pydantic_core.core_schema
This module contains definitions to build schemas which pydantic_core
can
validate and serialize.
WhenUsed
module-attribute
¶
WhenUsed = Literal[
"always", "unless-none", "json", "json-unless-none"
]
Values have the following meanings:
'always'
means always use'unless-none'
means use unless the value isNone
'json'
means use when serializing to JSON'json-unless-none'
means use when serializing to JSON and the value is notNone
CoreConfig ¶
Bases: TypedDict
Base class for schema configuration options.
Attributes:
Name | Type | Description |
---|---|---|
title |
str
|
The name of the configuration. |
strict |
bool
|
Whether the configuration should strictly adhere to specified rules. |
extra_fields_behavior |
ExtraBehavior
|
The behavior for handling extra fields. |
typed_dict_total |
bool
|
Whether the TypedDict should be considered total. Default is |
from_attributes |
bool
|
Whether to use attributes for models, dataclasses, and tagged union keys. |
loc_by_alias |
bool
|
Whether to use the used alias (or first alias for "field required" errors) instead of
|
revalidate_instances |
Literal['always', 'never', 'subclass-instances']
|
Whether instances of models and dataclasses should re-validate. Default is 'never'. |
validate_default |
bool
|
Whether to validate default values during validation. Default is |
populate_by_name |
bool
|
Whether an aliased field may be populated by its name as given by the model attribute,
as well as the alias. (Replaces 'allow_population_by_field_name' in Pydantic v1.) Default is |
str_max_length |
int
|
The maximum length for string fields. |
str_min_length |
int
|
The minimum length for string fields. |
str_strip_whitespace |
bool
|
Whether to strip whitespace from string fields. |
str_to_lower |
bool
|
Whether to convert string fields to lowercase. |
str_to_upper |
bool
|
Whether to convert string fields to uppercase. |
allow_inf_nan |
bool
|
Whether to allow infinity and NaN values for float fields. Default is |
ser_json_timedelta |
Literal['iso8601', 'float']
|
The serialization option for |
ser_json_bytes |
Literal['utf8', 'base64', 'hex']
|
The serialization option for |
ser_json_inf_nan |
Literal['null', 'constants', 'strings']
|
The serialization option for infinity and NaN values in float fields. Default is 'null'. |
val_json_bytes |
Literal['utf8', 'base64', 'hex']
|
The validation option for |
hide_input_in_errors |
bool
|
Whether to hide input data from |
validation_error_cause |
bool
|
Whether to add user-python excs to the cause of a ValidationError. Requires exceptiongroup backport pre Python 3.11. |
coerce_numbers_to_str |
bool
|
Whether to enable coercion of any |
regex_engine |
Literal['rust-regex', 'python-re']
|
The regex engine to use for regex pattern validation. Default is 'rust-regex'. See |
cache_strings |
Union[bool, Literal['all', 'keys', 'none']]
|
Whether to cache strings. Default is |
SerializationInfo ¶
simple_ser_schema ¶
simple_ser_schema(
type: ExpectedSerializationTypes,
) -> SimpleSerSchema
Returns a schema for serialization with a custom type.
Parameters:
Name | Type | Description | Default |
---|---|---|---|
type |
ExpectedSerializationTypes
|
The type to use for serialization |
required |
Source code in .venv/lib/python3.10/site-packages/pydantic_core/core_schema.py
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|
plain_serializer_function_ser_schema ¶
plain_serializer_function_ser_schema(
function: SerializerFunction,
*,
is_field_serializer: bool | None = None,
info_arg: bool | None = None,
return_schema: CoreSchema | None = None,
when_used: WhenUsed = "always"
) -> PlainSerializerFunctionSerSchema
Returns a schema for serialization with a function, can be either a "general" or "field" function.
Parameters:
Name | Type | Description | Default |
---|---|---|---|
function |
SerializerFunction
|
The function to use for serialization |
required |
is_field_serializer |
bool | None
|
Whether the serializer is for a field, e.g. takes |
None
|
info_arg |
bool | None
|
Whether the function takes an |
None
|
return_schema |
CoreSchema | None
|
Schema to use for serializing return value |
None
|
when_used |
WhenUsed
|
When the function should be called |
'always'
|
Source code in .venv/lib/python3.10/site-packages/pydantic_core/core_schema.py
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wrap_serializer_function_ser_schema ¶
wrap_serializer_function_ser_schema(
function: WrapSerializerFunction,
*,
is_field_serializer: bool | None = None,
info_arg: bool | None = None,
schema: CoreSchema | None = None,
return_schema: CoreSchema | None = None,
when_used: WhenUsed = "always"
) -> WrapSerializerFunctionSerSchema
Returns a schema for serialization with a wrap function, can be either a "general" or "field" function.
Parameters:
Name | Type | Description | Default |
---|---|---|---|
function |
WrapSerializerFunction
|
The function to use for serialization |
required |
is_field_serializer |
bool | None
|
Whether the serializer is for a field, e.g. takes |
None
|
info_arg |
bool | None
|
Whether the function takes an |
None
|
schema |
CoreSchema | None
|
The schema to use for the inner serialization |
None
|
return_schema |
CoreSchema | None
|
Schema to use for serializing return value |
None
|
when_used |
WhenUsed
|
When the function should be called |
'always'
|
Source code in .venv/lib/python3.10/site-packages/pydantic_core/core_schema.py
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format_ser_schema ¶
format_ser_schema(
formatting_string: str,
*,
when_used: WhenUsed = "json-unless-none"
) -> FormatSerSchema
Returns a schema for serialization using python's format
method.
Parameters:
Name | Type | Description | Default |
---|---|---|---|
formatting_string |
str
|
String defining the format to use |
required |
when_used |
WhenUsed
|
Same meaning as for [general_function_plain_ser_schema], but with a different default |
'json-unless-none'
|
Source code in .venv/lib/python3.10/site-packages/pydantic_core/core_schema.py
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|
to_string_ser_schema ¶
to_string_ser_schema(
*, when_used: WhenUsed = "json-unless-none"
) -> ToStringSerSchema
Returns a schema for serialization using python's str()
/ __str__
method.
Parameters:
Name | Type | Description | Default |
---|---|---|---|
when_used |
WhenUsed
|
Same meaning as for [general_function_plain_ser_schema], but with a different default |
'json-unless-none'
|
Source code in .venv/lib/python3.10/site-packages/pydantic_core/core_schema.py
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|
model_ser_schema ¶
Returns a schema for serialization using a model.
Parameters:
Name | Type | Description | Default |
---|---|---|---|
cls |
Type[Any]
|
The expected class type, used to generate warnings if the wrong type is passed |
required |
schema |
CoreSchema
|
Internal schema to use to serialize the model dict |
required |
Source code in .venv/lib/python3.10/site-packages/pydantic_core/core_schema.py
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computed_field ¶
computed_field(
property_name: str,
return_schema: CoreSchema,
*,
alias: str | None = None,
metadata: Dict[str, Any] | None = None
) -> ComputedField
ComputedFields are properties of a model or dataclass that are included in serialization.
Parameters:
Name | Type | Description | Default |
---|---|---|---|
property_name |
str
|
The name of the property on the model or dataclass |
required |
return_schema |
CoreSchema
|
The schema used for the type returned by the computed field |
required |
alias |
str | None
|
The name to use in the serialized output |
None
|
metadata |
Dict[str, Any] | None
|
Any other information you want to include with the schema, not used by pydantic-core |
None
|
Source code in .venv/lib/python3.10/site-packages/pydantic_core/core_schema.py
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any_schema ¶
any_schema(
*,
ref: str | None = None,
metadata: Dict[str, Any] | None = None,
serialization: SerSchema | None = None
) -> AnySchema
Returns a schema that matches any value, e.g.:
from pydantic_core import SchemaValidator, core_schema
schema = core_schema.any_schema()
v = SchemaValidator(schema)
assert v.validate_python(1) == 1
Parameters:
Name | Type | Description | Default |
---|---|---|---|
ref |
str | None
|
optional unique identifier of the schema, used to reference the schema in other places |
None
|
metadata |
Dict[str, Any] | None
|
Any other information you want to include with the schema, not used by pydantic-core |
None
|
serialization |
SerSchema | None
|
Custom serialization schema |
None
|
Source code in .venv/lib/python3.10/site-packages/pydantic_core/core_schema.py
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none_schema ¶
none_schema(
*,
ref: str | None = None,
metadata: Dict[str, Any] | None = None,
serialization: SerSchema | None = None
) -> NoneSchema
Returns a schema that matches a None value, e.g.:
from pydantic_core import SchemaValidator, core_schema
schema = core_schema.none_schema()
v = SchemaValidator(schema)
assert v.validate_python(None) is None
Parameters:
Name | Type | Description | Default |
---|---|---|---|
ref |
str | None
|
optional unique identifier of the schema, used to reference the schema in other places |
None
|
metadata |
Dict[str, Any] | None
|
Any other information you want to include with the schema, not used by pydantic-core |
None
|
serialization |
SerSchema | None
|
Custom serialization schema |
None
|
Source code in .venv/lib/python3.10/site-packages/pydantic_core/core_schema.py
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bool_schema ¶
bool_schema(
strict: bool | None = None,
ref: str | None = None,
metadata: Dict[str, Any] | None = None,
serialization: SerSchema | None = None,
) -> BoolSchema
Returns a schema that matches a bool value, e.g.:
from pydantic_core import SchemaValidator, core_schema
schema = core_schema.bool_schema()
v = SchemaValidator(schema)
assert v.validate_python('True') is True
Parameters:
Name | Type | Description | Default |
---|---|---|---|
strict |
bool | None
|
Whether the value should be a bool or a value that can be converted to a bool |
None
|
ref |
str | None
|
optional unique identifier of the schema, used to reference the schema in other places |
None
|
metadata |
Dict[str, Any] | None
|
Any other information you want to include with the schema, not used by pydantic-core |
None
|
serialization |
SerSchema | None
|
Custom serialization schema |
None
|
Source code in .venv/lib/python3.10/site-packages/pydantic_core/core_schema.py
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int_schema ¶
int_schema(
*,
multiple_of: int | None = None,
le: int | None = None,
ge: int | None = None,
lt: int | None = None,
gt: int | None = None,
strict: bool | None = None,
ref: str | None = None,
metadata: Dict[str, Any] | None = None,
serialization: SerSchema | None = None
) -> IntSchema
Returns a schema that matches a int value, e.g.:
from pydantic_core import SchemaValidator, core_schema
schema = core_schema.int_schema(multiple_of=2, le=6, ge=2)
v = SchemaValidator(schema)
assert v.validate_python('4') == 4
Parameters:
Name | Type | Description | Default |
---|---|---|---|
multiple_of |
int | None
|
The value must be a multiple of this number |
None
|
le |
int | None
|
The value must be less than or equal to this number |
None
|
ge |
int | None
|
The value must be greater than or equal to this number |
None
|
lt |
int | None
|
The value must be strictly less than this number |
None
|
gt |
int | None
|
The value must be strictly greater than this number |
None
|
strict |
bool | None
|
Whether the value should be a int or a value that can be converted to a int |
None
|
ref |
str | None
|
optional unique identifier of the schema, used to reference the schema in other places |
None
|
metadata |
Dict[str, Any] | None
|
Any other information you want to include with the schema, not used by pydantic-core |
None
|
serialization |
SerSchema | None
|
Custom serialization schema |
None
|
Source code in .venv/lib/python3.10/site-packages/pydantic_core/core_schema.py
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|
float_schema ¶
float_schema(
*,
allow_inf_nan: bool | None = None,
multiple_of: float | None = None,
le: float | None = None,
ge: float | None = None,
lt: float | None = None,
gt: float | None = None,
strict: bool | None = None,
ref: str | None = None,
metadata: Dict[str, Any] | None = None,
serialization: SerSchema | None = None
) -> FloatSchema
Returns a schema that matches a float value, e.g.:
from pydantic_core import SchemaValidator, core_schema
schema = core_schema.float_schema(le=0.8, ge=0.2)
v = SchemaValidator(schema)
assert v.validate_python('0.5') == 0.5
Parameters:
Name | Type | Description | Default |
---|---|---|---|
allow_inf_nan |
bool | None
|
Whether to allow inf and nan values |
None
|
multiple_of |
float | None
|
The value must be a multiple of this number |
None
|
le |
float | None
|
The value must be less than or equal to this number |
None
|
ge |
float | None
|
