":"open","sticky":false,"template":"","format":"standard","meta":{"footnotes":""},"categories":[32],"tags":[],"class_list":["post-220","post","type-post","status-publish","format-standard","hentry","category-8-metaprogramming-exceptions"],"_links":{"self":[{"href":"https:\/\/learnpython.elegantwallp.com\/wp-json\/wp\/v2\/posts\/220","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/learnpython.elegantwallp.com\/wp-json\/wp\/v2\/posts"}],"about":[{"href":"https:\/\/learnpython.elegantwallp.com\/wp-json\/wp\/v2\/types\/post"}],"author":[{"embeddable":true,"href":"https:\/\/learnpython.elegantwallp.com\/wp-json\/wp\/v2\/users\/1"}],"replies":[{"embeddable":true,"href":"https:\/\/learnpython.elegantwallp.com\/wp-json\/wp\/v2\/comments?post=220"}],"version-history":[{"count":1,"href":"https:\/\/learnpython.elegantwallp.com\/wp-json\/wp\/v2\/posts\/220\/revisions"}],"predecessor-version":[{"id":221,"href":"https:\/\/learnpython.elegantwallp.com\/wp-json\/wp\/v2\/posts\/220\/revisions\/221"}],"wp:attachment":[{"href":"https:\/\/learnpython.elegantwallp.com\/wp-json\/wp\/v2\/media?parent=220"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/learnpython.elegantwallp.com\/wp-json\/wp\/v2\/categories?post=220"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/learnpython.elegantwallp.com\/wp-json\/wp\/v2\/tags?post=220"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}