Pydantic is a library in Python that provides a way to validate and parse data using Python type annotations. It is commonly used in data validation and serialization tasks, especially in web development frameworks such as FastAPI.
In Pydantic, fields can be defined as required or not required. By default, all fields are assumed to be required. However, it is possible to specify a field as not required by using the Optional type. The Optional type is provided by the typing module and can be imported as follows:
from typing import Optional
To define a field as not required, you can use the Optional type as a Union with the desired field type. For example, consider a user model with a name field that is not required:
from pydantic import BaseModel
from typing import Optional
class User(BaseModel):
name: Optional[str]
In the above example, the name field is declared as Optional[str], indicating that it is not required. This means that when creating an instance of the User model, the name field can be omitted or set to None.
Here is an example of creating a User instance without providing a name:
user = User()
In the above example, the User instance is created without specifying the name field. The value of the name field will be None.
Alternatively, you can explicitly set the name field to None:
user = User(name=None)
In this case, the value of the name field is explicitly set to None.