AlkantarClanX12
Your IP : 3.145.8.139
from __future__ import annotations
from collections import defaultdict
from copy import copy
from functools import partial
from typing import TYPE_CHECKING, Any, Callable, Iterable
import annotated_types as at
from pydantic_core import CoreSchema, PydanticCustomError, to_jsonable_python
from pydantic_core import core_schema as cs
from . import _validators
from ._fields import PydanticGeneralMetadata, PydanticMetadata
if TYPE_CHECKING:
from ..annotated_handlers import GetJsonSchemaHandler
STRICT = {'strict'}
SEQUENCE_CONSTRAINTS = {'min_length', 'max_length'}
INEQUALITY = {'le', 'ge', 'lt', 'gt'}
NUMERIC_CONSTRAINTS = {'multiple_of', 'allow_inf_nan', *INEQUALITY}
STR_CONSTRAINTS = {*SEQUENCE_CONSTRAINTS, *STRICT, 'strip_whitespace', 'to_lower', 'to_upper', 'pattern'}
BYTES_CONSTRAINTS = {*SEQUENCE_CONSTRAINTS, *STRICT}
LIST_CONSTRAINTS = {*SEQUENCE_CONSTRAINTS, *STRICT}
TUPLE_CONSTRAINTS = {*SEQUENCE_CONSTRAINTS, *STRICT}
SET_CONSTRAINTS = {*SEQUENCE_CONSTRAINTS, *STRICT}
DICT_CONSTRAINTS = {*SEQUENCE_CONSTRAINTS, *STRICT}
GENERATOR_CONSTRAINTS = {*SEQUENCE_CONSTRAINTS, *STRICT}
FLOAT_CONSTRAINTS = {*NUMERIC_CONSTRAINTS, *STRICT}
INT_CONSTRAINTS = {*NUMERIC_CONSTRAINTS, *STRICT}
BOOL_CONSTRAINTS = STRICT
DATE_TIME_CONSTRAINTS = {*NUMERIC_CONSTRAINTS, *STRICT}
TIMEDELTA_CONSTRAINTS = {*NUMERIC_CONSTRAINTS, *STRICT}
TIME_CONSTRAINTS = {*NUMERIC_CONSTRAINTS, *STRICT}
UNION_CONSTRAINTS = {'union_mode'}
URL_CONSTRAINTS = {
'max_length',
'allowed_schemes',
'host_required',
'default_host',
'default_port',
'default_path',
}
TEXT_SCHEMA_TYPES = ('str', 'bytes', 'url', 'multi-host-url')
SEQUENCE_SCHEMA_TYPES = ('list', 'tuple', 'set', 'frozenset', 'generator', *TEXT_SCHEMA_TYPES)
NUMERIC_SCHEMA_TYPES = ('float', 'int', 'date', 'time', 'timedelta', 'datetime')
CONSTRAINTS_TO_ALLOWED_SCHEMAS: dict[str, set[str]] = defaultdict(set)
for constraint in STR_CONSTRAINTS:
CONSTRAINTS_TO_ALLOWED_SCHEMAS[constraint].update(TEXT_SCHEMA_TYPES)
for constraint in BYTES_CONSTRAINTS:
CONSTRAINTS_TO_ALLOWED_SCHEMAS[constraint].update(('bytes',))
for constraint in LIST_CONSTRAINTS:
CONSTRAINTS_TO_ALLOWED_SCHEMAS[constraint].update(('list',))
for constraint in TUPLE_CONSTRAINTS:
CONSTRAINTS_TO_ALLOWED_SCHEMAS[constraint].update(('tuple',))
for constraint in SET_CONSTRAINTS:
CONSTRAINTS_TO_ALLOWED_SCHEMAS[constraint].update(('set', 'frozenset'))
for constraint in DICT_CONSTRAINTS:
CONSTRAINTS_TO_ALLOWED_SCHEMAS[constraint].update(('dict',))
for constraint in GENERATOR_CONSTRAINTS:
CONSTRAINTS_TO_ALLOWED_SCHEMAS[constraint].update(('generator',))
for constraint in FLOAT_CONSTRAINTS:
CONSTRAINTS_TO_ALLOWED_SCHEMAS[constraint].update(('float',))
for constraint in INT_CONSTRAINTS:
CONSTRAINTS_TO_ALLOWED_SCHEMAS[constraint].update(('int',))
for constraint in DATE_TIME_CONSTRAINTS:
CONSTRAINTS_TO_ALLOWED_SCHEMAS[constraint].update(('date', 'time', 'datetime'))
