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| Dir : //proc/self/root/opt/saltstack/salt/lib/python3.10/site-packages/pydantic/_internal/_core_utils.py |
from __future__ import annotations
import os
from collections import defaultdict
from typing import (
Any,
Callable,
Hashable,
TypeVar,
Union,
)
from pydantic_core import CoreSchema, core_schema
from pydantic_core import validate_core_schema as _validate_core_schema
from typing_extensions import TypeAliasType, TypeGuard, get_args, get_origin
from . import _repr
from ._typing_extra import is_generic_alias
AnyFunctionSchema = Union[
core_schema.AfterValidatorFunctionSchema,
core_schema.BeforeValidatorFunctionSchema,
core_schema.WrapValidatorFunctionSchema,
core_schema.PlainValidatorFunctionSchema,
]
FunctionSchemaWithInnerSchema = Union[
core_schema.AfterValidatorFunctionSchema,
core_schema.BeforeValidatorFunctionSchema,
core_schema.WrapValidatorFunctionSchema,
]
CoreSchemaField = Union[
core_schema.ModelField, core_schema.DataclassField, core_schema.TypedDictField, core_schema.ComputedField
]
CoreSchemaOrField = Union[core_schema.CoreSchema, CoreSchemaField]
_CORE_SCHEMA_FIELD_TYPES = {'typed-dict-field', 'dataclass-field', 'model-field', 'computed-field'}
_FUNCTION_WITH_INNER_SCHEMA_TYPES = {'function-before', 'function-after', 'function-wrap'}
_LIST_LIKE_SCHEMA_WITH_ITEMS_TYPES = {'list', 'set', 'frozenset'}
_DEFINITIONS_CACHE_METADATA_KEY = 'pydantic.definitions_cache'
TAGGED_UNION_TAG_KEY = 'pydantic.internal.tagged_union_tag'
"""
Used in a `Tag` schema to specify the tag used for a discriminated union.
"""
HAS_INVALID_SCHEMAS_METADATA_KEY = 'pydantic.internal.invalid'
"""Used to mark a schema that is invalid because it refers to a definition that was not yet defined when the
schema was first encountered.
"""
def is_core_schema(
schema: CoreSchemaOrField,
) -> TypeGuard[CoreSchema]:
return schema['type'] not in _CORE_SCHEMA_FIELD_TYPES
def is_core_schema_field(
schema: CoreSchemaOrField,
) -> TypeGuard[CoreSchemaField]:
return schema['type'] in _CORE_SCHEMA_FIELD_TYPES
def is_function_with_inner_schema(
schema: CoreSchemaOrField,
) -> TypeGuard[FunctionSchemaWithInnerSchema]:
return schema['type'] in _FUNCTION_WITH_INNER_SCHEMA_TYPES
def is_list_like_schema_with_items_schema(
schema: CoreSchema,
) -> TypeGuard[core_schema.ListSchema | core_schema.SetSchema | core_schema.FrozenSetSchema]:
return schema['type'] in _LIST_LIKE_SCHEMA_WITH_ITEMS_TYPES
def get_type_ref(type_: type[Any], args_override: tuple[type[Any], ...] | None = None) -> str:
"""Produces the ref to be used for this type by pydantic_core's core schemas.
This `args_override` argument was added for the purpose of creating valid recursive references
when creating generic models without needing to create a concrete class.
"""
origin = get_origin(type_) or type_
args = get_args(type_) if is_generic_alias(type_) else (args_override or ())
generic_metadata = getattr(type_, '__pydantic_generic_metadata__', None)
if generic_metadata:
origin = generic_metadata['origin'] or origin
args = generic_metadata['args'] or args
module_name = getattr(origin, '__module__', '<No __module__>')
if isinstance(origin, TypeAliasType):
type_ref = f'{module_name}.{origin.__name__}:{id(origin)}'
else:
try:
qualname = getattr(origin, '__qualname__', f'<No __qualname__: {origin}>')
except Exception:
qualname = getattr(origin, '__qualname__', '<No __qualname__>')
type_ref = f'{module_name}.{qualname}:{id(origin)}'
arg_refs: list[str] = []
for arg in args:
if isinstance(arg, str):
# Handle string literals as a special case; we may be able to remove this special handling if we
# wrap them in a ForwardRef at some point.
arg_ref = f'{arg}:str-{id(arg)}'
else:
arg_ref = f'{_repr.display_as_type(arg)}:{id(arg)}'
arg_refs.append(arg_ref)
if arg_refs:
type_ref = f'{type_ref}[{",".join(arg_refs)}]'
return type_ref
def get_ref(s: core_schema.CoreSchema) -> None | str:
"""Get the ref from the schema if it has one.
