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 theField
- must be a
str
- must be a
validation_alias
on theField
- can be an instance of
str
,AliasPath
, orAliasChoices
- can be an instance of
serialization_alias
on theField
- must be a
str
- must be a
alias_generator
on theConfig
- can be a callable or an instance of
AliasGenerator
- can be a callable or an instance of
For examples of how to use alias
, validation_alias
, and serialization_alias
, see Field aliases.
AliasPath
and AliasChoices
¶
API Documentation
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'
-
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'
- We are using the second alias choice for both fields.
- 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 doin't
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`][pydantic.alias_generators.to_pascal]
* [`to_camel`][pydantic.alias_generators.to_camel]
* [`to_snake`][pydantic.alias_generators.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
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.