for constraint in TIMEDELTA_CONSTRAINTS:
CONSTRAINTS_TO_ALLOWED_SCHEMAS[constraint].update(('timedelta',))
for constraint in TIME_CONSTRAINTS:
CONSTRAINTS_TO_ALLOWED_SCHEMAS[constraint].update(('time',))
for schema_type in (*TEXT_SCHEMA_TYPES, *SEQUENCE_SCHEMA_TYPES, *NUMERIC_SCHEMA_TYPES, 'typed-dict', 'model'):
CONSTRAINTS_TO_ALLOWED_SCHEMAS['strict'].add(schema_type)
for constraint in UNION_CONSTRAINTS:
CONSTRAINTS_TO_ALLOWED_SCHEMAS[constraint].update(('union',))
for constraint in URL_CONSTRAINTS:
CONSTRAINTS_TO_ALLOWED_SCHEMAS[constraint].update(('url', 'multi-host-url'))
for constraint in BOOL_CONSTRAINTS:
CONSTRAINTS_TO_ALLOWED_SCHEMAS[constraint].update(('bool',))
def add_js_update_schema(s: cs.CoreSchema, f: Callable[[], dict[str, Any]]) -> None:
def update_js_schema(s: cs.CoreSchema, handler: GetJsonSchemaHandler) -> dict[str, Any]:
js_schema = handler(s)
js_schema.update(f())
return js_schema
if 'metadata' in s:
metadata = s['metadata']
if 'pydantic_js_functions' in s:
metadata['pydantic_js_functions'].append(update_js_schema)
else:
metadata['pydantic_js_functions'] = [update_js_schema]
else:
s['metadata'] = {'pydantic_js_functions': [update_js_schema]}
def as_jsonable_value(v: Any) -> Any:
if type(v) not in (int, str, float, bytes, bool, type(None)):
return to_jsonable_python(v)
return v
def expand_grouped_metadata(annotations: Iterable[Any]) -> Iterable[Any]:
"""Expand the annotations.
Args:
annotations: An iterable of annotations.
Returns:
An iterable of expanded annotations.
Example:
```py
from annotated_types import Ge, Len
from pydantic._internal._known_annotated_metadata import expand_grouped_metadata
print(list(expand_grouped_metadata([Ge(4), Len(5)])))
#> [Ge(ge=4), MinLen(min_length=5)]
```
"""
from pydantic.fields import FieldInfo # circular import
for annotation in annotations:
if isinstance(annotation, at.GroupedMetadata):
yield from annotation
elif isinstance(annotation, FieldInfo):
yield from annotation.metadata
# this is a bit problematic in that it results in duplicate metadata
# all of our "consumers" can handle it, but it is not ideal
# we probably should split up FieldInfo into:
# - annotated types metadata
# - individual metadata known only to Pydantic
annotation = copy(annotation)
annotation.metadata = []
yield annotation
else:
yield annotation
def apply_known_metadata(annotation: Any, schema: CoreSchema) -> CoreSchema | None: # noqa: C901
"""Apply `annotation` to `schema` if it is an annotation we know about (Gt, Le, etc.).
Otherwise return `None`.
This does not handle all known annotations. If / when it does, it can always
return a CoreSchema and return the unmodified schema if the annotation should be ignored.
Assumes that GroupedMetadata has already been expanded via `expand_grouped_metadata`.
Args:
annotation: The annotation.
schema: The schema.