This exists just for type checking to work correctly.
"""
return s.get('ref', None)
def collect_definitions(schema: core_schema.CoreSchema) -> dict[str, core_schema.CoreSchema]:
defs: dict[str, CoreSchema] = {}
def _record_valid_refs(s: core_schema.CoreSchema, recurse: Recurse) -> core_schema.CoreSchema:
ref = get_ref(s)
if ref:
defs[ref] = s
return recurse(s, _record_valid_refs)
walk_core_schema(schema, _record_valid_refs)
return defs
def define_expected_missing_refs(
schema: core_schema.CoreSchema, allowed_missing_refs: set[str]
) -> core_schema.CoreSchema | None:
if not allowed_missing_refs:
# in this case, there are no missing refs to potentially substitute, so there's no need to walk the schema
# this is a common case (will be hit for all non-generic models), so it's worth optimizing for
return None
refs = collect_definitions(schema).keys()
expected_missing_refs = allowed_missing_refs.difference(refs)
if expected_missing_refs:
definitions: list[core_schema.CoreSchema] = [
# TODO: Replace this with a (new) CoreSchema that, if present at any level, makes validation fail
# Issue: https://github.com/pydantic/pydantic-core/issues/619
core_schema.none_schema(ref=ref, metadata={HAS_INVALID_SCHEMAS_METADATA_KEY: True})
for ref in expected_missing_refs
]
return core_schema.definitions_schema(schema, definitions)
return None
def collect_invalid_schemas(schema: core_schema.CoreSchema) -> bool:
invalid = False
def _is_schema_valid(s: core_schema.CoreSchema, recurse: Recurse) -> core_schema.CoreSchema:
nonlocal invalid
if 'metadata' in s:
metadata = s['metadata']
if HAS_INVALID_SCHEMAS_METADATA_KEY in metadata:
invalid = metadata[HAS_INVALID_SCHEMAS_METADATA_KEY]
return s
return recurse(s, _is_schema_valid)
walk_core_schema(schema, _is_schema_valid)
return invalid
T = TypeVar('T')
Recurse = Callable[[core_schema.CoreSchema, 'Walk'], core_schema.CoreSchema]
Walk = Callable[[core_schema.CoreSchema, Recurse], core_schema.CoreSchema]
# TODO: Should we move _WalkCoreSchema into pydantic_core proper?
# Issue: https://github.com/pydantic/pydantic-core/issues/615
class _WalkCoreSchema:
def __init__(self):
self._schema_type_to_method = self._build_schema_type_to_method()
def _build_schema_type_to_method(self) -> dict[core_schema.CoreSchemaType, Recurse]:
mapping: dict[core_schema.CoreSchemaType, Recurse] = {}
key: core_schema.CoreSchemaType
for key in get_args(core_schema.CoreSchemaType):
method_name = f"handle_{key.replace('-', '_')}_schema"
mapping[key] = getattr(self, method_name, self._handle_other_schemas)
return mapping
def walk(self, schema: core_schema.CoreSchema, f: Walk) -> core_schema.CoreSchema:
return f(schema, self._walk)
def _walk(self, schema: core_schema.CoreSchema, f: Walk) -> core_schema.CoreSchema:
schema = self._schema_type_to_method[schema['type']](schema.copy(), f)
ser_schema: core_schema.SerSchema | None = schema.get('serialization') # type: ignore
if ser_schema:
schema['serialization'] = self._handle_ser_schemas(ser_schema, f)
return schema
def _handle_other_schemas(self, schema: core_schema.CoreSchema, f: Walk) -> core_schema.CoreSchema:
sub_schema = schema.get('schema', None)
if sub_schema is not None:
schema['schema'] = self.walk(sub_schema, f) # type: ignore
return schema
def _handle_ser_schemas(self, ser_schema: core_schema.SerSchema, f: Walk) -> core_schema.SerSchema:
schema: core_schema.CoreSchema | None = ser_schema.get('schema', None)
if schema is not None:
ser_schema['schema'] = self.walk(schema, f) # type: ignore
return_schema: core_schema.CoreSchema | None = ser_schema.get('return_schema', None)
if return_schema is not None:
ser_schema['return_schema'] = self.walk(return_schema, f) # type: ignore
return ser_schema
def handle_definitions_schema(self, schema: core_schema.DefinitionsSchema, f: Walk) -> core_schema.CoreSchema:
new_definitions: list[core_schema.CoreSchema] = []
for definition in schema['definitions']:
if 'schema_ref' in definition and 'ref' in definition:
# This indicates a purposely indirect reference
# We want to keep such references around for implications related to JSON schema, etc.:
new_definitions.append(definition)
# However, we still need to walk the referenced definition:
self.walk(definition, f)
continue
updated_definition = self.walk(definition, f)
if 'ref' in updated_definition:
# If the updated definition schema doesn't have a 'ref', it shouldn't go in the definitions
# This is most likely to happen due to replacing something with a definition reference, in
# which case it should certainly not go in the definitions list
new_definitions.append(updated_definition)
new_inner_schema = self.walk(schema['schema'], f)
if not new_definitions and len(schema) == 3:
# This means we'd be returning a "trivial" definitions schema that just wrapped the inner schema
return new_inner_schema
new_schema = schema.copy()
new_schema['schema'] = new_inner_schema
new_schema['definitions'] = new_definitions
return new_schema
def handle_list_schema(self, schema: core_schema.ListSchema, f: Walk) -> core_schema.CoreSchema:
items_schema = schema.get('items_schema')
if items_schema is not None:
schema['items_schema'] = self.walk(items_schema, f)
return schema
def handle_set_schema(self, schema: core_schema.SetSchema, f: Walk) -> core_schema.CoreSchema:
items_schema = schema.get('items_schema')
if items_schema is not None:
schema['items_schema'] = self.walk(items_schema, f)
return schema
def handle_frozenset_schema(self, schema: core_schema.FrozenSetSchema, f: Walk) -> core_schema.CoreSchema:
items_schema = schema.get('items_schema')
if items_schema is not None:
schema['items_schema'] = self.walk(items_schema, f)
return schema
def handle_generator_schema(self, schema: core_schema.GeneratorSchema, f: Walk) -> core_schema.CoreSchema:
items_schema = schema.get('items_schema')
if items_schema is not None:
schema['items_schema'] = self.walk(items_schema, f)
return schema
def handle_tuple_schema(self, schema: core_schema.TupleSchema, f: Walk) -> core_schema.CoreSchema:
schema['items_schema'] = [self.walk(v, f) for v in schema['items_schema']]
return schema
def handle_dict_schema(self, schema: core_schema.DictSchema, f: Walk) -> core_schema.CoreSchema:
keys_schema = schema.get('keys_schema')
if keys_schema is not None:
schema['keys_schema'] = self.walk(keys_schema, f)
values_schema = schema.get('values_schema')
if values_schema:
schema['values_schema'] = self.walk(values_schema, f)
return schema
def handle_function_schema(self, schema: AnyFunctionSchema, f: Walk) -> core_schema.CoreSchema:
if not is_function_with_inner_schema(schema):
return schema
schema['schema'] = self.walk(schema['schema'], f)
return schema
def handle_union_schema(self, schema: core_schema.UnionSchema, f: Walk) -> core_schema.CoreSchema:
new_choices: list[CoreSchema | tuple[CoreSchema, str]] = []
for v in schema['choices']:
if isinstance(v, tuple):
new_choices.append((self.walk(v[0], f), v[1]))
else:
new_choices.append(self.walk(v, f))
schema['choices'] = new_choices
return schema
def handle_tagged_union_schema(self, schema: core_schema.TaggedUnionSchema, f: Walk) -> core_schema.CoreSchema:
new_choices: dict[Hashable, core_schema.CoreSchema] = {}
for k, v in schema['choices'].items():
new_choices[k] = v if isinstance(v, (str, int)) else self.walk(v, f)
schema['choices'] = new_choices
return schema
def handle_chain_schema(self, schema: core_schema.ChainSchema, f: Walk) -> core_schema.CoreSchema:
schema['steps'] = [self.walk(v, f) for v in schema['steps']]
return schema
def handle_lax_or_strict_schema(self, schema: core_schema.LaxOrStrictSchema, f: Walk) -> core_schema.CoreSchema:
schema['lax_schema'] = self.walk(schema['lax_schema'], f)
schema['strict_schema'] = self.walk(schema['strict_schema'], f)
return schema
def handle_json_or_python_schema(self, schema: core_schema.JsonOrPythonSchema, f: Walk) -> core_schema.CoreSchema:
schema['json_schema'] = self.walk(schema['json_schema'], f)
schema['python_schema'] = self.walk(schema['python_schema'], f)
return schema