The value must be greater than or equal to this number |
None
|
lt |
float | None
|
The value must be strictly less than this number |
None
|
gt |
float | None
|
The value must be strictly greater than this number |
None
|
strict |
bool | None
|
Whether the value should be a float or a value that can be converted to a float |
None
|
ref |
str | None
|
optional unique identifier of the schema, used to reference the schema in other places |
None
|
metadata |
Dict[str, Any] | None
|
Any other information you want to include with the schema, not used by pydantic-core |
None
|
serialization |
SerSchema | None
|
Custom serialization schema |
None
|
Source code in .venv/lib/python3.10/site-packages/pydantic_core/core_schema.py
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|
decimal_schema ¶
decimal_schema(
*,
allow_inf_nan: bool = None,
multiple_of: Decimal | None = None,
le: Decimal | None = None,
ge: Decimal | None = None,
lt: Decimal | None = None,
gt: Decimal | None = None,
max_digits: int | None = None,
decimal_places: int | None = None,
strict: bool | None = None,
ref: str | None = None,
metadata: Dict[str, Any] | None = None,
serialization: SerSchema | None = None
) -> DecimalSchema
Returns a schema that matches a decimal value, e.g.:
from decimal import Decimal
from pydantic_core import SchemaValidator, core_schema
schema = core_schema.decimal_schema(le=0.8, ge=0.2)
v = SchemaValidator(schema)
assert v.validate_python('0.5') == Decimal('0.5')
Parameters:
Name | Type | Description | Default |
---|---|---|---|
allow_inf_nan |
bool
|
Whether to allow inf and nan values |
None
|
multiple_of |
Decimal | None
|
The value must be a multiple of this number |
None
|
le |
Decimal | None
|
The value must be less than or equal to this number |
None
|
ge |
Decimal | None
|
The value must be greater than or equal to this number |
None
|
lt |
Decimal | None
|
The value must be strictly less than this number |
None
|
gt |
Decimal | None
|
The value must be strictly greater than this number |
None
|
max_digits |
int | None
|
The maximum number of decimal digits allowed |
None
|
decimal_places |
int | None
|
The maximum number of decimal places allowed |
None
|
strict |
bool | None
|
Whether the value should be a float or a value that can be converted to a float |
None
|
ref |
str | None
|
optional unique identifier of the schema, used to reference the schema in other places |
None
|
metadata |
Dict[str, Any] | None
|
Any other information you want to include with the schema, not used by pydantic-core |
None
|
serialization |
SerSchema | None
|
Custom serialization schema |
None
|
Source code in .venv/lib/python3.10/site-packages/pydantic_core/core_schema.py
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|
complex_schema ¶
complex_schema(
*,
strict: bool | None = None,
ref: str | None = None,
metadata: Dict[str, Any] | None = None,
serialization: SerSchema | None = None
) -> ComplexSchema
Returns a schema that matches a complex value, e.g.:
from pydantic_core import SchemaValidator, core_schema
schema = core_schema.complex_schema()
v = SchemaValidator(schema)
assert v.validate_python('1+2j') == complex(1, 2)
assert v.validate_python(complex(1, 2)) == complex(1, 2)
Parameters:
Name | Type | Description | Default |
---|---|---|---|
strict |
bool | None
|
Whether the value should be a complex object instance or a value that can be converted to a complex object |
None
|
ref |
str | None
|
optional unique identifier of the schema, used to reference the schema in other places |
None
|
metadata |
Dict[str, Any] | None
|
Any other information you want to include with the schema, not used by pydantic-core |
None
|
serialization |
SerSchema | None
|
Custom serialization schema |
None
|
Source code in .venv/lib/python3.10/site-packages/pydantic_core/core_schema.py
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str_schema ¶
str_schema(
*,
pattern: str | Pattern[str] | None = None,
max_length: int | None = None,
min_length: int | None = None,
strip_whitespace: bool | None = None,
to_lower: bool | None = None,
to_upper: bool | None = None,
regex_engine: (
Literal["rust-regex", "python-re"] | None
) = None,
strict: bool | None = None,
coerce_numbers_to_str: bool | None = None,
ref: str | None = None,
metadata: Dict[str, Any] | None = None,
serialization: SerSchema | None = None
) -> StringSchema
Returns a schema that matches a string value, e.g.:
from pydantic_core import SchemaValidator, core_schema
schema = core_schema.str_schema(max_length=10, min_length=2)
v = SchemaValidator(schema)
assert v.validate_python('hello') == 'hello'
Parameters:
Name | Type | Description | Default |
---|---|---|---|
pattern |
str | Pattern[str] | None
|
A regex pattern that the value must match |
None
|
max_length |
int | None
|
The value must be at most this length |
None
|
min_length |
int | None
|
The value must be at least this length |
None
|
strip_whitespace |
bool | None
|
Whether to strip whitespace from the value |
None
|
to_lower |
bool | None
|
Whether to convert the value to lowercase |
None
|
to_upper |
bool | None
|
Whether to convert the value to uppercase |
None
|
regex_engine |
Literal['rust-regex', 'python-re'] | None
|
None
|
|
strict |
bool | None
|
Whether the value should be a string or a value that can be converted to a string |
None
|
coerce_numbers_to_str |
bool | None
|
Whether to enable coercion of any |
None
|
ref |
str | None
|
optional unique identifier of the schema, used to reference the schema in other places |
None
|
metadata |
Dict[str, Any] | None
|
Any other information you want to include with the schema, not used by pydantic-core |
None
|
serialization |
SerSchema | None
|
Custom serialization schema |
None
|
Source code in .venv/lib/python3.10/site-packages/pydantic_core/core_schema.py
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|
bytes_schema ¶
bytes_schema(
*,
max_length: int | None = None,
min_length: int | None = None,
strict: bool | None = None,
ref: str | None = None,
metadata: Dict[str, Any] | None = None,
serialization: SerSchema | None = None
) -> BytesSchema
Returns a schema that matches a bytes value, e.g.:
from pydantic_core import SchemaValidator, core_schema
schema = core_schema.bytes_schema(max_length=10, min_length=2)
v = SchemaValidator(schema)
assert v.validate_python(b'hello') == b'hello'
Parameters:
Name | Type | Description | Default |
---|---|---|---|
max_length |
int | None
|
The value must be at most this length |
None
|
min_length |
int | None
|
The value must be at least this length |
None
|
strict |
bool | None
|
Whether the value should be a bytes or a value that can be converted to a bytes |
None
|
ref |
str | None
|
optional unique identifier of the schema, used to reference the schema in other places |
None
|
metadata |
Dict[str, Any] | None
|
Any other information you want to include with the schema, not used by pydantic-core |
None
|
serialization |
SerSchema | None
|
Custom serialization schema |
None
|
Source code in .venv/lib/python3.10/site-packages/pydantic_core/core_schema.py
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|
date_schema ¶
date_schema(
*,
strict: bool | None = None,
le: date | None = None,
ge: date | None = None,
lt: date | None = None,
gt: date | None = None,
now_op: Literal["past", "future"] | None = None,
now_utc_offset: int | None = None,
ref: str | None = None,
metadata: Dict[str, Any] | None = None,
serialization: SerSchema | None = None
) -> DateSchema
Returns a schema that matches a date value, e.g.:
from datetime import date
from pydantic_core import SchemaValidator, core_schema
schema = core_schema.date_schema(le=date(2020, 1, 1), ge=date(2019, 1, 1))
v = SchemaValidator(schema)
assert v.validate_python(date(2019, 6, 1)) == date(2019, 6, 1)
Parameters:
Name | Type | Description | Default |
---|---|---|---|
strict |
bool | None
|
Whether the value should be a date or a value that can be converted to a date |
None
|
le |
date | None
|
The value must be less than or equal to this date |
None
|
ge |
date | None
|
The value must be greater than or equal to this date |
None
|
lt |
date | None
|
The value must be strictly less than this date |
None
|
gt |
date | None
|
The value must be strictly greater than this date |
None
|
now_op |
Literal['past', 'future'] | None
|
The value must be in the past or future relative to the current date |
None
|
now_utc_offset |
int | None
|
The value must be in the past or future relative to the current date with this utc offset |
None
|
ref |
str | None
|
optional unique identifier of the schema, used to reference the schema in other places |
None
|
metadata |
Dict[str, Any] | None
|
Any other information you want to include with the schema, not used by pydantic-core |
None
|
serialization |
SerSchema | None
|
Custom serialization schema |
None
|
Source code in .venv/lib/python3.10/site-packages/pydantic_core/core_schema.py
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|
time_schema ¶
time_schema(
*,
strict: bool | None = None,
le: time | None = None,
ge: time | None = None,
lt: time | None = None,
gt: time | None = None,
tz_constraint: (
Literal["aware", "naive"] | int | None
) = None,
microseconds_precision: Literal[
"truncate", "error"
] = "truncate",
ref: str | None = None,
metadata: Dict[str, Any] | None = None,
serialization: SerSchema | None = None
) -> TimeSchema
Returns a schema that matches a time value, e.g.:
from datetime import time
from pydantic_core import SchemaValidator, core_schema
schema = core_schema.time_schema(le=time(12, 0, 0), ge=time(6, 0, 0))
v = SchemaValidator(schema)
assert v.validate_python(time(9, 0, 0)) == time(9, 0, 0)
Parameters:
Name | Type | Description | Default |
---|---|---|---|
strict |
bool | None
|
Whether the value should be a time or a value that can be converted to a time |
None
|
le |
time | None
|
The value must be less than or equal to this time |
None
|
ge |
time | None
|
The value must be greater than or equal to this time |
None
|
lt |
time | None
|
The value must be strictly less than this time |
None
|
gt |
time | None
|
The value must be strictly greater than this time |
None
|
tz_constraint |
Literal['aware', 'naive'] | int | None
|
The value must be timezone aware or naive, or an int to indicate required tz offset |
None
|
microseconds_precision |
Literal['truncate', 'error']
|
The behavior when seconds have more than 6 digits or microseconds is too large |
'truncate'
|
ref |
str | None
|
optional unique identifier of the schema, used to reference the schema in other places |
None
|
metadata |
Dict[str, Any] | None
|
Any other information you want to include with the schema, not used by pydantic-core |
None
|
serialization |
SerSchema | None
|
Custom serialization schema |
None
|
Source code in .venv/lib/python3.10/site-packages/pydantic_core/core_schema.py
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|
datetime_schema ¶
datetime_schema(
*,
strict: bool | None = None,
le: datetime | None = None,
ge: datetime | None = None,
lt: datetime | None = None,
gt: datetime | None = None,
now_op: Literal["past", "future"] | None = None,
tz_constraint: (
Literal["aware", "naive"] | int | None
) = None,
now_utc_offset: int | None = None,
microseconds_precision: Literal[
"truncate", "error"
] = "truncate",
ref: str | None = None,
metadata: Dict[str, Any] | None = None,
serialization: SerSchema | None = None
) -> DatetimeSchema
Returns a schema that matches a datetime value, e.g.:
from datetime import datetime
from pydantic_core import SchemaValidator, core_schema
schema = core_schema.datetime_schema()
v = SchemaValidator(schema)
now = datetime.now()
assert v.validate_python(str(now)) == now
Parameters:
Name | Type | Description | Default |
---|---|---|---|
strict |
bool | None
|
Whether the value should be a datetime or a value that can be converted to a datetime |
None
|
le |
datetime | None
|
The value must be less than or equal to this datetime |
None
|
ge |
datetime | None
|
The value must be greater than or equal to this datetime |
None
|
lt |
datetime | None
|
The value must be strictly less than this datetime |
None
|
gt |
datetime | None
|
The value must be strictly greater than this datetime |
None
|
now_op |
Literal['past', 'future'] | None
|
The value must be in the past or future relative to the current datetime |
None
|
tz_constraint |
Literal['aware', 'naive'] | int | None
|
The value must be timezone aware or naive, or an int to indicate required tz offset TODO: use of a tzinfo where offset changes based on the datetime is not yet supported |
None
|
now_utc_offset |
int | None
|
The value must be in the past or future relative to the current datetime with this utc offset |
None
|
microseconds_precision |
Literal['truncate', 'error']
|
The behavior when seconds have more than 6 digits or microseconds is too large |
'truncate'
|
ref |
str | None
|
optional unique identifier of the schema, used to reference the schema in other places |
None
|
metadata |
Dict[str, Any] | None
|
Any other information you want to include with the schema, not used by pydantic-core |
