Python dataclass validation
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:
1from dataclasses import dataclass
2
3@dataclass
4class Person:
5 first_name: str
6 last_name: str
7 age: intThis class can be instantiated in several ways:
1john = Person(first_name="john", last_name="doe", age=35)
2sally = Person(first_name="sally", last_name="may", age=-20)
3zachary = Person(first_name="zachary", last_name="taylor", age=12.5)
4print(john) # Person(first_name='john', last_name='doe', age=35)
5print(sally) # Person(first_name='sally', last_name='may', age=-20)
6print(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:
1from dataclasses import dataclass
2
3@dataclass
4class Person:
5 first_name: str
6 last_name: str
7 age: int
8
9 def __post_init__(self):
10 if not isinstance(self.age, int):
11 raise ValueError("age is not an int")
12 if self.age <= 0:
13 raise ValueError("age must be a positive integer greater than 0")sally’s error:
1ValueError: age must be a positive integer greater than 0zachary’s error:
1ValueError: age is not an int