Coverage for pydantic/_internal/_core_utils.py: 96.72%

1from __future__ import annotations 36 ctx1rstuvwabcdefgxyzABChijklJDEFGHImnopq

2 

3import inspect 36 ctx1rstuvwabcdefgxyzABChijklJDEFGHImnopq

4from collections.abc import Mapping, Sequence 36 ctx1rstuvwabcdefgxyzABChijklJDEFGHImnopq

5from typing import TYPE_CHECKING, Any, Union 36 ctx1rstuvwabcdefgxyzABChijklJDEFGHImnopq

6 

7from pydantic_core import CoreSchema, core_schema 36 ctx1rstuvwabcdefgxyzABChijklJDEFGHImnopq

8from typing_extensions import TypeGuard, get_args, get_origin 36 ctx1rstuvwabcdefgxyzABChijklJDEFGHImnopq

9from typing_inspection import typing_objects 36 ctx1rstuvwabcdefgxyzABChijklJDEFGHImnopq

10 

11from . import _repr 36 ctx1rstuvwabcdefgxyzABChijklJDEFGHImnopq

12from ._typing_extra import is_generic_alias 36 ctx1rstuvwabcdefgxyzABChijklJDEFGHImnopq

13 

14if TYPE_CHECKING: 36 ctx1rstuvwabcdefgxyzABChijklJDEFGHImnopq

15 from rich.console import Console 

16 

17AnyFunctionSchema = Union[ 36 ctx1rstuvwabcdefgxyzABChijklJDEFGHImnopq

18 core_schema.AfterValidatorFunctionSchema, 

19 core_schema.BeforeValidatorFunctionSchema, 

20 core_schema.WrapValidatorFunctionSchema, 

21 core_schema.PlainValidatorFunctionSchema, 

22] 

23 

24 

25FunctionSchemaWithInnerSchema = Union[ 36 ctx1rstuvwabcdefgxyzABChijklJDEFGHImnopq

26 core_schema.AfterValidatorFunctionSchema, 

27 core_schema.BeforeValidatorFunctionSchema, 

28 core_schema.WrapValidatorFunctionSchema, 

29] 

30 

31CoreSchemaField = Union[ 36 ctx1rstuvwabcdefgxyzABChijklJDEFGHImnopq

32 core_schema.ModelField, core_schema.DataclassField, core_schema.TypedDictField, core_schema.ComputedField 

33] 

34CoreSchemaOrField = Union[core_schema.CoreSchema, CoreSchemaField] 36 ctx1rstuvwabcdefgxyzABChijklJDEFGHImnopq

35 

36_CORE_SCHEMA_FIELD_TYPES = {'typed-dict-field', 'dataclass-field', 'model-field', 'computed-field'} 36 ctx1rstuvwabcdefgxyzABChijklJDEFGHImnopq

37_FUNCTION_WITH_INNER_SCHEMA_TYPES = {'function-before', 'function-after', 'function-wrap'} 36 ctx1rstuvwabcdefgxyzABChijklJDEFGHImnopq

38_LIST_LIKE_SCHEMA_WITH_ITEMS_TYPES = {'list', 'set', 'frozenset'} 36 ctx1rstuvwabcdefgxyzABChijklJDEFGHImnopq

39 

40 

41def is_core_schema( 36 ctx1rstuvwabcdefgxyzABChijklJDEFGHImnopq

42 schema: CoreSchemaOrField, 

43) -> TypeGuard[CoreSchema]: 

44 return schema['type'] not in _CORE_SCHEMA_FIELD_TYPES 35 ctx1rstuvwabcdefgxyzABChijklDEFGHImnopq

45 

46 

47def is_core_schema_field( 36 ctx1rstuvwabcdefgxyzABChijklJDEFGHImnopq

48 schema: CoreSchemaOrField, 

49) -> TypeGuard[CoreSchemaField]: 

50 return schema['type'] in _CORE_SCHEMA_FIELD_TYPES 35 ctx1rstuvwabcdefgxyzABChijklDEFGHImnopq

51 

52 

53def is_function_with_inner_schema( 36 ctx1rstuvwabcdefgxyzABChijklJDEFGHImnopq

54 schema: CoreSchemaOrField, 

55) -> TypeGuard[FunctionSchemaWithInnerSchema]: 

