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authorS. Solomon Darnell2025-03-28 21:52:21 -0500
committerS. Solomon Darnell2025-03-28 21:52:21 -0500
commit4a52a71956a8d46fcb7294ac71734504bb09bcc2 (patch)
treeee3dc5af3b6313e921cd920906356f5d4febc4ed /.venv/lib/python3.12/site-packages/pydantic/_internal/_known_annotated_metadata.py
parentcc961e04ba734dd72309fb548a2f97d67d578813 (diff)
downloadgn-ai-master.tar.gz
two version of R2R are hereHEADmaster
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+from __future__ import annotations
+
+from collections import defaultdict
+from copy import copy
+from functools import lru_cache, partial
+from typing import TYPE_CHECKING, Any, Iterable
+
+from pydantic_core import CoreSchema, PydanticCustomError, ValidationError, to_jsonable_python
+from pydantic_core import core_schema as cs
+
+from ._fields import PydanticMetadata
+from ._import_utils import import_cached_field_info
+
+if TYPE_CHECKING:
+ pass
+
+STRICT = {'strict'}
+FAIL_FAST = {'fail_fast'}
+LENGTH_CONSTRAINTS = {'min_length', 'max_length'}
+INEQUALITY = {'le', 'ge', 'lt', 'gt'}
+NUMERIC_CONSTRAINTS = {'multiple_of', *INEQUALITY}
+ALLOW_INF_NAN = {'allow_inf_nan'}
+
+STR_CONSTRAINTS = {
+ *LENGTH_CONSTRAINTS,
+ *STRICT,
+ 'strip_whitespace',
+ 'to_lower',
+ 'to_upper',
+ 'pattern',
+ 'coerce_numbers_to_str',
+}
+BYTES_CONSTRAINTS = {*LENGTH_CONSTRAINTS, *STRICT}
+
+LIST_CONSTRAINTS = {*LENGTH_CONSTRAINTS, *STRICT, *FAIL_FAST}
+TUPLE_CONSTRAINTS = {*LENGTH_CONSTRAINTS, *STRICT, *FAIL_FAST}
+SET_CONSTRAINTS = {*LENGTH_CONSTRAINTS, *STRICT, *FAIL_FAST}
+DICT_CONSTRAINTS = {*LENGTH_CONSTRAINTS, *STRICT}
+GENERATOR_CONSTRAINTS = {*LENGTH_CONSTRAINTS, *STRICT}
+SEQUENCE_CONSTRAINTS = {*LENGTH_CONSTRAINTS, *FAIL_FAST}
+
+FLOAT_CONSTRAINTS = {*NUMERIC_CONSTRAINTS, *ALLOW_INF_NAN, *STRICT}
+DECIMAL_CONSTRAINTS = {'max_digits', 'decimal_places', *FLOAT_CONSTRAINTS}
+INT_CONSTRAINTS = {*NUMERIC_CONSTRAINTS, *ALLOW_INF_NAN, *STRICT}
+BOOL_CONSTRAINTS = STRICT
+UUID_CONSTRAINTS = STRICT
+
+DATE_TIME_CONSTRAINTS = {*NUMERIC_CONSTRAINTS, *STRICT}
+TIMEDELTA_CONSTRAINTS = {*NUMERIC_CONSTRAINTS, *STRICT}
+TIME_CONSTRAINTS = {*NUMERIC_CONSTRAINTS, *STRICT}
+LAX_OR_STRICT_CONSTRAINTS = STRICT
+ENUM_CONSTRAINTS = STRICT
+COMPLEX_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)
+
+constraint_schema_pairings: list[tuple[set[str], tuple[str, ...]]] = [
+ (STR_CONSTRAINTS, TEXT_SCHEMA_TYPES),
+ (BYTES_CONSTRAINTS, ('bytes',)),
+ (LIST_CONSTRAINTS, ('list',)),
+ (TUPLE_CONSTRAINTS, ('tuple',)),
+ (SET_CONSTRAINTS, ('set', 'frozenset')),
+ (DICT_CONSTRAINTS, ('dict',)),
+ (GENERATOR_CONSTRAINTS, ('generator',)),
+ (FLOAT_CONSTRAINTS, ('float',)),
+ (INT_CONSTRAINTS, ('int',)),
+ (DATE_TIME_CONSTRAINTS, ('date', 'time', 'datetime', 'timedelta')),
+ # TODO: this is a bit redundant, we could probably avoid some of these
+ (STRICT, (*TEXT_SCHEMA_TYPES, *SEQUENCE_SCHEMA_TYPES, *NUMERIC_SCHEMA_TYPES, 'typed-dict', 'model')),
+ (UNION_CONSTRAINTS, ('union',)),
+ (URL_CONSTRAINTS, ('url', 'multi-host-url')),
+ (BOOL_CONSTRAINTS, ('bool',)),
+ (UUID_CONSTRAINTS, ('uuid',)),
+ (LAX_OR_STRICT_CONSTRAINTS, ('lax-or-strict',)),
+ (ENUM_CONSTRAINTS, ('enum',)),
+ (DECIMAL_CONSTRAINTS, ('decimal',)),
+ (COMPLEX_CONSTRAINTS, ('complex',)),
+]
+
+for constraints, schemas in constraint_schema_pairings:
+ for c in constraints:
+ CONSTRAINTS_TO_ALLOWED_SCHEMAS[c].update(schemas)
+
+
+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:
+ ```python
+ 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)]
+ ```
+ """
+ import annotated_types as at
+
+ FieldInfo = import_cached_field_info()
+
+ 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
+
+
+@lru_cache
+def _get_at_to_constraint_map() -> dict[type, str]:
+ """Return a mapping of annotated types to constraints.
+
+ Normally, we would define a mapping like this in the module scope, but we can't do that
+ because we don't permit module level imports of `annotated_types`, in an attempt to speed up
+ the import time of `pydantic`. We still only want to have this dictionary defined in one place,
+ so we use this function to cache the result.
+ """
+ import annotated_types as at
+
+ return {
+ at.Gt: 'gt',
+ at.Ge: 'ge',
+ at.Lt: 'lt',
+ at.Le: 'le',
+ at.MultipleOf: 'multiple_of',
+ at.MinLen: 'min_length',
+ at.MaxLen: 'max_length',
+ }
+
+
+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.
+ """
+ import annotated_types as at
+
+ from ._validators import NUMERIC_VALIDATOR_LOOKUP, forbid_inf_nan_check
+
+ schema = schema.copy()
+ schema_update, other_metadata = collect_known_metadata([annotation])
+ schema_type = schema['type']
+
+ chain_schema_constraints: set[str] = {
+ 'pattern',
+ 'strip_whitespace',
+ 'to_lower',
+ 'to_upper',
+ 'coerce_numbers_to_str',
+ }
+ chain_schema_steps: list[CoreSchema] = []
+
+ 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 it becomes necessary to handle more than one constraint
+ # in this recursive case with function-after or function-wrap, we should refactor
+ # this is a bit challenging because we sometimes want to apply constraints to the inner schema,
+ # whereas other times we want to wrap the existing schema with a new one that enforces a new constraint.
+ if schema_type in {'function-before', 'function-wrap', 'function-after'} and constraint == 'strict':
+ schema['schema'] = apply_known_metadata(annotation, schema['schema']) # type: ignore # schema is function schema
+ return schema
+
+ # if we're allowed to apply constraint directly to the schema, like le to int, do that
+ 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
+
+ # else, apply a function after validator to the schema to enforce the corresponding constraint
+ if constraint in chain_schema_constraints:
+
+ def _apply_constraint_with_incompatibility_info(
+ value: Any, handler: cs.ValidatorFunctionWrapHandler
+ ) -> Any:
+ try:
+ x = handler(value)
+ except ValidationError as ve:
+ # if the error is about the type, it's likely that the constraint is incompatible the type of the field
+ # for example, the following invalid schema wouldn't be caught during schema build, but rather at this point
+ # with a cryptic 'string_type' error coming from the string validator,
+ # that we'd rather express as a constraint incompatibility error (TypeError)
+ # Annotated[list[int], Field(pattern='abc')]
+ if 'type' in ve.errors()[0]['type']:
+ raise TypeError(
+ f"Unable to apply constraint '{constraint}' to supplied value {value} for schema of type '{schema_type}'" # noqa: B023
+ )
+ raise ve
+ return x
+
+ chain_schema_steps.append(
+ cs.no_info_wrap_validator_function(
+ _apply_constraint_with_incompatibility_info, cs.str_schema(**{constraint: value})
+ )
+ )
+ elif constraint in NUMERIC_VALIDATOR_LOOKUP:
+ if constraint in LENGTH_CONSTRAINTS:
+ inner_schema = schema
+ while inner_schema['type'] in {'function-before', 'function-wrap', 'function-after'}:
+ inner_schema = inner_schema['schema'] # type: ignore
+ inner_schema_type = inner_schema['type']
+ if inner_schema_type == 'list' or (
+ inner_schema_type == 'json-or-python' and inner_schema['json_schema']['type'] == 'list' # type: ignore
+ ):
+ js_constraint_key = 'minItems' if constraint == 'min_length' else 'maxItems'
+ else:
+ js_constraint_key = 'minLength' if constraint == 'min_length' else 'maxLength'
+ else:
+ js_constraint_key = constraint
+
+ schema = cs.no_info_after_validator_function(
+ partial(NUMERIC_VALIDATOR_LOOKUP[constraint], **{constraint: value}), schema
+ )
+ metadata = schema.get('metadata', {})
+ if (existing_json_schema_updates := metadata.get('pydantic_js_updates')) is not None:
+ metadata['pydantic_js_updates'] = {
+ **existing_json_schema_updates,
+ **{js_constraint_key: as_jsonable_value(value)},
+ }
+ else:
+ metadata['pydantic_js_updates'] = {js_constraint_key: as_jsonable_value(value)}
+ schema['metadata'] = metadata
+ elif constraint == 'allow_inf_nan' and value is False:
+ schema = cs.no_info_after_validator_function(
+ forbid_inf_nan_check,
+ schema,
+ )
+ else:
+ # It's rare that we'd get here, but it's possible if we add a new constraint and forget to handle it
+ # Most constraint errors are caught at runtime during attempted application
+ raise RuntimeError(f"Unable to apply constraint '{constraint}' to schema of type '{schema_type}'")
+
+ for annotation in other_metadata:
+ if (annotation_type := type(annotation)) in (at_to_constraint_map := _get_at_to_constraint_map()):
+ constraint = at_to_constraint_map[annotation_type]
+ validator = NUMERIC_VALIDATOR_LOOKUP.get(constraint)
+ if validator is None:
+ raise ValueError(f'Unknown constraint {constraint}')
+ schema = cs.no_info_after_validator_function(
+ partial(validator, {constraint: getattr(annotation, constraint)}), schema
+ )
+ continue
+ elif isinstance(annotation, (at.Predicate, at.Not)):
+ predicate_name = f'{annotation.func.__qualname__}' if hasattr(annotation.func, '__qualname__') else ''
+
+ def val_func(v: Any) -> Any:
+ predicate_satisfied = annotation.func(v) # noqa: B023
+
+ # annotation.func may also raise an exception, let it pass through
+ if isinstance(annotation, at.Predicate): # noqa: B023
+ if not predicate_satisfied:
+ raise PydanticCustomError(
+ 'predicate_failed',
+ f'Predicate {predicate_name} failed', # type: ignore # noqa: B023
+ )
+ else:
+ if predicate_satisfied:
+ raise PydanticCustomError(
+ 'not_operation_failed',
+ f'Not of {predicate_name} failed', # type: ignore # noqa: B023
+ )
+
+ return v
+
+ schema = cs.no_info_after_validator_function(val_func, schema)
+ else:
+ # ignore any other unknown metadata
+ return None
+
+ if chain_schema_steps:
+ chain_schema_steps = [schema] + chain_schema_steps
+ return cs.chain_schema(chain_schema_steps)
+
+ 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:
+ ```python
+ 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:
+ # isinstance(annotation, PydanticMetadata) also covers ._fields:_PydanticGeneralMetadata
+ if isinstance(annotation, PydanticMetadata):
+ res.update(annotation.__dict__)
+ # we don't use dataclasses.asdict because that recursively calls asdict on the field values
+ elif (annotation_type := type(annotation)) in (at_to_constraint_map := _get_at_to_constraint_map()):
+ constraint = at_to_constraint_map[annotation_type]
+ res[constraint] = getattr(annotation, constraint)
+ 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])}'
+ )