This project is deprecated since pydantic v2 now supports computed fields and will no longer be maintained.
A new decorator for pydantic allowing you to define dynamic fields that are computed from other properties.
Install the package by running
pip install pydantic_computed
from pydantic import BaseModel
from pydantic_computed import Computed, computed
class ComputedModelInt(BaseModel):
a: int
b: int
c: Computed[int]
@computed('c')
def calculate_c(a: int, b: int, **kwargs):
return a + b
model = ComputedModelInt(a=1, b=2)
print(model.c) # Outputs 3
from pydantic import BaseModel
from pydantic_computed import Computed, computed
class MultipleComputed(BaseModel):
a: int
b: int
c: Computed[int]
d: Computed[int]
e: Computed[int]
@computed('c')
def calc_c(a: int, b: int, **kwargs):
return a + b
@computed('d')
def calc_d(c: int, **kwargs): # Note that property d uses the value of the computed property c (The order of declaration matters!)
return c * 2
model = MultipleComputed(a=1, b=2)
print(model.c) # Outputs 3
print(model.d) # Outputs 6
Since all properties are passed as **kwargs to calculate_c, we can use the property names for the parameters
Suppose you set up a FastAPI application where you have users and orders stored in a database. All Models in the database have an automatically generated id. Now you want to be able to dynamically generate links to those objects. E.g. the user with id=3 is accessible on the endpoint http://my-api/users/3 Instead of storing those links in the database you can simply generate them with the computed decorator. example:
from pydantic import BaseModel, Field
from pydantic_computed import Computed, computed
class Link(BaseModel):
href: str
method: str
class SchemaLinked(BaseModel):
id: int
base_url: str
link: Computed[Link]
@computed('link')
def compute_link( id: int, base_url: str, **kwargs):
return Link(href=f'{base_url}/{id}', method='GET')
class User(SchemaLinked):
base_url: str = Field('/users', exclude=True)
username: str
class Order(SchemaLinked):
base_url: str = Field('/orders', exclude=True)
user: User
user = User(id=3, username='exampleuser')
user.json()
"""
{
id: 3,
username: "exampleuser",
link: {
href: "/users/3",
method: "GET"
}
}
"""
order = Order(id=2, user=user)
order.json()
"""
{
id: 2,
link: {
href: "/orders/2",
method: "GET"
},
user: {
id: 3,
username: "exampleuser",
link: {
href: "/users/3",
method: "GET"
}
}
}
"""
from pydantic import BaseModel
from pydantic_computed import computed, Computed
import math
class Point(BaseModel):
x: int
y: int
class Vector(BaseModel):
p1: Point
p2: Point
x: Computed[float]
y: Computed[float]
weight: Computed[float]
@computed('x')
def compute_x(p1: Point, p2: Point, **kwargs):
return p2.x - p1.x
@computed('y')
def compute_y(p1: Point, p2: Point, **kwargs):
return p2.y - p1.y
@computed('weight')
def compute_weight(x: float, y: float, **kwargs):
return math.sqrt(x ** 2 + y ** 2)
v1 = Vector(p1=Point(x=0,y=0), p2=Point(x=1,y=0))
print(v1.weight) # Outputs 1.0
v1.p2 = Point(x=2,y=0)
print(v1.weight) # Outputs now 2.0 since p2 changed
# NOTE: if we would have written v1.p2.x = 2 instead of v1.p2 = Point(x=2, y=0), it would not have worked, because of the way pydantic triggers validations
# The computed field only gets updated if one of the fields in the same model changes (in this case it is property p1 of Vector)