None
|
serialization |
SerSchema | None
|
Custom serialization schema |
None
|
Source code in .venv/lib/python3.10/site-packages/pydantic_core/core_schema.py
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|
timedelta_schema ¶
timedelta_schema(
*,
strict: bool | None = None,
le: timedelta | None = None,
ge: timedelta | None = None,
lt: timedelta | None = None,
gt: timedelta | None = None,
microseconds_precision: Literal[
"truncate", "error"
] = "truncate",
ref: str | None = None,
metadata: Dict[str, Any] | None = None,
serialization: SerSchema | None = None
) -> TimedeltaSchema
Returns a schema that matches a timedelta value, e.g.:
from datetime import timedelta
from pydantic_core import SchemaValidator, core_schema
schema = core_schema.timedelta_schema(le=timedelta(days=1), ge=timedelta(days=0))
v = SchemaValidator(schema)
assert v.validate_python(timedelta(hours=12)) == timedelta(hours=12)
Parameters:
Name | Type | Description | Default |
---|---|---|---|
strict |
bool | None
|
Whether the value should be a timedelta or a value that can be converted to a timedelta |
None
|
le |
timedelta | None
|
The value must be less than or equal to this timedelta |
None
|
ge |
timedelta | None
|
The value must be greater than or equal to this timedelta |
None
|
lt |
timedelta | None
|
The value must be strictly less than this timedelta |
None
|
gt |
timedelta | None
|
The value must be strictly greater than this timedelta |
None
|
microseconds_precision |
Literal['truncate', 'error']
|
The behavior when seconds have more than 6 digits or microseconds is too large |
'truncate'
|
ref |
str | None
|
optional unique identifier of the schema, used to reference the schema in other places |
None
|
metadata |
Dict[str, Any] | None
|
Any other information you want to include with the schema, not used by pydantic-core |
None
|
serialization |
SerSchema | None
|
Custom serialization schema |
None
|
Source code in .venv/lib/python3.10/site-packages/pydantic_core/core_schema.py
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|
literal_schema ¶
literal_schema(
expected: list[Any],
*,
ref: str | None = None,
metadata: Dict[str, Any] | None = None,
serialization: SerSchema | None = None
) -> LiteralSchema
Returns a schema that matches a literal value, e.g.:
from pydantic_core import SchemaValidator, core_schema
schema = core_schema.literal_schema(['hello', 'world'])
v = SchemaValidator(schema)
assert v.validate_python('hello') == 'hello'
Parameters:
Name | Type | Description | Default |
---|---|---|---|
expected |
list[Any]
|
The value must be one of these values |
required |
ref |
str | None
|
optional unique identifier of the schema, used to reference the schema in other places |
None
|
metadata |
Dict[str, Any] | None
|
Any other information you want to include with the schema, not used by pydantic-core |
None
|
serialization |
SerSchema | None
|
Custom serialization schema |
None
|
Source code in .venv/lib/python3.10/site-packages/pydantic_core/core_schema.py
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|
enum_schema ¶
enum_schema(
cls: Any,
members: list[Any],
*,
sub_type: Literal["str", "int", "float"] | None = None,
missing: Callable[[Any], Any] | None = None,
strict: bool | None = None,
ref: str | None = None,
metadata: Dict[str, Any] | None = None,
serialization: SerSchema | None = None
) -> EnumSchema
Returns a schema that matches an enum value, e.g.:
from enum import Enum
from pydantic_core import SchemaValidator, core_schema
class Color(Enum):
RED = 1
GREEN = 2
BLUE = 3
schema = core_schema.enum_schema(Color, list(Color.__members__.values()))
v = SchemaValidator(schema)
assert v.validate_python(2) is Color.GREEN
Parameters:
Name | Type | Description | Default |
---|---|---|---|
cls |
Any
|
The enum class |
required |
members |
list[Any]
|
The members of the enum, generally |
required |
sub_type |
Literal['str', 'int', 'float'] | None
|
The type of the enum, either 'str' or 'int' or None for plain enums |
None
|
missing |
Callable[[Any], Any] | None
|
A function to use when the value is not found in the enum, from |
None
|
strict |
bool | None
|
Whether to use strict mode, defaults to False |
None
|
ref |
str | None
|
optional unique identifier of the schema, used to reference the schema in other places |
None
|
metadata |
Dict[str, Any] | None
|
Any other information you want to include with the schema, not used by pydantic-core |
None
|
serialization |
SerSchema | None
|
Custom serialization schema |
None
|
Source code in .venv/lib/python3.10/site-packages/pydantic_core/core_schema.py
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|
is_instance_schema ¶
is_instance_schema(
cls: Any,
*,
cls_repr: str | None = None,
ref: str | None = None,
metadata: Dict[str, Any] | None = None,
serialization: SerSchema | None = None
) -> IsInstanceSchema
Returns a schema that checks if a value is an instance of a class, equivalent to python's isinstance
method, e.g.:
from pydantic_core import SchemaValidator, core_schema
class A:
pass
schema = core_schema.is_instance_schema(cls=A)
v = SchemaValidator(schema)
v.validate_python(A())
Parameters:
Name | Type | Description | Default |
---|---|---|---|
cls |
Any
|
The value must be an instance of this class |
required |
cls_repr |
str | None
|
If provided this string is used in the validator name instead of |
None
|
ref |
str | None
|
optional unique identifier of the schema, used to reference the schema in other places |
None
|
metadata |
Dict[str, Any] | None
|
Any other information you want to include with the schema, not used by pydantic-core |
None
|
serialization |
SerSchema | None
|
Custom serialization schema |
None
|
Source code in .venv/lib/python3.10/site-packages/pydantic_core/core_schema.py
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|
is_subclass_schema ¶
is_subclass_schema(
cls: Type[Any],
*,
cls_repr: str | None = None,
ref: str | None = None,
metadata: Dict[str, Any] | None = None,
serialization: SerSchema | None = None
) -> IsInstanceSchema
Returns a schema that checks if a value is a subtype of a class, equivalent to python's issubclass
method, e.g.:
from pydantic_core import SchemaValidator, core_schema
class A:
pass
class B(A):
pass
schema = core_schema.is_subclass_schema(cls=A)
v = SchemaValidator(schema)
v.validate_python(B)
Parameters:
Name | Type | Description | Default |
---|---|---|---|
cls |
Type[Any]
|
The value must be a subclass of this class |
required |
cls_repr |
str | None
|
If provided this string is used in the validator name instead of |
None
|
ref |
str | None
|
optional unique identifier of the schema, used to reference the schema in other places |
None
|
metadata |
Dict[str, Any] | None
|
Any other information you want to include with the schema, not used by pydantic-core |
None
|
serialization |
SerSchema | None
|
Custom serialization schema |
None
|
Source code in .venv/lib/python3.10/site-packages/pydantic_core/core_schema.py
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|
callable_schema ¶
callable_schema(
*,
ref: str | None = None,
metadata: Dict[str, Any] | None = None,
serialization: SerSchema | None = None
) -> CallableSchema
Returns a schema that checks if a value is callable, equivalent to python's callable
method, e.g.:
from pydantic_core import SchemaValidator, core_schema
schema = core_schema.callable_schema()
v = SchemaValidator(schema)
v.validate_python(min)
Parameters:
Name | Type | Description | Default |
---|---|---|---|
ref |
str | None
|
optional unique identifier of the schema, used to reference the schema in other places |
None
|
metadata |
Dict[str, Any] | None
|
Any other information you want to include with the schema, not used by pydantic-core |
None
|
serialization |
SerSchema | None
|
Custom serialization schema |
None
|
Source code in .venv/lib/python3.10/site-packages/pydantic_core/core_schema.py
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|
list_schema ¶
list_schema(
items_schema: CoreSchema | None = None,
*,
min_length: int | None = None,
max_length: int | None = None,
fail_fast: bool | None = None,
strict: bool | None = None,
ref: str | None = None,
metadata: Dict[str, Any] | None = None,
serialization: IncExSeqOrElseSerSchema | None = None
) -> ListSchema
Returns a schema that matches a list value, e.g.:
from pydantic_core import SchemaValidator, core_schema
schema = core_schema.list_schema(core_schema.int_schema(), min_length=0, max_length=10)
v = SchemaValidator(schema)
assert v.validate_python(['4']) == [4]
Parameters:
Name | Type | Description | Default |
---|---|---|---|
items_schema |
CoreSchema | None
|
The value must be a list of items that match this schema |
None
|
min_length |
int | None
|
The value must be a list with at least this many items |
None
|
max_length |
int | None
|
The value must be a list with at most this many items |
None
|
fail_fast |
bool | None
|
Stop validation on the first error |
None
|
strict |
bool | None
|
The value must be a list with exactly this many items |
None
|
ref |
str | None
|
optional unique identifier of the schema, used to reference the schema in other places |
None
|
metadata |
Dict[str, Any] | None
|
Any other information you want to include with the schema, not used by pydantic-core |
None
|
serialization |
IncExSeqOrElseSerSchema | None
|
Custom serialization schema |
None
|
Source code in .venv/lib/python3.10/site-packages/pydantic_core/core_schema.py
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|
tuple_positional_schema ¶
tuple_positional_schema(
items_schema: list[CoreSchema],
*,
extras_schema: CoreSchema | None = None,
strict: bool | None = None,
ref: str | None = None,
metadata: Dict[str, Any] | None = None,
serialization: IncExSeqOrElseSerSchema | None = None
) -> TupleSchema
Returns a schema that matches a tuple of schemas, e.g.:
from pydantic_core import SchemaValidator, core_schema
schema = core_schema.tuple_positional_schema(
[core_schema.int_schema(), core_schema.str_schema()]
)
v = SchemaValidator(schema)
assert v.validate_python((1, 'hello')) == (1, 'hello')
Parameters:
Name | Type | Description | Default |
---|---|---|---|
items_schema |
list[CoreSchema]
|
The value must be a tuple with items that match these schemas |
required |
extras_schema |
CoreSchema | None
|
The value must be a tuple with items that match this schema
This was inspired by JSON schema's |
None
|
strict |
bool | None
|
The value must be a tuple with exactly this many items |
None
|
ref |
str | None
|
optional unique identifier of the schema, used to reference the schema in other places |
None
|
metadata |
Dict[str, Any] | None
|
Any other information you want to include with the schema, not used by pydantic-core |
None
|
serialization |
IncExSeqOrElseSerSchema | None
|
Custom serialization schema |
None
|
Source code in .venv/lib/python3.10/site-packages/pydantic_core/core_schema.py
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|
tuple_variable_schema ¶
tuple_variable_schema(
items_schema: CoreSchema | None = None,
*,
min_length: int | None = None,
max_length: int | None = None,
strict: bool | None = None,
ref: str | None = None,
metadata: Dict[str, Any] | None = None,
serialization: IncExSeqOrElseSerSchema | None = None
) -> TupleSchema
Returns a schema that matches a tuple of a given schema, e.g.:
from pydantic_core import SchemaValidator, core_schema
schema = core_schema.tuple_variable_schema(
items_schema=core_schema.int_schema(), min_length=0, max_length=10
)
v = SchemaValidator(schema)
assert v.validate_python(('1', 2, 3)) == (1, 2, 3)
Parameters:
Name | Type | Description | Default |
---|---|---|---|
items_schema |
CoreSchema | None
|
The value must be a tuple with items that match this schema |
None
|
min_length |
int | None
|
The value must be a tuple with at least this many items |
None
|
max_length |
int | None
|
The value must be a tuple with at most this many items |
None
|
strict |
bool | None
|
The value must be a tuple with exactly this many items |
None
|
ref |
str | None
|
Optional unique identifier of the schema, used to reference the schema in other places |
None
|
metadata |
Dict[str, Any] | None
|
Any other information you want to include with the schema, not used by pydantic-core |
None
|
serialization |
IncExSeqOrElseSerSchema | None
|
Custom serialization schema |
None
|
Source code in .venv/lib/python3.10/site-packages/pydantic_core/core_schema.py
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|
tuple_schema ¶
tuple_schema(
items_schema: list[CoreSchema],
*,
variadic_item_index: int | None = None,
min_length: int | None = None,
max_length: int | None = None,
fail_fast: bool | None = None,
strict: bool | None = None,
ref: str | None = None,
metadata: Dict[str, Any] | None = None,
serialization: IncExSeqOrElseSerSchema | None = None
) -> TupleSchema
Returns a schema that matches a tuple of schemas, with an optional variadic item, e.g.:
from pydantic_core import SchemaValidator, core_schema
schema = core_schema.tuple_schema(
[core_schema.int_schema(), core_schema.str_schema(), core_schema.float_schema()],
variadic_item_index=1,
