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author | S. Solomon Darnell | 2025-03-28 21:52:21 -0500 |
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committer | S. Solomon Darnell | 2025-03-28 21:52:21 -0500 |
commit | 4a52a71956a8d46fcb7294ac71734504bb09bcc2 (patch) | |
tree | ee3dc5af3b6313e921cd920906356f5d4febc4ed /.venv/lib/python3.12/site-packages/pydantic/_internal/_known_annotated_metadata.py | |
parent | cc961e04ba734dd72309fb548a2f97d67d578813 (diff) | |
download | gn-ai-master.tar.gz |
Diffstat (limited to '.venv/lib/python3.12/site-packages/pydantic/_internal/_known_annotated_metadata.py')
-rw-r--r-- | .venv/lib/python3.12/site-packages/pydantic/_internal/_known_annotated_metadata.py | 392 |
1 files changed, 392 insertions, 0 deletions
diff --git a/.venv/lib/python3.12/site-packages/pydantic/_internal/_known_annotated_metadata.py b/.venv/lib/python3.12/site-packages/pydantic/_internal/_known_annotated_metadata.py new file mode 100644 index 00000000..78de89ec --- /dev/null +++ b/.venv/lib/python3.12/site-packages/pydantic/_internal/_known_annotated_metadata.py @@ -0,0 +1,392 @@ +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])}' + ) |