Alias

An alias is an alternative name for a field, used when serializing and deserializing data.

You can specify an alias in the following ways:

• alias on the Field
  • must be a str
• validation_alias on the Field
  • can be an instance of str, AliasPath, or AliasChoices
• serialization_alias on the Field
  • must be a str
• alias_generator on the Config
  • can be a callable or an instance of AliasGenerator

For examples of how to use alias, validation_alias, and serialization_alias, see Field aliases.

AliasPath and AliasChoices

API Documentation

pydantic.aliases.AliasPath
pydantic.aliases.AliasChoices

Pydantic provides two special types for convenience when using validation_alias: AliasPath and AliasChoices.

The AliasPath is used to specify a path to a field using aliases. For example:

from pydantic import BaseModel, Field, AliasPath


class User(BaseModel):
    first_name: str = Field(validation_alias=AliasPath('names', 0))
    last_name: str = Field(validation_alias=AliasPath('names', 1))

user = User.model_validate({'names': ['John', 'Doe']})  # (1)!
print(user)
#> first_name='John' last_name='Doe'

1. We are using model_validate to validate a dictionary using the field aliases.

   You can see more details about model_validate in the API reference.

In the 'first_name' field, we are using the alias 'names' and the index 0 to specify the path to the first name. In the 'last_name' field, we are using the alias 'names' and the index 1 to specify the path to the last name.

AliasChoices is used to specify a choice of aliases. For example:

from pydantic import BaseModel, Field, AliasChoices


class User(BaseModel):
    first_name: str = Field(validation_alias=AliasChoices('first_name', 'fname'))
    last_name: str = Field(validation_alias=AliasChoices('last_name', 'lname'))

user = User.model_validate({'fname': 'John', 'lname': 'Doe'})  # (1)!
print(user)
#> first_name='John' last_name='Doe'
user = User.model_validate({'first_name': 'John', 'lname': 'Doe'})  # (2)!
print(user)
#> first_name='John' last_name='Doe'

1. We are using the second alias choice for both fields.
2. We are using the first alias choice for the field 'first_name' and the second alias choice for the field 'last_name'.

You can also use AliasChoices with AliasPath:

from pydantic import BaseModel, Field, AliasPath, AliasChoices


class User(BaseModel):
    first_name: str = Field(validation_alias=AliasChoices('first_name', AliasPath('names', 0)))
    last_name: str = Field(validation_alias=AliasChoices('last_name', AliasPath('names', 1)))


user = User.model_validate({'first_name': 'John', 'last_name': 'Doe'})
print(user)
#> first_name='John' last_name='Doe'
user = User.model_validate({'names': ['John', 'Doe']})
print(user)
#> first_name='John' last_name='Doe'
user = User.model_validate({'names': ['John'], 'last_name': 'Doe'})
print(user)
#> first_name='John' last_name='Doe'

Using alias generators

You can use the alias_generator parameter of Config to specify a callable (or group of callables, via AliasGenerator) that will generate aliases for all fields in a model. This is useful if you want to use a consistent naming convention for all fields in a model, but do not want to specify the alias for each field individually.

Note

Pydantic offers three built-in alias generators that you can use out of the box:

to_pascal
to_camel
to_snake

Using a callable

Here's a basic example using a callable:

from pydantic import BaseModel, ConfigDict


class Tree(BaseModel):
    model_config = ConfigDict(
        alias_generator=lambda field_name: field_name.upper()
    )

    age: int
    height: float
    kind: str


t = Tree.model_validate({'AGE': 12, 'HEIGHT': 1.2, 'KIND': 'oak'})
print(t.model_dump(by_alias=True))
#> {'AGE': 12, 'HEIGHT': 1.2, 'KIND': 'oak'}

Using an AliasGenerator

API Documentation

pydantic.aliases.AliasGenerator

AliasGenerator is a class that allows you to specify multiple alias generators for a model. You can use an AliasGenerator to specify different alias generators for validation and serialization.

This is particularly useful if you need to use different naming conventions for loading and saving data, but you don't want to specify the validation and serialization aliases for each field individually.

For example:

from pydantic import AliasGenerator, BaseModel, ConfigDict


class Tree(BaseModel):
    model_config = ConfigDict(
        alias_generator=AliasGenerator(
            validation_alias=lambda field_name: field_name.upper(),
            serialization_alias=lambda field_name: field_name.title(),
        )
    )

    age: int
    height: float
    kind: str


t = Tree.model_validate({'AGE': 12, 'HEIGHT': 1.2, 'KIND': 'oak'})
print(t.model_dump(by_alias=True))
#> {'Age': 12, 'Height': 1.2, 'Kind': 'oak'}

Alias Precedence

If you specify an alias on the Field, it will take precedence over the generated alias by default:

from pydantic import BaseModel, ConfigDict, Field


def to_camel(string: str) -> str:
    return ''.join(word.capitalize() for word in string.split('_'))


class Voice(BaseModel):
    model_config = ConfigDict(alias_generator=to_camel)

    name: str
    language_code: str = Field(alias='lang')


voice = Voice(Name='Filiz', lang='tr-TR')
print(voice.language_code)
#> tr-TR
print(voice.model_dump(by_alias=True))
#> {'Name': 'Filiz', 'lang': 'tr-TR'}

Alias Priority

You may set alias_priority on a field to change this behavior:

• alias_priority=2 the alias will not be overridden by the alias generator.
• alias_priority=1 the alias will be overridden by the alias generator.
• alias_priority not set:
  • alias is set: the alias will not be overridden by the alias generator.
  • alias is not set: the alias will be overridden by the alias generator.

The same precedence applies to validation_alias and serialization_alias. See more about the different field aliases under field aliases.