def handle_model_fields_schema(self, schema: core_schema.ModelFieldsSchema, f: Walk) -> core_schema.CoreSchema:
extras_schema = schema.get('extras_schema')
if extras_schema is not None:
schema['extras_schema'] = self.walk(extras_schema, f)
replaced_fields: dict[str, core_schema.ModelField] = {}
replaced_computed_fields: list[core_schema.ComputedField] = []
for computed_field in schema.get('computed_fields', ()):
replaced_field = computed_field.copy()
replaced_field['return_schema'] = self.walk(computed_field['return_schema'], f)
replaced_computed_fields.append(replaced_field)
if replaced_computed_fields:
schema['computed_fields'] = replaced_computed_fields
for k, v in schema['fields'].items():
replaced_field = v.copy()
replaced_field['schema'] = self.walk(v['schema'], f)
replaced_fields[k] = replaced_field
schema['fields'] = replaced_fields
return schema
def handle_typed_dict_schema(self, schema: core_schema.TypedDictSchema, f: Walk) -> core_schema.CoreSchema:
extras_schema = schema.get('extras_schema')
if extras_schema is not None:
schema['extras_schema'] = self.walk(extras_schema, f)
replaced_computed_fields: list[core_schema.ComputedField] = []
for computed_field in schema.get('computed_fields', ()):
replaced_field = computed_field.copy()
replaced_field['return_schema'] = self.walk(computed_field['return_schema'], f)
replaced_computed_fields.append(replaced_field)
if replaced_computed_fields:
schema['computed_fields'] = replaced_computed_fields
replaced_fields: dict[str, core_schema.TypedDictField] = {}
for k, v in schema['fields'].items():
replaced_field = v.copy()
replaced_field['schema'] = self.walk(v['schema'], f)
replaced_fields[k] = replaced_field
schema['fields'] = replaced_fields
return schema
def handle_dataclass_args_schema(self, schema: core_schema.DataclassArgsSchema, f: Walk) -> core_schema.CoreSchema:
replaced_fields: list[core_schema.DataclassField] = []
replaced_computed_fields: list[core_schema.ComputedField] = []
for computed_field in schema.get('computed_fields', ()):
replaced_field = computed_field.copy()
replaced_field['return_schema'] = self.walk(computed_field['return_schema'], f)
replaced_computed_fields.append(replaced_field)
if replaced_computed_fields:
schema['computed_fields'] = replaced_computed_fields
for field in schema['fields']:
replaced_field = field.copy()
replaced_field['schema'] = self.walk(field['schema'], f)
replaced_fields.append(replaced_field)
schema['fields'] = replaced_fields
return schema
def handle_arguments_schema(self, schema: core_schema.ArgumentsSchema, f: Walk) -> core_schema.CoreSchema:
replaced_arguments_schema: list[core_schema.ArgumentsParameter] = []
for param in schema['arguments_schema']:
replaced_param = param.copy()
replaced_param['schema'] = self.walk(param['schema'], f)
replaced_arguments_schema.append(replaced_param)
schema['arguments_schema'] = replaced_arguments_schema
if 'var_args_schema' in schema:
schema['var_args_schema'] = self.walk(schema['var_args_schema'], f)
if 'var_kwargs_schema' in schema:
schema['var_kwargs_schema'] = self.walk(schema['var_kwargs_schema'], f)
return schema
def handle_call_schema(self, schema: core_schema.CallSchema, f: Walk) -> core_schema.CoreSchema:
schema['arguments_schema'] = self.walk(schema['arguments_schema'], f)
if 'return_schema' in schema:
schema['return_schema'] = self.walk(schema['return_schema'], f)
return schema
_dispatch = _WalkCoreSchema().walk
def walk_core_schema(schema: core_schema.CoreSchema, f: Walk) -> core_schema.CoreSchema:
"""Recursively traverse a CoreSchema.
Args:
schema (core_schema.CoreSchema): The CoreSchema to process, it will not be modified.
f (Walk): A function to apply. This function takes two arguments:
1. The current CoreSchema that is being processed
(not the same one you passed into this function, one level down).
2. The "next" `f` to call. This lets you for example use `f=functools.partial(some_method, some_context)`
to pass data down the recursive calls without using globals or other mutable state.
Returns:
core_schema.CoreSchema: A processed CoreSchema.