)
v = SchemaValidator(schema)
assert v.validate_python((1, 'hello', 'world', 1.5)) == (1, 'hello', 'world', 1.5)
Parameters:
Name | Type | Description | Default |
---|---|---|---|
items_schema |
list[CoreSchema]
|
The value must be a tuple with items that match these schemas |
required |
variadic_item_index |
int | None
|
The index of the schema in |
None
|
min_length |
int | None
|
The value must be a tuple with at least this many items |
None
|
max_length |
int | None
|
The value must be a tuple with at most this many items |
None
|
fail_fast |
bool | None
|
Stop validation on the first error |
None
|
strict |
bool | None
|
The value must be a tuple with exactly this many items |
None
|
ref |
str | None
|
Optional unique identifier of the schema, used to reference the schema in other places |
None
|
metadata |
Dict[str, Any] | None
|
Any other information you want to include with the schema, not used by pydantic-core |
None
|
serialization |
IncExSeqOrElseSerSchema | None
|
Custom serialization schema |
None
|
Source code in .venv/lib/python3.10/site-packages/pydantic_core/core_schema.py
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|
set_schema ¶
set_schema(
items_schema: CoreSchema | None = None,
*,
min_length: int | None = None,
max_length: int | None = None,
fail_fast: bool | None = None,
strict: bool | None = None,
ref: str | None = None,
metadata: Dict[str, Any] | None = None,
serialization: SerSchema | None = None
) -> SetSchema
Returns a schema that matches a set of a given schema, e.g.:
from pydantic_core import SchemaValidator, core_schema
schema = core_schema.set_schema(
items_schema=core_schema.int_schema(), min_length=0, max_length=10
)
v = SchemaValidator(schema)
assert v.validate_python({1, '2', 3}) == {1, 2, 3}
Parameters:
Name | Type | Description | Default |
---|---|---|---|
items_schema |
CoreSchema | None
|
The value must be a set with items that match this schema |
None
|
min_length |
int | None
|
The value must be a set with at least this many items |
None
|
max_length |
int | None
|
The value must be a set with at most this many items |
None
|
fail_fast |
bool | None
|
Stop validation on the first error |
None
|
strict |
bool | None
|
The value must be a set with exactly this many items |
None
|
ref |
str | None
|
optional unique identifier of the schema, used to reference the schema in other places |
None
|
metadata |
Dict[str, Any] | None
|
Any other information you want to include with the schema, not used by pydantic-core |
None
|
serialization |
SerSchema | None
|
Custom serialization schema |
None
|
Source code in .venv/lib/python3.10/site-packages/pydantic_core/core_schema.py
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|
frozenset_schema ¶
frozenset_schema(
items_schema: CoreSchema | None = None,
*,
min_length: int | None = None,
max_length: int | None = None,
fail_fast: bool | None = None,
strict: bool | None = None,
ref: str | None = None,
metadata: Dict[str, Any] | None = None,
serialization: SerSchema | None = None
) -> FrozenSetSchema
Returns a schema that matches a frozenset of a given schema, e.g.:
from pydantic_core import SchemaValidator, core_schema
schema = core_schema.frozenset_schema(
items_schema=core_schema.int_schema(), min_length=0, max_length=10
)
v = SchemaValidator(schema)
assert v.validate_python(frozenset(range(3))) == frozenset({0, 1, 2})
Parameters:
Name | Type | Description | Default |
---|---|---|---|
items_schema |
CoreSchema | None
|
The value must be a frozenset with items that match this schema |
None
|
min_length |
int | None
|
The value must be a frozenset with at least this many items |
None
|
max_length |
int | None
|
The value must be a frozenset with at most this many items |
None
|
fail_fast |
bool | None
|
Stop validation on the first error |
None
|
strict |
bool | None
|
The value must be a frozenset with exactly this many items |
None
|
ref |
str | None
|
optional unique identifier of the schema, used to reference the schema in other places |
None
|
metadata |
Dict[str, Any] | None
|
Any other information you want to include with the schema, not used by pydantic-core |
None
|
serialization |
SerSchema | None
|
Custom serialization schema |
None
|
Source code in .venv/lib/python3.10/site-packages/pydantic_core/core_schema.py
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|
generator_schema ¶
generator_schema(
items_schema: CoreSchema | None = None,
*,
min_length: int | None = None,
max_length: int | None = None,
ref: str | None = None,
metadata: Dict[str, Any] | None = None,
serialization: IncExSeqOrElseSerSchema | None = None
) -> GeneratorSchema
Returns a schema that matches a generator value, e.g.:
from typing import Iterator
from pydantic_core import SchemaValidator, core_schema
def gen() -> Iterator[int]:
yield 1
schema = core_schema.generator_schema(items_schema=core_schema.int_schema())
v = SchemaValidator(schema)
v.validate_python(gen())
Unlike other types, validated generators do not raise ValidationErrors eagerly, but instead will raise a ValidationError when a violating value is actually read from the generator. This is to ensure that "validated" generators retain the benefit of lazy evaluation.
Parameters:
Name | Type | Description | Default |
---|---|---|---|
items_schema |
CoreSchema | None
|
The value must be a generator with items that match this schema |
None
|
min_length |
int | None
|
The value must be a generator that yields at least this many items |
None
|
max_length |
int | None
|
The value must be a generator that yields at most this many items |
None
|
ref |
str | None
|
optional unique identifier of the schema, used to reference the schema in other places |
None
|
metadata |
Dict[str, Any] | None
|
Any other information you want to include with the schema, not used by pydantic-core |
None
|
serialization |
IncExSeqOrElseSerSchema | None
|
Custom serialization schema |
None
|
Source code in .venv/lib/python3.10/site-packages/pydantic_core/core_schema.py
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|
dict_schema ¶
dict_schema(
keys_schema: CoreSchema | None = None,
values_schema: CoreSchema | None = None,
*,
min_length: int | None = None,
max_length: int | None = None,
strict: bool | None = None,
ref: str | None = None,
metadata: Dict[str, Any] | None = None,
serialization: SerSchema | None = None
) -> DictSchema
Returns a schema that matches a dict value, e.g.:
from pydantic_core import SchemaValidator, core_schema
schema = core_schema.dict_schema(
keys_schema=core_schema.str_schema(), values_schema=core_schema.int_schema()
)
v = SchemaValidator(schema)
assert v.validate_python({'a': '1', 'b': 2}) == {'a': 1, 'b': 2}
Parameters:
Name | Type | Description | Default |
---|---|---|---|
keys_schema |
CoreSchema | None
|
The value must be a dict with keys that match this schema |
None
|
values_schema |
CoreSchema | None
|
The value must be a dict with values that match this schema |
None
|
min_length |
int | None
|
The value must be a dict with at least this many items |
None
|
max_length |
int | None
|
The value must be a dict with at most this many items |
None
|
strict |
bool | None
|
Whether the keys and values should be validated with strict mode |
None
|
ref |
str | None
|
optional unique identifier of the schema, used to reference the schema in other places |
None
|
metadata |
Dict[str, Any] | None
|
Any other information you want to include with the schema, not used by pydantic-core |
None
|
serialization |
SerSchema | None
|
Custom serialization schema |
None
|
Source code in .venv/lib/python3.10/site-packages/pydantic_core/core_schema.py
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|
no_info_before_validator_function ¶
no_info_before_validator_function(
function: NoInfoValidatorFunction,
schema: CoreSchema,
*,
ref: str | None = None,
metadata: Dict[str, Any] | None = None,
serialization: SerSchema | None = None
) -> BeforeValidatorFunctionSchema
Returns a schema that calls a validator function before validating, no info
argument is provided, e.g.:
from pydantic_core import SchemaValidator, core_schema
def fn(v: bytes) -> str:
return v.decode() + 'world'
func_schema = core_schema.no_info_before_validator_function(
function=fn, schema=core_schema.str_schema()
)
schema = core_schema.typed_dict_schema({'a': core_schema.typed_dict_field(func_schema)})
v = SchemaValidator(schema)
assert v.validate_python({'a': b'hello '}) == {'a': 'hello world'}
Parameters:
Name | Type | Description | Default |
---|---|---|---|
function |
NoInfoValidatorFunction
|
The validator function to call |
required |
schema |
CoreSchema
|
The schema to validate the output of the validator function |
required |
ref |
str | None
|
optional unique identifier of the schema, used to reference the schema in other places |
None
|
metadata |
Dict[str, Any] | None
|
Any other information you want to include with the schema, not used by pydantic-core |
None
|
serialization |
SerSchema | None
|
Custom serialization schema |
None
|
Source code in .venv/lib/python3.10/site-packages/pydantic_core/core_schema.py
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|
with_info_before_validator_function ¶
with_info_before_validator_function(
function: WithInfoValidatorFunction,
schema: CoreSchema,
*,
field_name: str | None = None,
ref: str | None = None,
metadata: Dict[str, Any] | None = None,
serialization: SerSchema | None = None
) -> BeforeValidatorFunctionSchema
Returns a schema that calls a validator function before validation, the function is called with
an info
argument, e.g.:
from pydantic_core import SchemaValidator, core_schema
def fn(v: bytes, info: core_schema.ValidationInfo) -> str:
assert info.data is not None
assert info.field_name is not None
return v.decode() + 'world'
func_schema = core_schema.with_info_before_validator_function(
function=fn, schema=core_schema.str_schema(), field_name='a'
)
schema = core_schema.typed_dict_schema({'a': core_schema.typed_dict_field(func_schema)})
v = SchemaValidator(schema)
assert v.validate_python({'a': b'hello '}) == {'a': 'hello world'}
Parameters:
Name | Type | Description | Default |
---|---|---|---|
function |
WithInfoValidatorFunction
|
The validator function to call |
required |
field_name |
str | None
|
The name of the field |
None
|
schema |
CoreSchema
|
The schema to validate the output of the validator function |
required |
ref |
str | None
|
optional unique identifier of the schema, used to reference the schema in other places |
None
|
metadata |
Dict[str, Any] | None
|
Any other information you want to include with the schema, not used by pydantic-core |
None
|
serialization |
SerSchema | None
|
Custom serialization schema |
None
|
Source code in .venv/lib/python3.10/site-packages/pydantic_core/core_schema.py
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|
no_info_after_validator_function ¶
no_info_after_validator_function(
function: NoInfoValidatorFunction,
schema: CoreSchema,
*,
ref: str | None = None,
metadata: Dict[str, Any] | None = None,
serialization: SerSchema | None = None
) -> AfterValidatorFunctionSchema
Returns a schema that calls a validator function after validating, no info
argument is provided, e.g.:
from pydantic_core import SchemaValidator, core_schema
def fn(v: str) -> str:
return v + 'world'
func_schema = core_schema.no_info_after_validator_function(fn, core_schema.str_schema())
schema = core_schema.typed_dict_schema({'a': core_schema.typed_dict_field(func_schema)})
v = SchemaValidator(schema)
assert v.validate_python({'a': b'hello '}) == {'a': 'hello world'}
Parameters:
Name | Type | Description | Default |
---|---|---|---|
function |
NoInfoValidatorFunction
|
The validator function to call after the schema is validated |
required |
schema |
CoreSchema
|
The schema to validate before the validator function |
required |
ref |
str | None
|
optional unique identifier of the schema, used to reference the schema in other places |
None
|
metadata |
Dict[str, Any] | None
|
Any other information you want to include with the schema, not used by pydantic-core |
None
|
serialization |
SerSchema | None
|
Custom serialization schema |
None
|
Source code in .venv/lib/python3.10/site-packages/pydantic_core/core_schema.py
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|
with_info_after_validator_function ¶
with_info_after_validator_function(
function: WithInfoValidatorFunction,
schema: CoreSchema,
*,
field_name: str | None = None,
ref: str | None = None,
metadata: Dict[str, Any] | None = None,
serialization: SerSchema | None = None
) -> AfterValidatorFunctionSchema
Returns a schema that calls a validator function after validation, the function is called with
an info
argument, e.g.:
from pydantic_core import SchemaValidator, core_schema
def fn(v: str, info: core_schema.ValidationInfo) -> str:
assert info.data is not None
assert info.field_name is not None
return v + 'world'
func_schema = core_schema.with_info_after_validator_function(
function=fn, schema=core_schema.str_schema(), field_name='a'
)
schema = core_schema.typed_dict_schema({'a': core_schema.typed_dict_field(func_schema)})
