Pydantic: Transform a value before it is assigned to a field?

Question

I have the following model

class Window(BaseModel):
    size: tuple[int, int]

and I would like to instantiate it like this:

fields = {'size': '1920x1080'}
window = Window(**fields)

Of course this fails since the value of 'size' is not of the correct type. However, I would like to add logic so that the value is split at x, i.e.:

def transform(raw: str) -> tuple[int, int]:
    x, y = raw.split('x')
    return int(x), int(y)

Does Pydantic support this?

Answer 1

Pydantic 2.x (edit)

Pydantic 2.0 introduced the field_validator decorator which lets you implement such a behaviour in a very simple way. Given the original parsing function:

from pydantic import BaseModel, field_validator

class Window(BaseModel):
    size: tuple[int, int]

    @field_validator("size", mode="before")
    @classmethod
    def transform(cls, raw: str) -> tuple[int, int]:
        x, y = raw.split("x")
        return int(x), int(y)

Note:

• The validator method is a class method, as denoted by the cls first argument. Implementing it as an instance method (with self) will raise an error.
• The mode="before" in the decorator is critical here, as expected this is what makes the method run before checking "size" is a tuple.

---

Pydantic 1.x (original answer)

You can implement such a behaviour with pydantic's validator. Given your predefined function:

def transform(raw: str) -> tuple[int, int]:
    x, y = raw.split('x')
    return int(x), int(y)

You can implement it in your class like this:

from pydantic import BaseModel, validator


class Window(BaseModel):
    
    size: tuple[int, int]
    _extract_size = validator('size', pre=True, allow_reuse=True)(transform)

Note the pre=True argument passed to the validator. It means that it will be run before the default validator that checks if size is a tuple.

---

Now:

fields = {'size': '1920x1080'}
window = Window(**fields)
print(window)
# output: size=(1920, 1080)

Note that after that, you won't be able to instantiate your Window with a tuple for size.

fields2 = {'size': (800, 600)}
window2 = Window(**fields2)
# AttributeError: 'tuple' object has no attribute 'split'

In order to overcome that, you could simply bypass the function if a tuple is passed by altering slightly your code:

Pydantic 2.x

class Window(BaseModel):
    size: tuple[int, int]

    @field_validator("size", mode="before")
    def transform(cls, raw: str | tuple[int, int]) -> tuple[int, int]:
        if isinstance(raw, tuple):
            return raw
        x, y = raw.split("x")
        return int(x), int(y)

Pydantic 1.x

def transform(raw: str | tuple[int, int]) -> tuple[int, int]:
    if isinstance(raw, tuple):
        return raw
    x, y = raw.split('x')
    return int(x), int(y)

class Window(BaseModel):

    size: tuple[int, int]
    _extract_size = validator('size', pre=True, allow_reuse=True)(transform)

Which should give:

fields2 = {'size': (800, 600)}
window2 = Window(**fields2)
print(window2)
# output: size:(800, 600)

Answer 2

There is another option if you would like to keep the transform/validation logic more modular or separated from the class itself.

from pydantic import BaseModel, AfterValidator
from typing_extensions import Annotated

def transform(raw: str) -> tuple[int, int]:
    x, y = raw.split('x')
    return int(x), int(y)

WindowSize = Annotated[str, AfterValidator(transform)]

class Window(BaseModel):
    size: WindowSize

fields = {'size': '1920x1080'}
window = Window(**fields)

print(window.size)  # (1920, 1080)