"""
return f(schema.copy(), _dispatch)
def simplify_schema_references(schema: core_schema.CoreSchema) -> core_schema.CoreSchema: # noqa: C901
definitions: dict[str, core_schema.CoreSchema] = {}
ref_counts: dict[str, int] = defaultdict(int)
involved_in_recursion: dict[str, bool] = {}
current_recursion_ref_count: dict[str, int] = defaultdict(int)
def collect_refs(s: core_schema.CoreSchema, recurse: Recurse) -> core_schema.CoreSchema:
if s['type'] == 'definitions':
for definition in s['definitions']:
ref = get_ref(definition)
assert ref is not None
if ref not in definitions:
definitions[ref] = definition
recurse(definition, collect_refs)
return recurse(s['schema'], collect_refs)
else:
ref = get_ref(s)
if ref is not None:
new = recurse(s, collect_refs)
new_ref = get_ref(new)
if new_ref:
definitions[new_ref] = new
return core_schema.definition_reference_schema(schema_ref=ref)
else:
return recurse(s, collect_refs)
schema = walk_core_schema(schema, collect_refs)
def count_refs(s: core_schema.CoreSchema, recurse: Recurse) -> core_schema.CoreSchema:
if s['type'] != 'definition-ref':
return recurse(s, count_refs)
ref = s['schema_ref']
ref_counts[ref] += 1
if ref_counts[ref] >= 2:
# If this model is involved in a recursion this should be detected
# on its second encounter, we can safely stop the walk here.
if current_recursion_ref_count[ref] != 0:
involved_in_recursion[ref] = True
return s
current_recursion_ref_count[ref] += 1
recurse(definitions[ref], count_refs)
current_recursion_ref_count[ref] -= 1
return s
schema = walk_core_schema(schema, count_refs)
assert all(c == 0 for c in current_recursion_ref_count.values()), 'this is a bug! please report it'
def can_be_inlined(s: core_schema.DefinitionReferenceSchema, ref: str) -> bool:
if ref_counts[ref] > 1:
return False
if involved_in_recursion.get(ref, False):
return False
if 'serialization' in s:
return False
if 'metadata' in s:
metadata = s['metadata']
for k in (
'pydantic_js_functions',
'pydantic_js_annotation_functions',
'pydantic.internal.union_discriminator',
):
if k in metadata:
# we need to keep this as a ref
return False
return True
def inline_refs(s: core_schema.CoreSchema, recurse: Recurse) -> core_schema.CoreSchema:
if s['type'] == 'definition-ref':
ref = s['schema_ref']
# Check if the reference is only used once, not involved in recursion and does not have
# any extra keys (like 'serialization')
if can_be_inlined(s, ref):
# Inline the reference by replacing the reference with the actual schema
new = definitions.pop(ref)
ref_counts[ref] -= 1 # because we just replaced it!
# put all other keys that were on the def-ref schema into the inlined version
# in particular this is needed for `serialization`
if 'serialization' in s:
new['serialization'] = s['serialization']
s = recurse(new, inline_refs)
return s
else:
return recurse(s, inline_refs)
else:
return recurse(s, inline_refs)
schema = walk_core_schema(schema, inline_refs)
def_values = [v for v in definitions.values() if ref_counts[v['ref']] > 0] # type: ignore
if def_values:
schema = core_schema.definitions_schema(schema=schema, definitions=def_values)
return schema
def _strip_metadata(schema: CoreSchema) -> CoreSchema:
def strip_metadata(s: CoreSchema, recurse: Recurse) -> CoreSchema:
s = s.copy()
s.pop('metadata', None)
if s['type'] == 'model-fields':
s = s.copy()
s['fields'] = {k: v.copy() for k, v in s['fields'].items()}
for field_name, field_schema in s['fields'].items():
field_schema.pop('metadata', None)
s['fields'][field_name] = field_schema
computed_fields = s.get('computed_fields', None)
if computed_fields:
s['computed_fields'] = [cf.copy() for cf in computed_fields]
for cf in computed_fields:
cf.pop('metadata', None)
else:
s.pop('computed_fields', None)
elif s['type'] == 'model':
# remove some defaults
if s.get('custom_init', True) is False:
s.pop('custom_init')
if s.get('root_model', True) is False:
s.pop('root_model')
if {'title'}.issuperset(s.get('config', {}).keys()):
s.pop('config', None)
return recurse(s, strip_metadata)
return walk_core_schema(schema, strip_metadata)
def pretty_print_core_schema(
schema: CoreSchema,
include_metadata: bool = False,
) -> None:
"""Pretty print a CoreSchema using rich.
This is intended for debugging purposes.
Args:
schema: The CoreSchema to print.
include_metadata: Whether to include metadata in the output. Defaults to `False`.
"""
from rich import print # type: ignore # install it manually in your dev env
if not include_metadata:
schema = _strip_metadata(schema)
return print(schema)
def validate_core_schema(schema: CoreSchema) -> CoreSchema:
if 'PYDANTIC_SKIP_VALIDATING_CORE_SCHEMAS' in os.environ:
return schema
return _validate_core_schema(schema)