v = SchemaValidator(schema)
assert v.validate_python({'a': b'hello '}) == {'a': 'hello world'}
Parameters:
Name | Type | Description | Default |
---|---|---|---|
function |
WithInfoValidatorFunction
|
The validator function to call after the schema is validated |
required |
schema |
CoreSchema
|
The schema to validate before the validator function |
required |
field_name |
str | None
|
The name of the field this validators is applied to, if any |
None
|
ref |
str | None
|
optional unique identifier of the schema, used to reference the schema in other places |
None
|
metadata |
Dict[str, Any] | None
|
Any other information you want to include with the schema, not used by pydantic-core |
None
|
serialization |
SerSchema | None
|
Custom serialization schema |
None
|
Source code in .venv/lib/python3.10/site-packages/pydantic_core/core_schema.py
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|
no_info_wrap_validator_function ¶
no_info_wrap_validator_function(
function: NoInfoWrapValidatorFunction,
schema: CoreSchema,
*,
ref: str | None = None,
metadata: Dict[str, Any] | None = None,
serialization: SerSchema | None = None
) -> WrapValidatorFunctionSchema
Returns a schema which calls a function with a validator
callable argument which can
optionally be used to call inner validation with the function logic, this is much like the
"onion" implementation of middleware in many popular web frameworks, no info
argument is passed, e.g.:
from pydantic_core import SchemaValidator, core_schema
def fn(
v: str,
validator: core_schema.ValidatorFunctionWrapHandler,
) -> str:
return validator(input_value=v) + 'world'
schema = core_schema.no_info_wrap_validator_function(
function=fn, schema=core_schema.str_schema()
)
v = SchemaValidator(schema)
assert v.validate_python('hello ') == 'hello world'
Parameters:
Name | Type | Description | Default |
---|---|---|---|
function |
NoInfoWrapValidatorFunction
|
The validator function to call |
required |
schema |
CoreSchema
|
The schema to validate the output of the validator function |
required |
ref |
str | None
|
optional unique identifier of the schema, used to reference the schema in other places |
None
|
metadata |
Dict[str, Any] | None
|
Any other information you want to include with the schema, not used by pydantic-core |
None
|
serialization |
SerSchema | None
|
Custom serialization schema |
None
|
Source code in .venv/lib/python3.10/site-packages/pydantic_core/core_schema.py
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|
with_info_wrap_validator_function ¶
with_info_wrap_validator_function(
function: WithInfoWrapValidatorFunction,
schema: CoreSchema,
*,
field_name: str | None = None,
ref: str | None = None,
metadata: Dict[str, Any] | None = None,
serialization: SerSchema | None = None
) -> WrapValidatorFunctionSchema
Returns a schema which calls a function with a validator
callable argument which can
optionally be used to call inner validation with the function logic, this is much like the
"onion" implementation of middleware in many popular web frameworks, an info
argument is also passed, e.g.:
from pydantic_core import SchemaValidator, core_schema
def fn(
v: str,
validator: core_schema.ValidatorFunctionWrapHandler,
info: core_schema.ValidationInfo,
) -> str:
return validator(input_value=v) + 'world'
schema = core_schema.with_info_wrap_validator_function(
function=fn, schema=core_schema.str_schema()
)
v = SchemaValidator(schema)
assert v.validate_python('hello ') == 'hello world'
Parameters:
Name | Type | Description | Default |
---|---|---|---|
function |
WithInfoWrapValidatorFunction
|
The validator function to call |
required |
schema |
CoreSchema
|
The schema to validate the output of the validator function |
required |
field_name |
str | None
|
The name of the field this validators is applied to, if any |
None
|
ref |
str | None
|
optional unique identifier of the schema, used to reference the schema in other places |
None
|
metadata |
Dict[str, Any] | None
|
Any other information you want to include with the schema, not used by pydantic-core |
None
|
serialization |
SerSchema | None
|
Custom serialization schema |
None
|
Source code in .venv/lib/python3.10/site-packages/pydantic_core/core_schema.py
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|
no_info_plain_validator_function ¶
no_info_plain_validator_function(
function: NoInfoValidatorFunction,
*,
ref: str | None = None,
metadata: Dict[str, Any] | None = None,
serialization: SerSchema | None = None
) -> PlainValidatorFunctionSchema
Returns a schema that uses the provided function for validation, no info
argument is passed, e.g.:
from pydantic_core import SchemaValidator, core_schema
def fn(v: str) -> str:
assert 'hello' in v
return v + 'world'
schema = core_schema.no_info_plain_validator_function(function=fn)
v = SchemaValidator(schema)
assert v.validate_python('hello ') == 'hello world'
Parameters:
Name | Type | Description | Default |
---|---|---|---|
function |
NoInfoValidatorFunction
|
The validator function to call |
required |
ref |
str | None
|
optional unique identifier of the schema, used to reference the schema in other places |
None
|
metadata |
Dict[str, Any] | None
|
Any other information you want to include with the schema, not used by pydantic-core |
None
|
serialization |
SerSchema | None
|
Custom serialization schema |
None
|
Source code in .venv/lib/python3.10/site-packages/pydantic_core/core_schema.py
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|
with_info_plain_validator_function ¶
with_info_plain_validator_function(
function: WithInfoValidatorFunction,
*,
field_name: str | None = None,
ref: str | None = None,
metadata: Dict[str, Any] | None = None,
serialization: SerSchema | None = None
) -> PlainValidatorFunctionSchema
Returns a schema that uses the provided function for validation, an info
argument is passed, e.g.:
from pydantic_core import SchemaValidator, core_schema
def fn(v: str, info: core_schema.ValidationInfo) -> str:
assert 'hello' in v
return v + 'world'
schema = core_schema.with_info_plain_validator_function(function=fn)
v = SchemaValidator(schema)
assert v.validate_python('hello ') == 'hello world'
Parameters:
Name | Type | Description | Default |
---|---|---|---|
function |
WithInfoValidatorFunction
|
The validator function to call |
required |
field_name |
str | None
|
The name of the field this validators is applied to, if any |
None
|
ref |
str | None
|
optional unique identifier of the schema, used to reference the schema in other places |
None
|
metadata |
Dict[str, Any] | None
|
Any other information you want to include with the schema, not used by pydantic-core |
None
|
serialization |
SerSchema | None
|
Custom serialization schema |
None
|
Source code in .venv/lib/python3.10/site-packages/pydantic_core/core_schema.py
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|
with_default_schema ¶
with_default_schema(
schema: CoreSchema,
*,
default: Any = PydanticUndefined,
default_factory: Callable[[], Any] | None = None,
on_error: (
Literal["raise", "omit", "default"] | None
) = None,
validate_default: bool | None = None,
strict: bool | None = None,
ref: str | None = None,
metadata: Dict[str, Any] | None = None,
serialization: SerSchema | None = None
) -> WithDefaultSchema
Returns a schema that adds a default value to the given schema, e.g.:
from pydantic_core import SchemaValidator, core_schema
schema = core_schema.with_default_schema(core_schema.str_schema(), default='hello')
wrapper_schema = core_schema.typed_dict_schema(
{'a': core_schema.typed_dict_field(schema)}
)
v = SchemaValidator(wrapper_schema)
assert v.validate_python({}) == v.validate_python({'a': 'hello'})
Parameters:
Name | Type | Description | Default |
---|---|---|---|
schema |
CoreSchema
|
The schema to add a default value to |
required |
default |
Any
|
The default value to use |
PydanticUndefined
|
default_factory |
Callable[[], Any] | None
|
A function that returns the default value to use |
None
|
on_error |
Literal['raise', 'omit', 'default'] | None
|
What to do if the schema validation fails. One of 'raise', 'omit', 'default' |
None
|
validate_default |
bool | None
|
Whether the default value should be validated |
None
|
strict |
bool | None
|
Whether the underlying schema should be validated with strict mode |
None
|
ref |
str | None
|
optional unique identifier of the schema, used to reference the schema in other places |
None
|
metadata |
Dict[str, Any] | None
|
Any other information you want to include with the schema, not used by pydantic-core |
None
|
serialization |
SerSchema | None
|
Custom serialization schema |
None
|
Source code in .venv/lib/python3.10/site-packages/pydantic_core/core_schema.py
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|
nullable_schema ¶
nullable_schema(
schema: CoreSchema,
*,
strict: bool | None = None,
ref: str | None = None,
metadata: Dict[str, Any] | None = None,
serialization: SerSchema | None = None
) -> NullableSchema
Returns a schema that matches a nullable value, e.g.:
from pydantic_core import SchemaValidator, core_schema
schema = core_schema.nullable_schema(core_schema.str_schema())
v = SchemaValidator(schema)
assert v.validate_python(None) is None
Parameters:
Name | Type | Description | Default |
---|---|---|---|
schema |
CoreSchema
|
The schema to wrap |
required |
strict |
bool | None
|
Whether the underlying schema should be validated with strict mode |
None
|
ref |
str | None
|
optional unique identifier of the schema, used to reference the schema in other places |
None
|
metadata |
Dict[str, Any] | None
|
Any other information you want to include with the schema, not used by pydantic-core |
None
|
serialization |
SerSchema | None
|
Custom serialization schema |
None
|
Source code in .venv/lib/python3.10/site-packages/pydantic_core/core_schema.py
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|
union_schema ¶
union_schema(
choices: list[CoreSchema | tuple[CoreSchema, str]],
*,
auto_collapse: bool | None = None,
custom_error_type: str | None = None,
custom_error_message: str | None = None,
custom_error_context: (
dict[str, str | int] | None
) = None,
mode: Literal["smart", "left_to_right"] | None = None,
strict: bool | None = None,
ref: str | None = None,
metadata: Dict[str, Any] | None = None,
serialization: SerSchema | None = None
) -> UnionSchema
Returns a schema that matches a union value, e.g.:
from pydantic_core import SchemaValidator, core_schema
schema = core_schema.union_schema([core_schema.str_schema(), core_schema.int_schema()])
v = SchemaValidator(schema)
assert v.validate_python('hello') == 'hello'
assert v.validate_python(1) == 1
Parameters:
Name | Type | Description | Default |
---|---|---|---|
choices |
list[CoreSchema | tuple[CoreSchema, str]]
|
The schemas to match. If a tuple, the second item is used as the label for the case. |
required |
auto_collapse |
bool | None
|
whether to automatically collapse unions with one element to the inner validator, default true |
None
|
custom_error_type |
str | None
|
The custom error type to use if the validation fails |
None
|
custom_error_message |
str | None
|
The custom error message to use if the validation fails |
None
|
custom_error_context |
dict[str, str | int] | None
|
The custom error context to use if the validation fails |
None
|
mode |
Literal['smart', 'left_to_right'] | None
|
How to select which choice to return
* |
None
|
strict |
bool | None
|
Whether the underlying schemas should be validated with strict mode |
None
|
ref |
str | None
|
optional unique identifier of the schema, used to reference the schema in other places |
None
|
metadata |
Dict[str, Any] | None
|
Any other information you want to include with the schema, not used by pydantic-core |
None
|
serialization |
SerSchema | None
|
Custom serialization schema |
None
|
Source code in .venv/lib/python3.10/site-packages/pydantic_core/core_schema.py
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|
tagged_union_schema ¶
tagged_union_schema(
choices: Dict[Any, CoreSchema],
discriminator: (
str
| list[str | int]
| list[list[str | int]]
| Callable[[Any], Any]
),
*,
custom_error_type: str | None = None,
custom_error_message: str | None = None,
custom_error_context: (
dict[str, int | str | float] | None
) = None,
strict: bool | None = None,
from_attributes: bool | None = None,
ref: str | None = None,
metadata: Dict[str, Any] | None = None,
serialization: SerSchema | None = None
) -> TaggedUnionSchema
Returns a schema that matches a tagged union value, e.g.:
from pydantic_core import SchemaValidator, core_schema
apple_schema = core_schema.typed_dict_schema(
{
'foo': core_schema.typed_dict_field(core_schema.str_schema()),
'bar': core_schema.typed_dict_field(core_schema.int_schema()),
}
)
banana_schema = core_schema.typed_dict_schema(
{
'foo': core_schema.typed_dict_field(core_schema.str_schema()),
'spam': core_schema.typed_dict_field(
core_schema.list_schema(items_schema=core_schema.int_schema())
),
}
)
schema = core_schema.tagged_union_schema(
choices={
'apple': apple_schema,
'banana': banana_schema,
