Dicts and Mapping Types¶
dict
dict(v)
is used to attempt to convert a dictionary; seetyping.Dict
below for sub-type constraints
from pydantic import BaseModel, ValidationError
class Model(BaseModel):
x: dict
m = Model(x={'foo': 1})
print(m.model_dump())
#> {'x': {'foo': 1}}
try:
Model(x='test')
except ValidationError as e:
print(e)
"""
1 validation error for Model
x
Input should be a valid dictionary [type=dict_type, input_value='test', input_type=str]
"""
typing.Dict
from typing import Dict
from pydantic import BaseModel, ValidationError
class Model(BaseModel):
x: Dict[str, int]
m = Model(x={'foo': 1})
print(m.model_dump())
#> {'x': {'foo': 1}}
try:
Model(x={'foo': '1'})
except ValidationError as e:
print(e)
"""
1 validation error for Model
x
Input should be a valid dictionary [type=dict_type, input_value='test', input_type=str]
"""
TypedDict¶
Note
This is a new feature of the Python standard library as of Python 3.8. Prior to Python 3.8, it requires the typing-extensions package. But required and optional fields are properly differentiated only since Python 3.9. We therefore recommend using typing-extensions with Python 3.8 as well.
TypedDict declares a dictionary type that expects all of its instances to have a certain set of keys, where each key is associated with a value of a consistent type.
It is same as dict
but Pydantic will validate the dictionary since keys are annotated.
from typing_extensions import TypedDict
from pydantic import TypeAdapter, ValidationError
class User(TypedDict):
name: str
id: int
ta = TypeAdapter(User)
print(ta.validate_python({'name': 'foo', 'id': 1}))
#> {'name': 'foo', 'id': 1}
try:
ta.validate_python({'name': 'foo'})
except ValidationError as e:
print(e)
"""
1 validation error for typed-dict
id
Field required [type=missing, input_value={'name': 'foo'}, input_type=dict]
"""
You can define __pydantic_config__
to change the model inherited from TypedDict
.
See Model Config for more details.
from typing import Optional
from typing_extensions import TypedDict
from pydantic import ConfigDict, TypeAdapter, ValidationError
# `total=False` means keys are non-required
class UserIdentity(TypedDict, total=False):
name: Optional[str]
surname: str
class User(TypedDict):
__pydantic_config__ = ConfigDict(extra='forbid')
identity: UserIdentity
age: int
ta = TypeAdapter(User)
print(
ta.validate_python(
{'identity': {'name': 'Smith', 'surname': 'John'}, 'age': 37}
)
)
#> {'identity': {'name': 'Smith', 'surname': 'John'}, 'age': 37}
print(
ta.validate_python(
{'identity': {'name': None, 'surname': 'John'}, 'age': 37}
)
)
#> {'identity': {'name': None, 'surname': 'John'}, 'age': 37}
print(ta.validate_python({'identity': {}, 'age': 37}))
#> {'identity': {}, 'age': 37}
try:
ta.validate_python(
{'identity': {'name': ['Smith'], 'surname': 'John'}, 'age': 24}
)
except ValidationError as e:
print(e)
"""
1 validation error for typed-dict
identity.name
Input should be a valid string [type=string_type, input_value=['Smith'], input_type=list]
"""
try:
ta.validate_python(
{
'identity': {'name': 'Smith', 'surname': 'John'},
'age': '37',
'email': '[email protected]',
}
)
except ValidationError as e:
print(e)
"""
1 validation error for typed-dict
email
Extra inputs are not permitted [type=extra_forbidden, input_value='[email protected]', input_type=str]
"""