Returns:
An updated schema with annotation if it is an annotation we know about, `None` otherwise.
Raises:
PydanticCustomError: If `Predicate` fails.
"""
schema = schema.copy()
schema_update, other_metadata = collect_known_metadata([annotation])
schema_type = schema['type']
for constraint, value in schema_update.items():
if constraint not in CONSTRAINTS_TO_ALLOWED_SCHEMAS:
raise ValueError(f'Unknown constraint {constraint}')
allowed_schemas = CONSTRAINTS_TO_ALLOWED_SCHEMAS[constraint]
if schema_type in allowed_schemas:
if constraint == 'union_mode' and schema_type == 'union':
schema['mode'] = value # type: ignore # schema is UnionSchema
else:
schema[constraint] = value
continue
if constraint == 'allow_inf_nan' and value is False:
return cs.no_info_after_validator_function(
_validators.forbid_inf_nan_check,
schema,
)
elif constraint == 'pattern':
# insert a str schema to make sure the regex engine matches
return cs.chain_schema(
[
schema,
cs.str_schema(pattern=value),
]
)
elif constraint == 'gt':
s = cs.no_info_after_validator_function(
partial(_validators.greater_than_validator, gt=value),
schema,
)
add_js_update_schema(s, lambda: {'gt': as_jsonable_value(value)})
return s
elif constraint == 'ge':
return cs.no_info_after_validator_function(
partial(_validators.greater_than_or_equal_validator, ge=value),
schema,
)
elif constraint == 'lt':
return cs.no_info_after_validator_function(
partial(_validators.less_than_validator, lt=value),
schema,
)
elif constraint == 'le':
return cs.no_info_after_validator_function(
partial(_validators.less_than_or_equal_validator, le=value),
schema,
)
elif constraint == 'multiple_of':
return cs.no_info_after_validator_function(
partial(_validators.multiple_of_validator, multiple_of=value),
schema,
)
elif constraint == 'min_length':
s = cs.no_info_after_validator_function(
partial(_validators.min_length_validator, min_length=value),
schema,
)
add_js_update_schema(s, lambda: {'minLength': (as_jsonable_value(value))})
return s
elif constraint == 'max_length':
s = cs.no_info_after_validator_function(
partial(_validators.max_length_validator, max_length=value),
schema,
)
add_js_update_schema(s, lambda: {'maxLength': (as_jsonable_value(value))})
return s
elif constraint == 'strip_whitespace':
return cs.chain_schema(
[
schema,
cs.str_schema(strip_whitespace=True),
]
)
elif constraint == 'to_lower':
return cs.chain_schema(
[
schema,
cs.str_schema(to_lower=True),
]
)
elif constraint == 'to_upper':
return cs.chain_schema(
[
schema,
cs.str_schema(to_upper=True),
]
)
elif constraint == 'min_length':
return cs.no_info_after_validator_function(
partial(_validators.min_length_validator, min_length=annotation.min_length),
schema,
)
elif constraint == 'max_length':
return cs.no_info_after_validator_function(
partial(_validators.max_length_validator, max_length=annotation.max_length),
schema,
)
else:
raise RuntimeError(f'Unable to apply constraint {constraint} to schema {schema_type}')
for annotation in other_metadata:
if isinstance(annotation, at.Gt):
return cs.no_info_after_validator_function(
partial(_validators.greater_than_validator, gt=annotation.gt),
schema,
)
elif isinstance(annotation, at.Ge):
return cs.no_info_after_validator_function(
partial(_validators.greater_than_or_equal_validator, ge=annotation.ge),
schema,
)
elif isinstance(annotation, at.Lt):
return cs.no_info_after_validator_function(
partial(_validators.less_than_validator, lt=annotation.lt),
schema,
)
elif isinstance(annotation, at.Le):
return cs.no_info_after_validator_function(
partial(_validators.less_than_or_equal_validator, le=annotation.le),
schema,
)
elif isinstance(annotation, at.MultipleOf):
return cs.no_info_after_validator_function(
partial(_validators.multiple_of_validator, multiple_of=annotation.multiple_of),
schema,
)
elif isinstance(annotation, at.MinLen):
return cs.no_info_after_validator_function(
partial(_validators.min_length_validator, min_length=annotation.min_length),
schema,
)
elif isinstance(annotation, at.MaxLen):
return cs.no_info_after_validator_function(
partial(_validators.max_length_validator, max_length=annotation.max_length),
schema,
)
elif isinstance(annotation, at.Predicate):
predicate_name = f'{annotation.func.__qualname__} ' if hasattr(annotation.func, '__qualname__') else ''
def val_func(v: Any) -> Any:
# annotation.func may also raise an exception, let it pass through
if not annotation.func(v):
raise PydanticCustomError(
'predicate_failed',
f'Predicate {predicate_name}failed', # type: ignore
)
return v
return cs.no_info_after_validator_function(val_func, schema)
# ignore any other unknown metadata
return None
return schema
def collect_known_metadata(annotations: Iterable[Any]) -> tuple[dict[str, Any], list[Any]]:
"""Split `annotations` into known metadata and unknown annotations.