},
discriminator='foo',
)
v = SchemaValidator(schema)
assert v.validate_python({'foo': 'apple', 'bar': '123'}) == {'foo': 'apple', 'bar': 123}
assert v.validate_python({'foo': 'banana', 'spam': [1, 2, 3]}) == {
'foo': 'banana',
'spam': [1, 2, 3],
}
Parameters:
Name | Type | Description | Default |
---|---|---|---|
choices |
Dict[Any, CoreSchema]
|
The schemas to match
When retrieving a schema from |
required |
discriminator |
str | list[str | int] | list[list[str | int]] | Callable[[Any], Any]
|
The discriminator to use to determine the schema to use
* If |
required |
custom_error_type |
str | None
|
The custom error type to use if the validation fails |
None
|
custom_error_message |
str | None
|
The custom error message to use if the validation fails |
None
|
custom_error_context |
dict[str, int | str | float] | None
|
The custom error context to use if the validation fails |
None
|
strict |
bool | None
|
Whether the underlying schemas should be validated with strict mode |
None
|
from_attributes |
bool | None
|
Whether to use the attributes of the object to retrieve the discriminator value |
None
|
ref |
str | None
|
optional unique identifier of the schema, used to reference the schema in other places |
None
|
metadata |
Dict[str, Any] | None
|
Any other information you want to include with the schema, not used by pydantic-core |
None
|
serialization |
SerSchema | None
|
Custom serialization schema |
None
|
Source code in .venv/lib/python3.10/site-packages/pydantic_core/core_schema.py
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|
chain_schema ¶
chain_schema(
steps: list[CoreSchema],
*,
ref: str | None = None,
metadata: Dict[str, Any] | None = None,
serialization: SerSchema | None = None
) -> ChainSchema
Returns a schema that chains the provided validation schemas, e.g.:
from pydantic_core import SchemaValidator, core_schema
def fn(v: str, info: core_schema.ValidationInfo) -> str:
assert 'hello' in v
return v + ' world'
fn_schema = core_schema.with_info_plain_validator_function(function=fn)
schema = core_schema.chain_schema(
[fn_schema, fn_schema, fn_schema, core_schema.str_schema()]
)
v = SchemaValidator(schema)
assert v.validate_python('hello') == 'hello world world world'
Parameters:
Name | Type | Description | Default |
---|---|---|---|
steps |
list[CoreSchema]
|
The schemas to chain |
required |
ref |
str | None
|
optional unique identifier of the schema, used to reference the schema in other places |
None
|
metadata |
Dict[str, Any] | None
|
Any other information you want to include with the schema, not used by pydantic-core |
None
|
serialization |
SerSchema | None
|
Custom serialization schema |
None
|
Source code in .venv/lib/python3.10/site-packages/pydantic_core/core_schema.py
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|
lax_or_strict_schema ¶
lax_or_strict_schema(
lax_schema: CoreSchema,
strict_schema: CoreSchema,
*,
strict: bool | None = None,
ref: str | None = None,
metadata: Dict[str, Any] | None = None,
serialization: SerSchema | None = None
) -> LaxOrStrictSchema
Returns a schema that uses the lax or strict schema, e.g.:
from pydantic_core import SchemaValidator, core_schema
def fn(v: str, info: core_schema.ValidationInfo) -> str:
assert 'hello' in v
return v + ' world'
lax_schema = core_schema.int_schema(strict=False)
strict_schema = core_schema.int_schema(strict=True)
schema = core_schema.lax_or_strict_schema(
lax_schema=lax_schema, strict_schema=strict_schema, strict=True
)
v = SchemaValidator(schema)
assert v.validate_python(123) == 123
schema = core_schema.lax_or_strict_schema(
lax_schema=lax_schema, strict_schema=strict_schema, strict=False
)
v = SchemaValidator(schema)
assert v.validate_python('123') == 123
Parameters:
Name | Type | Description | Default |
---|---|---|---|
lax_schema |
CoreSchema
|
The lax schema to use |
required |
strict_schema |
CoreSchema
|
The strict schema to use |
required |
strict |
bool | None
|
Whether the strict schema should be used |
None
|
ref |
str | None
|
optional unique identifier of the schema, used to reference the schema in other places |
None
|
metadata |
Dict[str, Any] | None
|
Any other information you want to include with the schema, not used by pydantic-core |
None
|
serialization |
SerSchema | None
|
Custom serialization schema |
None
|
Source code in .venv/lib/python3.10/site-packages/pydantic_core/core_schema.py
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|
json_or_python_schema ¶
json_or_python_schema(
json_schema: CoreSchema,
python_schema: CoreSchema,
*,
ref: str | None = None,
metadata: Dict[str, Any] | None = None,
serialization: SerSchema | None = None
) -> JsonOrPythonSchema
Returns a schema that uses the Json or Python schema depending on the input:
from pydantic_core import SchemaValidator, ValidationError, core_schema
v = SchemaValidator(
core_schema.json_or_python_schema(
json_schema=core_schema.int_schema(),
python_schema=core_schema.int_schema(strict=True),
)
)
assert v.validate_json('"123"') == 123
try:
v.validate_python('123')
except ValidationError:
pass
else:
raise AssertionError('Validation should have failed')
Parameters:
Name | Type | Description | Default |
---|---|---|---|
json_schema |
CoreSchema
|
The schema to use for Json inputs |
required |
python_schema |
CoreSchema
|
The schema to use for Python inputs |
required |
ref |
str | None
|
optional unique identifier of the schema, used to reference the schema in other places |
None
|
metadata |
Dict[str, Any] | None
|
Any other information you want to include with the schema, not used by pydantic-core |
None
|
serialization |
SerSchema | None
|
Custom serialization schema |
None
|
Source code in .venv/lib/python3.10/site-packages/pydantic_core/core_schema.py
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|
typed_dict_field ¶
typed_dict_field(
schema: CoreSchema,
*,
required: bool | None = None,
validation_alias: (
str | list[str | int] | list[list[str | int]] | None
) = None,
serialization_alias: str | None = None,
serialization_exclude: bool | None = None,
metadata: Dict[str, Any] | None = None
) -> TypedDictField
Returns a schema that matches a typed dict field, e.g.:
from pydantic_core import core_schema
field = core_schema.typed_dict_field(schema=core_schema.int_schema(), required=True)
Parameters:
Name | Type | Description | Default |
---|---|---|---|
schema |
CoreSchema
|
The schema to use for the field |
required |
required |
bool | None
|
Whether the field is required |
None
|
validation_alias |
str | list[str | int] | list[list[str | int]] | None
|
The alias(es) to use to find the field in the validation data |
None
|
serialization_alias |
str | None
|
The alias to use as a key when serializing |
None
|
serialization_exclude |
bool | None
|
Whether to exclude the field when serializing |
None
|
metadata |
Dict[str, Any] | None
|
Any other information you want to include with the schema, not used by pydantic-core |
None
|
Source code in .venv/lib/python3.10/site-packages/pydantic_core/core_schema.py
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|
typed_dict_schema ¶
typed_dict_schema(
fields: Dict[str, TypedDictField],
*,
cls: Type[TypedDict] | None = None,
computed_fields: list[ComputedField] | None = None,
strict: bool | None = None,
extras_schema: CoreSchema | None = None,
extra_behavior: ExtraBehavior | None = None,
total: bool | None = None,
populate_by_name: bool | None = None,
ref: str | None = None,
metadata: Dict[str, Any] | None = None,
serialization: SerSchema | None = None,
config: CoreConfig | None = None
) -> TypedDictSchema
Returns a schema that matches a typed dict, e.g.:
from typing_extensions import TypedDict
from pydantic_core import SchemaValidator, core_schema
class MyTypedDict(TypedDict):
a: str
wrapper_schema = core_schema.typed_dict_schema(
{'a': core_schema.typed_dict_field(core_schema.str_schema())}, cls=MyTypedDict
)
v = SchemaValidator(wrapper_schema)
assert v.validate_python({'a': 'hello'}) == {'a': 'hello'}
Parameters:
Name | Type | Description | Default |
---|---|---|---|
fields |
Dict[str, TypedDictField]
|
The fields to use for the typed dict |
required |
cls |
Type[TypedDict] | None
|
The class to use for the typed dict |
None
|
computed_fields |
list[ComputedField] | None
|
Computed fields to use when serializing the model, only applies when directly inside a model |
None
|
strict |
bool | None
|
Whether the typed dict is strict |
None
|
extras_schema |
CoreSchema | None
|
The extra validator to use for the typed dict |
None
|
ref |
str | None
|
optional unique identifier of the schema, used to reference the schema in other places |
None
|
metadata |
Dict[str, Any] | None
|
Any other information you want to include with the schema, not used by pydantic-core |
None
|
extra_behavior |
ExtraBehavior | None
|
The extra behavior to use for the typed dict |
None
|
total |
bool | None
|
Whether the typed dict is total |
None
|
populate_by_name |
bool | None
|
Whether the typed dict should populate by name |
None
|
serialization |
SerSchema | None
|
Custom serialization schema |
None
|
Source code in .venv/lib/python3.10/site-packages/pydantic_core/core_schema.py
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|
model_field ¶
model_field(
schema: CoreSchema,
*,
validation_alias: (
str | list[str | int] | list[list[str | int]] | None
) = None,
serialization_alias: str | None = None,
serialization_exclude: bool | None = None,
frozen: bool | None = None,
metadata: Dict[str, Any] | None = None
) -> ModelField
Returns a schema for a model field, e.g.:
from pydantic_core import core_schema
field = core_schema.model_field(schema=core_schema.int_schema())
Parameters:
Name | Type | Description | Default |
---|---|---|---|
schema |
CoreSchema
|
The schema to use for the field |
required |
validation_alias |
str | list[str | int] | list[list[str | int]] | None
|
The alias(es) to use to find the field in the validation data |
None
|
serialization_alias |
str | None
|
The alias to use as a key when serializing |
None
|
serialization_exclude |
bool | None
|
Whether to exclude the field when serializing |
None
|
frozen |
bool | None
|
Whether the field is frozen |
None
|
metadata |
Dict[str, Any] | None
|
Any other information you want to include with the schema, not used by pydantic-core |
None
|
Source code in .venv/lib/python3.10/site-packages/pydantic_core/core_schema.py
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|
model_fields_schema ¶
model_fields_schema(
fields: Dict[str, ModelField],
*,
model_name: str | None = None,
computed_fields: list[ComputedField] | None = None,
strict: bool | None = None,
extras_schema: CoreSchema | None = None,
extra_behavior: ExtraBehavior | None = None,
populate_by_name: bool | None = None,
from_attributes: bool | None = None,
ref: str | None = None,
metadata: Dict[str, Any] | None = None,
serialization: SerSchema | None = None
) -> ModelFieldsSchema
Returns a schema that matches a typed dict, e.g.:
from pydantic_core import SchemaValidator, core_schema
wrapper_schema = core_schema.model_fields_schema(
{'a': core_schema.model_field(core_schema.str_schema())}
)
v = SchemaValidator(wrapper_schema)
print(v.validate_python({'a': 'hello'}))
#> ({'a': 'hello'}, None, {'a'})
Parameters:
Name | Type | Description | Default |
---|---|---|---|
fields |
Dict[str, ModelField]
|
The fields to use for the typed dict |
required |
model_name |
str | None
|
The name of the model, used for error messages, defaults to "Model" |
None
|
computed_fields |
list[ComputedField] | None
|
Computed fields to use when serializing the model, only applies when directly inside a model |
None
|
strict |
bool | None
|
Whether the typed dict is strict |
None
|
extras_schema |
CoreSchema | None
|
The extra validator to use for the typed dict |
None
|
ref |
str | None
|
optional unique identifier of the schema, used to reference the schema in other places |
None
|
metadata |
Dict[str, Any] | None
|
Any other information you want to include with the schema, not used by pydantic-core |
None
|
extra_behavior |
ExtraBehavior | None
|
The extra behavior to use for the typed dict |
None
|
populate_by_name |
bool | None
|
Whether the typed dict should populate by name |
None
|
from_attributes |
bool | None
|
Whether the typed dict should be populated from attributes |
None
|
serialization |
SerSchema | None
|
Custom serialization schema |
None
|
Source code in .venv/lib/python3.10/site-packages/pydantic_core/core_schema.py
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|
model_schema ¶
model_schema(
cls: Type[Any],
schema: CoreSchema,
*,
custom_init: bool | None = None,
root_model: bool | None = None,
post_init: str | None = None,
revalidate_instances: (
Literal["always", "never", "subclass-instances"]
| None
) = None,
strict: bool | None = None,
frozen: bool | None = None,
extra_behavior: ExtraBehavior | None = None,
config: CoreConfig | None = None,
ref: str | None = None,
metadata: Dict[str, Any] | None = None,
serialization: SerSchema | None = None
) -> ModelSchema
A model schema generally contains a typed-dict schema.