56 return schema['type'] in _FUNCTION_WITH_INNER_SCHEMA_TYPES 35 ctx1rstuvwabcdefgxyzABChijklDEFGHImnopq

57 

58 

59def is_list_like_schema_with_items_schema( 36 ctx1rstuvwabcdefgxyzABChijklJDEFGHImnopq

60 schema: CoreSchema, 

61) -> TypeGuard[core_schema.ListSchema | core_schema.SetSchema | core_schema.FrozenSetSchema]: 

62 return schema['type'] in _LIST_LIKE_SCHEMA_WITH_ITEMS_TYPES 35 ctx1rstuvwabcdefgxyzABChijklDEFGHImnopq

63 

64 

65def get_type_ref(type_: Any, args_override: tuple[type[Any], ...] | None = None) -> str: 36 ctx1rstuvwabcdefgxyzABChijklJDEFGHImnopq

66 """Produces the ref to be used for this type by pydantic_core's core schemas. 

67 

68 This `args_override` argument was added for the purpose of creating valid recursive references 

69 when creating generic models without needing to create a concrete class. 

70 """ 

71 origin = get_origin(type_) or type_ 36 ctx1rstuvwabcdefgxyzABChijklJDEFGHImnopq

72 

73 args = get_args(type_) if is_generic_alias(type_) else (args_override or ()) 36 ctx1rstuvwabcdefgxyzABChijklJDEFGHImnopq

74 generic_metadata = getattr(type_, '__pydantic_generic_metadata__', None) 36 ctx1rstuvwabcdefgxyzABChijklJDEFGHImnopq

75 if generic_metadata: 36 ctx1rstuvwabcdefgxyzABChijklJDEFGHImnopq

76 origin = generic_metadata['origin'] or origin 36 ctx1rstuvwabcdefgxyzABChijklJDEFGHImnopq

77 args = generic_metadata['args'] or args 36 ctx1rstuvwabcdefgxyzABChijklJDEFGHImnopq

78 

79 module_name = getattr(origin, '__module__', '<No __module__>') 36 ctx1rstuvwabcdefgxyzABChijklJDEFGHImnopq

80 if typing_objects.is_typealiastype(origin): 36 ctx1rstuvwabcdefgxyzABChijklJDEFGHImnopq

81 type_ref = f'{module_name}.{origin.__name__}:{id(origin)}' 35 ctx1rstuvwabcdefgxyzABChijklDEFGHImnopq

82 else: 

83 try: 36 ctx1rstuvwabcdefgxyzABChijklJDEFGHImnopq

84 qualname = getattr(origin, '__qualname__', f'<No __qualname__: {origin}>') 36 ctx1rstuvwabcdefgxyzABChijklJDEFGHImnopq

85 except Exception: 

86 qualname = getattr(origin, '__qualname__', '<No __qualname__>') 

87 type_ref = f'{module_name}.{qualname}:{id(origin)}' 36 ctx1rstuvwabcdefgxyzABChijklJDEFGHImnopq

88 

89 arg_refs: list[str] = [] 36 ctx1rstuvwabcdefgxyzABChijklJDEFGHImnopq

90 for arg in args: 36 ctx1rstuvwabcdefgxyzABChijklJDEFGHImnopq

91 if isinstance(arg, str): 36 ctx1rstuvwabcdefgxyzABChijklJDEFGHImnopq

92 # Handle string literals as a special case; we may be able to remove this special handling if we 

93 # wrap them in a ForwardRef at some point. 

94 arg_ref = f'{arg}:str-{id(arg)}' 35 ctx1rstuvwabcdefgxyzABChijklDEFGHImnopq

95 else: 

96 arg_ref = f'{_repr.display_as_type(arg)}:{id(arg)}' 36 ctx1rstuvwabcdefgxyzABChijklJDEFGHImnopq

97 arg_refs.append(arg_ref) 36 ctx1rstuvwabcdefgxyzABChijklJDEFGHImnopq

98 if arg_refs: 36 ctx1rstuvwabcdefgxyzABChijklJDEFGHImnopq

99 type_ref = f'{type_ref}[{",".join(arg_refs)}]' 36 ctx1rstuvwabcdefgxyzABChijklJDEFGHImnopq

100 return type_ref 36 ctx1rstuvwabcdefgxyzABChijklJDEFGHImnopq

101 

102 

103def get_ref(s: core_schema.CoreSchema) -> None | str: 36 ctx1rstuvwabcdefgxyzABChijklJDEFGHImnopq

104 """Get the ref from the schema if it has one. 