Args:
annotations: An iterable of annotations.
Returns:
A tuple contains a dict of known metadata and a list of unknown annotations.
Example:
```py
from annotated_types import Gt, Len
from pydantic._internal._known_annotated_metadata import collect_known_metadata
print(collect_known_metadata([Gt(1), Len(42), ...]))
#> ({'gt': 1, 'min_length': 42}, [Ellipsis])
```
"""
annotations = expand_grouped_metadata(annotations)
res: dict[str, Any] = {}
remaining: list[Any] = []
for annotation in annotations:
# Do we really want to consume any `BaseMetadata`?
# It does let us give a better error when there is an annotation that doesn't apply
# But it seems dangerous!
if isinstance(annotation, PydanticGeneralMetadata):
res.update(annotation.__dict__)
elif isinstance(annotation, PydanticMetadata):
res.update(annotation.__dict__)
# we don't use dataclasses.asdict because that recursively calls asdict on the field values
elif isinstance(annotation, at.MinLen):
res.update({'min_length': annotation.min_length})
elif isinstance(annotation, at.MaxLen):
res.update({'max_length': annotation.max_length})
elif isinstance(annotation, at.Gt):
res.update({'gt': annotation.gt})
elif isinstance(annotation, at.Ge):
res.update({'ge': annotation.ge})
elif isinstance(annotation, at.Lt):
res.update({'lt': annotation.lt})
elif isinstance(annotation, at.Le):
res.update({'le': annotation.le})
elif isinstance(annotation, at.MultipleOf):
res.update({'multiple_of': annotation.multiple_of})
elif isinstance(annotation, type) and issubclass(annotation, PydanticMetadata):
# also support PydanticMetadata classes being used without initialisation,
# e.g. `Annotated[int, Strict]` as well as `Annotated[int, Strict()]`
res.update({k: v for k, v in vars(annotation).items() if not k.startswith('_')})
else:
remaining.append(annotation)
# Nones can sneak in but pydantic-core will reject them
# it'd be nice to clean things up so we don't put in None (we probably don't _need_ to, it was just easier)
# but this is simple enough to kick that can down the road
res = {k: v for k, v in res.items() if v is not None}
return res, remaining
def check_metadata(metadata: dict[str, Any], allowed: Iterable[str], source_type: Any) -> None:
"""A small utility function to validate that the given metadata can be applied to the target.
More than saving lines of code, this gives us a consistent error message for all of our internal implementations.
Args:
metadata: A dict of metadata.
allowed: An iterable of allowed metadata.
source_type: The source type.
Raises:
TypeError: If there is metadatas that can't be applied on source type.
"""
unknown = metadata.keys() - set(allowed)
if unknown:
raise TypeError(
f'The following constraints cannot be applied to {source_type!r}: {", ".join([f"{k!r}" for k in unknown])}'
)