It will run the typed dict validator, then create a new class
and set the dict and fields set returned from the typed dict validator
to __dict__
and __pydantic_fields_set__
respectively.
Example:
from pydantic_core import CoreConfig, SchemaValidator, core_schema
class MyModel:
__slots__ = (
'__dict__',
'__pydantic_fields_set__',
'__pydantic_extra__',
'__pydantic_private__',
)
schema = core_schema.model_schema(
cls=MyModel,
config=CoreConfig(str_max_length=5),
schema=core_schema.model_fields_schema(
fields={'a': core_schema.model_field(core_schema.str_schema())},
),
)
v = SchemaValidator(schema)
assert v.isinstance_python({'a': 'hello'}) is True
assert v.isinstance_python({'a': 'too long'}) is False
Parameters:
Name | Type | Description | Default |
---|---|---|---|
cls |
Type[Any]
|
The class to use for the model |
required |
schema |
CoreSchema
|
The schema to use for the model |
required |
custom_init |
bool | None
|
Whether the model has a custom init method |
None
|
root_model |
bool | None
|
Whether the model is a |
None
|
post_init |
str | None
|
The call after init to use for the model |
None
|
revalidate_instances |
Literal['always', 'never', 'subclass-instances'] | None
|
whether instances of models and dataclasses (including subclass instances) should re-validate defaults to config.revalidate_instances, else 'never' |
None
|
strict |
bool | None
|
Whether the model is strict |
None
|
frozen |
bool | None
|
Whether the model is frozen |
None
|
extra_behavior |
ExtraBehavior | None
|
The extra behavior to use for the model, used in serialization |
None
|
config |
CoreConfig | None
|
The config to use for the model |
None
|
ref |
str | None
|
optional unique identifier of the schema, used to reference the schema in other places |
None
|
metadata |
Dict[str, Any] | None
|
Any other information you want to include with the schema, not used by pydantic-core |
None
|
serialization |
SerSchema | None
|
Custom serialization schema |
None
|
Source code in .venv/lib/python3.10/site-packages/pydantic_core/core_schema.py
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|
dataclass_field ¶
dataclass_field(
name: str,
schema: CoreSchema,
*,
kw_only: bool | None = None,
init: bool | None = None,
init_only: bool | None = None,
validation_alias: (
str | list[str | int] | list[list[str | int]] | None
) = None,
serialization_alias: str | None = None,
serialization_exclude: bool | None = None,
metadata: Dict[str, Any] | None = None,
frozen: bool | None = None
) -> DataclassField
Returns a schema for a dataclass field, e.g.:
from pydantic_core import SchemaValidator, core_schema
field = core_schema.dataclass_field(
name='a', schema=core_schema.str_schema(), kw_only=False
)
schema = core_schema.dataclass_args_schema('Foobar', [field])
v = SchemaValidator(schema)
assert v.validate_python({'a': 'hello'}) == ({'a': 'hello'}, None)
Parameters:
Name | Type | Description | Default |
---|---|---|---|
name |
str
|
The name to use for the argument parameter |
required |
schema |
CoreSchema
|
The schema to use for the argument parameter |
required |
kw_only |
bool | None
|
Whether the field can be set with a positional argument as well as a keyword argument |
None
|
init |
bool | None
|
Whether the field should be validated during initialization |
None
|
init_only |
bool | None
|
Whether the field should be omitted from |
None
|
validation_alias |
str | list[str | int] | list[list[str | int]] | None
|
The alias(es) to use to find the field in the validation data |
None
|
serialization_alias |
str | None
|
The alias to use as a key when serializing |
None
|
serialization_exclude |
bool | None
|
Whether to exclude the field when serializing |
None
|
metadata |
Dict[str, Any] | None
|
Any other information you want to include with the schema, not used by pydantic-core |
None
|
frozen |
bool | None
|
Whether the field is frozen |
None
|
Source code in .venv/lib/python3.10/site-packages/pydantic_core/core_schema.py
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|
dataclass_args_schema ¶
dataclass_args_schema(
dataclass_name: str,
fields: list[DataclassField],
*,
computed_fields: List[ComputedField] | None = None,
populate_by_name: bool | None = None,
collect_init_only: bool | None = None,
ref: str | None = None,
metadata: Dict[str, Any] | None = None,
serialization: SerSchema | None = None,
extra_behavior: ExtraBehavior | None = None
) -> DataclassArgsSchema
Returns a schema for validating dataclass arguments, e.g.:
from pydantic_core import SchemaValidator, core_schema
field_a = core_schema.dataclass_field(
name='a', schema=core_schema.str_schema(), kw_only=False
)
field_b = core_schema.dataclass_field(
name='b', schema=core_schema.bool_schema(), kw_only=False
)
schema = core_schema.dataclass_args_schema('Foobar', [field_a, field_b])
v = SchemaValidator(schema)
assert v.validate_python({'a': 'hello', 'b': True}) == ({'a': 'hello', 'b': True}, None)
Parameters:
Name | Type | Description | Default |
---|---|---|---|
dataclass_name |
str
|
The name of the dataclass being validated |
required |
fields |
list[DataclassField]
|
The fields to use for the dataclass |
required |
computed_fields |
List[ComputedField] | None
|
Computed fields to use when serializing the dataclass |
None
|
populate_by_name |
bool | None
|
Whether to populate by name |
None
|
collect_init_only |
bool | None
|
Whether to collect init only fields into a dict to pass to |
None
|
ref |
str | None
|
optional unique identifier of the schema, used to reference the schema in other places |
None
|
metadata |
Dict[str, Any] | None
|
Any other information you want to include with the schema, not used by pydantic-core |
None
|
serialization |
SerSchema | None
|
Custom serialization schema |
None
|
extra_behavior |
ExtraBehavior | None
|
How to handle extra fields |
None
|
Source code in .venv/lib/python3.10/site-packages/pydantic_core/core_schema.py
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|
dataclass_schema ¶
dataclass_schema(
cls: Type[Any],
schema: CoreSchema,
fields: List[str],
*,
cls_name: str | None = None,
post_init: bool | None = None,
revalidate_instances: (
Literal["always", "never", "subclass-instances"]
| None
) = None,
strict: bool | None = None,
ref: str | None = None,
metadata: Dict[str, Any] | None = None,
serialization: SerSchema | None = None,
frozen: bool | None = None,
slots: bool | None = None,
config: CoreConfig | None = None
) -> DataclassSchema
Returns a schema for a dataclass. As with ModelSchema
, this schema can only be used as a field within
another schema, not as the root type.
