parse_obj

Learn dict-to-model with Model.parse_obj.

model_validate

In Pydantic v2, model_validate turns a dict into a model. It is the recommended replacement for the old parse_obj. It builds a model instance from a dict.

from pydantic import BaseModel

class User(BaseModel):
    name: str
    age: int

data = {"name": "Ayşe", "age": 30}
u = User.model_validate(data)
print(u.name)  # Ayşe

This method is ideal for building a model from structured data (e.g. a structured-data format). Bad data raises a validation error.

Validation and errors

model_validate validates the data and turns it into a model. If a required field is missing or a type does not match, ValidationError is raised. The error is detailed; it tells which field failed and why.

try:
    u = User.model_validate({"name": "Ayşe"})  # age missing
except ValidationError as e:
    print(e)

For this reason, using try/except when converting data from an untrusted source is a good practice.

Exercise Build a User model from a dict

Start with from pydantic import BaseModel. Define class User(BaseModel): with fields name: str and age: int. Define data = {"name": "Ayşe", "age": 30}. Build the model with u = User.model_validate(data). Print the values with print(u.name, u.age).

Show example solution

from pydantic import BaseModel

class User(BaseModel):
    name: str
    age: int

data = {"name": "Ayşe", "age": 30}
u = User.model_validate(data)
print(u.name, u.age)

Test yourself

Complete the model_validate call

data = {"name": "Ayşe", "age": 30}
u = User.____(data)

Show answer

data = {"name": "Ayşe", "age": 30}
u = User.model_validate(data)

What does User.model_validate(data) return?
- A dict
- A User instance
- A string
- A list
Show answer

A User instance — model_validate returns a User instance.
Match the model_validate concepts

model_validate

Turns dict into model
ValidationError

Is a validation error
data

Is the input dict
User instance

Is the output

Next lesson: Summary - Pydantic

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