105 This exists just for type checking to work correctly. 

106 """ 

107 return s.get('ref', None) 36 ctx1rstuvwabcdefgxyzABChijklJDEFGHImnopq

108 

109 

110def _clean_schema_for_pretty_print(obj: Any, strip_metadata: bool = True) -> Any: # pragma: no cover 36 ctx1rstuvwabcdefgxyzABChijklJDEFGHImnopq

111 """A utility function to remove irrelevant information from a core schema.""" 

112 if isinstance(obj, Mapping): 

113 new_dct = {} 

114 for k, v in obj.items(): 

115 if k == 'metadata' and strip_metadata: 

116 new_metadata = {} 

117 

118 for meta_k, meta_v in v.items(): 

119 if meta_k in ('pydantic_js_functions', 'pydantic_js_annotation_functions'): 

120 new_metadata['js_metadata'] = '<stripped>' 

121 else: 

122 new_metadata[meta_k] = _clean_schema_for_pretty_print(meta_v, strip_metadata=strip_metadata) 

123 

124 if list(new_metadata.keys()) == ['js_metadata']: 

125 new_metadata = {'<stripped>'} 

126 

127 new_dct[k] = new_metadata 

128 # Remove some defaults: 

129 elif k in ('custom_init', 'root_model') and not v: 

130 continue 

131 else: 

132 new_dct[k] = _clean_schema_for_pretty_print(v, strip_metadata=strip_metadata) 

133 

134 return new_dct 

135 elif isinstance(obj, Sequence) and not isinstance(obj, str): 

136 return [_clean_schema_for_pretty_print(v, strip_metadata=strip_metadata) for v in obj] 

137 else: 

138 return obj 

139 

140 

141def pretty_print_core_schema( 36 ctx1rstuvwabcdefgxyzABChijklJDEFGHImnopq

142 val: Any, 18 ctx1abcdefghijklJmnopq

143 *, 

144 console: Console | None = None, 36 ctx1rstuvwabcdefgxyzABChijklJDEFGHImnopq

145 max_depth: int | None = None, 36 ctx1rstuvwabcdefgxyzABChijklJDEFGHImnopq

146 strip_metadata: bool = True, 36 ctx1rstuvwabcdefgxyzABChijklJDEFGHImnopq

147) -> None: # pragma: no cover 18 ctx1abcdefghijklJmnopq

148 """Pretty-print a core schema using the `rich` library. 

149 

150 Args: 

151 val: The core schema to print, or a Pydantic model/dataclass/type adapter 

152 (in which case the cached core schema is fetched and printed). 

153 console: A rich console to use when printing. Defaults to the global rich console instance. 

154 max_depth: The number of nesting levels which may be printed. 

155 strip_metadata: Whether to strip metadata in the output. If `True` any known core metadata 

156 attributes will be stripped (but custom attributes are kept). Defaults to `True`. 

157 """ 

158 # lazy import: 

159 from rich.pretty import pprint 

160 

161 # circ. imports: 

162 from pydantic import BaseModel, TypeAdapter 

163 from pydantic.dataclasses import is_pydantic_dataclass 

164 

165 if (inspect.isclass(val) and issubclass(val, BaseModel)) or is_pydantic_dataclass(val): 

166 val = val.__pydantic_core_schema__ 

167 if isinstance(val, TypeAdapter): 

168 val = val.core_schema 

169 cleaned_schema = _clean_schema_for_pretty_print(val, strip_metadata=strip_metadata) 

170 

171 pprint(cleaned_schema, console=console, max_depth=max_depth) 

172 

173 

174pps = pretty_print_core_schema 36 ctx1rstuvwabcdefgxyzABChijklJDEFGHImnopq