Parameters:
Name | Type | Description | Default |
---|---|---|---|
cls |
Type[Any]
|
The dataclass type, used to perform subclass checks |
required |
schema |
CoreSchema
|
The schema to use for the dataclass fields |
required |
fields |
List[str]
|
Fields of the dataclass, this is used in serialization and in validation during re-validation and while validating assignment |
required |
cls_name |
str | None
|
The name to use in error locs, etc; this is useful for generics (default: |
None
|
post_init |
bool | None
|
Whether to call |
None
|
revalidate_instances |
Literal['always', 'never', 'subclass-instances'] | None
|
whether instances of models and dataclasses (including subclass instances) should re-validate defaults to config.revalidate_instances, else 'never' |
None
|
strict |
bool | None
|
Whether to require an exact instance of |
None
|
ref |
str | None
|
optional unique identifier of the schema, used to reference the schema in other places |
None
|
metadata |
Dict[str, Any] | None
|
Any other information you want to include with the schema, not used by pydantic-core |
None
|
serialization |
SerSchema | None
|
Custom serialization schema |
None
|
frozen |
bool | None
|
Whether the dataclass is frozen |
None
|
slots |
bool | None
|
Whether |
None
|
Source code in .venv/lib/python3.10/site-packages/pydantic_core/core_schema.py
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|
arguments_parameter ¶
arguments_parameter(
name: str,
schema: CoreSchema,
*,
mode: (
Literal[
"positional_only",
"positional_or_keyword",
"keyword_only",
]
| None
) = None,
alias: (
str | list[str | int] | list[list[str | int]] | None
) = None
) -> ArgumentsParameter
Returns a schema that matches an argument parameter, e.g.:
from pydantic_core import SchemaValidator, core_schema
param = core_schema.arguments_parameter(
name='a', schema=core_schema.str_schema(), mode='positional_only'
)
schema = core_schema.arguments_schema([param])
v = SchemaValidator(schema)
assert v.validate_python(('hello',)) == (('hello',), {})
Parameters:
Name | Type | Description | Default |
---|---|---|---|
name |
str
|
The name to use for the argument parameter |
required |
schema |
CoreSchema
|
The schema to use for the argument parameter |
required |
mode |
Literal['positional_only', 'positional_or_keyword', 'keyword_only'] | None
|
The mode to use for the argument parameter |
None
|
alias |
str | list[str | int] | list[list[str | int]] | None
|
The alias to use for the argument parameter |
None
|
Source code in .venv/lib/python3.10/site-packages/pydantic_core/core_schema.py
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|
arguments_schema ¶
arguments_schema(
arguments: list[ArgumentsParameter],
*,
populate_by_name: bool | None = None,
var_args_schema: CoreSchema | None = None,
var_kwargs_schema: CoreSchema | None = None,
ref: str | None = None,
metadata: Dict[str, Any] | None = None,
serialization: SerSchema | None = None
) -> ArgumentsSchema
Returns a schema that matches an arguments schema, e.g.:
from pydantic_core import SchemaValidator, core_schema
param_a = core_schema.arguments_parameter(
name='a', schema=core_schema.str_schema(), mode='positional_only'
)
param_b = core_schema.arguments_parameter(
name='b', schema=core_schema.bool_schema(), mode='positional_only'
)
schema = core_schema.arguments_schema([param_a, param_b])
v = SchemaValidator(schema)
assert v.validate_python(('hello', True)) == (('hello', True), {})
Parameters:
Name | Type | Description | Default |
---|---|---|---|
arguments |
list[ArgumentsParameter]
|
The arguments to use for the arguments schema |
required |
populate_by_name |
bool | None
|
Whether to populate by name |
None
|
var_args_schema |
CoreSchema | None
|
The variable args schema to use for the arguments schema |
None
|
var_kwargs_schema |
CoreSchema | None
|
The variable kwargs schema to use for the arguments schema |
None
|
ref |
str | None
|
optional unique identifier of the schema, used to reference the schema in other places |
None
|
metadata |
Dict[str, Any] | None
|
Any other information you want to include with the schema, not used by pydantic-core |
None
|
serialization |
SerSchema | None
|
Custom serialization schema |
None
|
Source code in .venv/lib/python3.10/site-packages/pydantic_core/core_schema.py
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|
call_schema ¶
call_schema(
arguments: CoreSchema,
function: Callable[..., Any],
*,
function_name: str | None = None,
return_schema: CoreSchema | None = None,
ref: str | None = None,
metadata: Dict[str, Any] | None = None,
serialization: SerSchema | None = None
) -> CallSchema
Returns a schema that matches an arguments schema, then calls a function, e.g.:
from pydantic_core import SchemaValidator, core_schema
param_a = core_schema.arguments_parameter(
name='a', schema=core_schema.str_schema(), mode='positional_only'
)
param_b = core_schema.arguments_parameter(
name='b', schema=core_schema.bool_schema(), mode='positional_only'
)
args_schema = core_schema.arguments_schema([param_a, param_b])
schema = core_schema.call_schema(
arguments=args_schema,
function=lambda a, b: a + str(not b),
return_schema=core_schema.str_schema(),
)
v = SchemaValidator(schema)
assert v.validate_python((('hello', True))) == 'helloFalse'
Parameters:
Name | Type | Description | Default |
---|---|---|---|
arguments |
CoreSchema
|
The arguments to use for the arguments schema |
required |
function |
Callable[..., Any]
|
The function to use for the call schema |
required |
function_name |
str | None
|
The function name to use for the call schema, if not provided |
None
|
return_schema |
CoreSchema | None
|
The return schema to use for the call schema |
None
|
ref |
str | None
|
optional unique identifier of the schema, used to reference the schema in other places |
None
|
metadata |
Dict[str, Any] | None
|
Any other information you want to include with the schema, not used by pydantic-core |
None
|
serialization |
SerSchema | None
|
Custom serialization schema |
None
|
Source code in .venv/lib/python3.10/site-packages/pydantic_core/core_schema.py
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|
custom_error_schema ¶
custom_error_schema(
schema: CoreSchema,
custom_error_type: str,
*,
custom_error_message: str | None = None,
custom_error_context: dict[str, Any] | None = None,
ref: str | None = None,
metadata: Dict[str, Any] | None = None,
serialization: SerSchema | None = None
) -> CustomErrorSchema
Returns a schema that matches a custom error value, e.g.:
from pydantic_core import SchemaValidator, core_schema
schema = core_schema.custom_error_schema(
schema=core_schema.int_schema(),
custom_error_type='MyError',
custom_error_message='Error msg',
)
v = SchemaValidator(schema)
v.validate_python(1)
Parameters:
Name | Type | Description | Default |
---|---|---|---|
schema |
CoreSchema
|
The schema to use for the custom error schema |
required |
custom_error_type |
str
|
The custom error type to use for the custom error schema |
required |
custom_error_message |
str | None
|
The custom error message to use for the custom error schema |
None
|
custom_error_context |
dict[str, Any] | None
|
The custom error context to use for the custom error schema |
None
|
ref |
str | None
|
optional unique identifier of the schema, used to reference the schema in other places |
None
|
metadata |
Dict[str, Any] | None
|
Any other information you want to include with the schema, not used by pydantic-core |
None
|
serialization |
SerSchema | None
|
Custom serialization schema |
None
|
Source code in .venv/lib/python3.10/site-packages/pydantic_core/core_schema.py
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|
json_schema ¶
json_schema(
schema: CoreSchema | None = None,
*,
ref: str | None = None,
metadata: Dict[str, Any] | None = None,
serialization: SerSchema | None = None
) -> JsonSchema
Returns a schema that matches a JSON value, e.g.:
from pydantic_core import SchemaValidator, core_schema
dict_schema = core_schema.model_fields_schema(
{
'field_a': core_schema.model_field(core_schema.str_schema()),
'field_b': core_schema.model_field(core_schema.bool_schema()),
},
)
class MyModel:
__slots__ = (
'__dict__',
'__pydantic_fields_set__',
'__pydantic_extra__',
'__pydantic_private__',
)
field_a: str
field_b: bool
json_schema = core_schema.json_schema(schema=dict_schema)
schema = core_schema.model_schema(cls=MyModel, schema=json_schema)
v = SchemaValidator(schema)
m = v.validate_python('{"field_a": "hello", "field_b": true}')
assert isinstance(m, MyModel)
Parameters:
Name | Type | Description | Default |
---|---|---|---|
schema |
CoreSchema | None
|
The schema to use for the JSON schema |
None
|
ref |
str | None
|
optional unique identifier of the schema, used to reference the schema in other places |
None
|
metadata |
Dict[str, Any] | None
|
Any other information you want to include with the schema, not used by pydantic-core |
None
|
serialization |
SerSchema | None
|
Custom serialization schema |
None
|
Source code in .venv/lib/python3.10/site-packages/pydantic_core/core_schema.py
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|
url_schema ¶
url_schema(
*,
max_length: int | None = None,
allowed_schemes: list[str] | None = None,
host_required: bool | None = None,
default_host: str | None = None,
default_port: int | None = None,
default_path: str | None = None,
strict: bool | None = None,
ref: str | None = None,
metadata: Dict[str, Any] | None = None,
serialization: SerSchema | None = None
) -> UrlSchema
Returns a schema that matches a URL value, e.g.:
from pydantic_core import SchemaValidator, core_schema
schema = core_schema.url_schema()
v = SchemaValidator(schema)
print(v.validate_python('https://example.com'))
#> https://example.com/
Parameters:
Name | Type | Description | Default |
---|---|---|---|
max_length |
int | None
|
The maximum length of the URL |
None
|
allowed_schemes |
list[str] | None
|
The allowed URL schemes |
None
|
host_required |
bool | None
|
Whether the URL must have a host |
None
|
default_host |
str | None
|
The default host to use if the URL does not have a host |
None
|
default_port |
int | None
|
The default port to use if the URL does not have a port |
None
|
default_path |
str | None
|
The default path to use if the URL does not have a path |
None
|
strict |
bool | None
|
Whether to use strict URL parsing |
None
|
ref |
str | None
|
optional unique identifier of the schema, used to reference the schema in other places |
None
|
metadata |
Dict[str, Any] | None
|
Any other information you want to include with the schema, not used by pydantic-core |
None
|
serialization |
SerSchema | None
|
Custom serialization schema |
None
|
Source code in .venv/lib/python3.10/site-packages/pydantic_core/core_schema.py
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|
multi_host_url_schema ¶
multi_host_url_schema(
*,
max_length: int | None = None,
allowed_schemes: list[str] | None = None,
host_required: bool | None = None,
default_host: str | None = None,
default_port: int | None = None,
default_path: str | None = None,
strict: bool | None = None,
ref: str | None = None,
metadata: Dict[str, Any] | None = None,
serialization: SerSchema | None = None
) -> MultiHostUrlSchema
Returns a schema that matches a URL value with possibly multiple hosts, e.g.:
from pydantic_core import SchemaValidator, core_schema
schema = core_schema.multi_host_url_schema()
v = SchemaValidator(schema)
print(v.validate_python('redis://localhost,0.0.0.0,127.0.0.1'))
#> redis://localhost,0.0.0.0,127.0.0.1
Parameters:
Name | Type | Description | Default |
---|---|---|---|
max_length |
int | None
|
The maximum length of the URL |
None
|
allowed_schemes |
list[str] | None
|
The allowed URL schemes |
None
|
host_required |
bool | None
|
Whether the URL must have a host |
None
|
default_host |
str | None
|
The default host to use if the URL does not have a host |
None
|
default_port |
int | None
|
The default port to use if the URL does not have a port |
None
|
default_path |
str | None
|
The default path to use if the URL does not have a path |
None
|
strict |
bool | None
|
Whether to use strict URL parsing |
None
|
ref |
str | None
|
optional unique identifier of the schema, used to reference the schema in other places |
None
|
metadata |
Dict[str, Any] | None
|
Any other information you want to include with the schema, not used by pydantic-core |
None
|
serialization |
SerSchema | None
|
Custom serialization schema |
None
|
Source code in .venv/lib/python3.10/site-packages/pydantic_core/core_schema.py
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|
definitions_schema ¶
definitions_schema(
schema: CoreSchema, definitions: list[CoreSchema]
) -> DefinitionsSchema
Build a schema that contains both an inner schema and a list of definitions which can be used within the inner schema.
from pydantic_core import SchemaValidator, core_schema
schema = core_schema.definitions_schema(
core_schema.list_schema(core_schema.definition_reference_schema('foobar')),
[core_schema.int_schema(ref='foobar')],
)
v = SchemaValidator(schema)
assert v.validate_python([1, 2, '3']) == [1, 2, 3]
Parameters:
Name | Type | Description | Default |
---|---|---|---|
schema |
CoreSchema
|
The inner schema |
required |
definitions |
list[CoreSchema]
|
List of definitions which can be referenced within inner schema |
required |
Source code in .venv/lib/python3.10/site-packages/pydantic_core/core_schema.py
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|
definition_reference_schema ¶
definition_reference_schema(
schema_ref: str,
ref: str | None = None,
metadata: Dict[str, Any] | None = None,
serialization: SerSchema | None = None,
) -> DefinitionReferenceSchema
Returns a schema that points to a schema stored in "definitions", this is useful for nested recursive models and also when you want to define validators separately from the main schema, e.g.:
from pydantic_core import SchemaValidator, core_schema
schema_definition = core_schema.definition_reference_schema('list-schema')
schema = core_schema.definitions_schema(
schema=schema_definition,
definitions=[
core_schema.list_schema(items_schema=schema_definition, ref='list-schema'),
],
)
v = SchemaValidator(schema)
assert v.validate_python([()]) == [[]]
Parameters:
Name | Type | Description | Default |
---|---|---|---|
schema_ref |
str
|
The schema ref to use for the definition reference schema |
required |
metadata |
Dict[str, Any] | None
|
Any other information you want to include with the schema, not used by pydantic-core |
None
|
serialization |
SerSchema | None
|
Custom serialization schema |
None
|
Source code in .venv/lib/python3.10/site-packages/pydantic_core/core_schema.py
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|