Python dataclass validation

By Thomas Taylor | | 1 minutes
python

Creating dataclasses in Python is simplistic; however, what if additional validation needs to be completed during initialization?

Creating a dataclass

The following example has a class named Person that models information about an individual:

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from dataclasses import dataclass

@dataclass
class Person:
    first_name: str
    last_name: str
    age: int

This class can be instantiated in several ways:

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john = Person(first_name="john", last_name="doe", age=35)
sally = Person(first_name="sally", last_name="may", age=-20)
zachary = Person(first_name="zachary", last_name="taylor", age=12.5)
print(john) # Person(first_name='john', last_name='doe', age=35)
print(sally) # Person(first_name='sally', last_name='may', age=-20)
print(zachary) # Person(first_name='zachary', last_name='taylor', age=12.5)

How to validate inputs for dataclasses

In the previous example, sally’s age was a non-positive integer and zachary’s age was a float value. To resolve erroneous input, a __post_init__ method can be used:

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from dataclasses import dataclass

@dataclass
class Person:
    first_name: str
    last_name: str
    age: int

    def __post_init__(self):
        if not isinstance(self.age, int):
            raise ValueError("age is not an int")
        if self.age <= 0:
            raise ValueError("age must be a positive integer greater than 0")

sally’s error:

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ValueError: age must be a positive integer greater than 0

zachary’s error:

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ValueError: age is not an int