How to Setup Data Classes in Python

In this article, you will learn how to Setup Data Classes in Python.

Let's start with the definition of the Data Classes in Python.

What is Data Classes in Python?

In Python, data classes are a feature introduced in Python 3.7 that allow you to define simple classes for storing data with minimal boilerplate. They are similar to regular classes, but with some added functionality to make them more convenient for storing data.

Data classes use type hints and the @dataclass decorator to automatically generate default implementations of the __init__ and __repr__ methods. They also provide support for default values, the field() function to define default value, types and some more properties like init, repr, compare, hash etc. and the asdict() function to convert data class instance to dictionary.

Here is an example of a simple data class for storing information about a person:

from dataclasses import dataclass

@dataclassclass Person:
    name: str
    age: int
    gender: str

You can then create instances of the class and access their properties as usual:

p = Person("John", 30, "Male")
print(p.name) # prints "John"

Data classes are particularly useful when you need to create simple classes for storing data, such as the fields of a database record or the attributes of an API response. They make it easy to define these classes with minimal boilerplate and support for default values, type hints, and other useful features.

Setting up Data Class in Python

To set up data classes in Python, you will need to do the following:

STEP 1: Import the dataclasses module by adding the line from dataclasses import dataclass at the top of your Python file.

STEP 2: Define a class and decorate it with @dataclass. This will tell Python that this class is a data class.

STEP 3: Define class variables and their types as usual. You can use type hints to specify the type of each variable.

Here is an example of a simple data class for storing information about a person:

from dataclasses import dataclass

@dataclassclass Person:
    name: str
    age: int
    gender: str

STEP 4: Once the data class is defined, you can create instances of the class and access their properties as usual.

p = Person("John", 30, "Male")
print(p.name) # prints "John"

STEP 5: You can also add default values to the class variables

@dataclassclass Person:
    name: str
    age: int = None
    gender: str = None

STEP 6: You can also use field() to define default value, types and some more properties like init, repr, compare, hash etc.

from dataclasses import field

@dataclassclass Person:
    name: str
    age: int = field(default=None, compare=False)
    gender: str = field(default=None, compare=False)

STEP 7: You can also use asdict() to convert data class instance to dictionary

from dataclasses import asdict

person = Person('John', 30, 'Male')
person_dict = asdict(person)
print(person_dict)

Output

 {'name': 'John', 'age': 30, 'gender': 'Male'}

Conclusion

In summary, data classes make it easy to define simple classes for storing data with minimal boilerplate. They also provide support for default values, type hints, and other useful features.

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