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

1from __future__ import annotations 42 ctx1opqrstabcduvMefwxyzABghijCDNPEFGHIJklmnKLO

2 

3import inspect 42 ctx1opqrstabcduvMefwxyzABghijCDNPEFGHIJklmnKLO

4from collections.abc import Mapping, Sequence 42 ctx1opqrstabcduvMefwxyzABghijCDNPEFGHIJklmnKLO

5from typing import TYPE_CHECKING, Any, Union 42 ctx1opqrstabcduvMefwxyzABghijCDNPEFGHIJklmnKLO

6 

7from pydantic_core import CoreSchema, core_schema 42 ctx1opqrstabcduvMefwxyzABghijCDNPEFGHIJklmnKLO

8from typing_extensions import TypeGuard, get_args, get_origin 42 ctx1opqrstabcduvMefwxyzABghijCDNPEFGHIJklmnKLO

9from typing_inspection import typing_objects 42 ctx1opqrstabcduvMefwxyzABghijCDNPEFGHIJklmnKLO

10 

11from . import _repr 42 ctx1opqrstabcduvMefwxyzABghijCDNPEFGHIJklmnKLO

12from ._typing_extra import is_generic_alias 42 ctx1opqrstabcduvMefwxyzABghijCDNPEFGHIJklmnKLO

13 

14if TYPE_CHECKING: 42 ctx1opqrstabcduvMefwxyzABghijCDNPEFGHIJklmnKLO

15 from rich.console import Console 

16 

17AnyFunctionSchema = Union[ 42 ctx1opqrstabcduvMefwxyzABghijCDNPEFGHIJklmnKLO

18 core_schema.AfterValidatorFunctionSchema, 

19 core_schema.BeforeValidatorFunctionSchema, 

20 core_schema.WrapValidatorFunctionSchema, 

21 core_schema.PlainValidatorFunctionSchema, 

22] 

23 

24 

25FunctionSchemaWithInnerSchema = Union[ 42 ctx1opqrstabcduvMefwxyzABghijCDNPEFGHIJklmnKLO

26 core_schema.AfterValidatorFunctionSchema, 

27 core_schema.BeforeValidatorFunctionSchema, 

28 core_schema.WrapValidatorFunctionSchema, 

29] 

30 

31CoreSchemaField = Union[ 42 ctx1opqrstabcduvMefwxyzABghijCDNPEFGHIJklmnKLO

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

33] 

34CoreSchemaOrField = Union[core_schema.CoreSchema, CoreSchemaField] 42 ctx1opqrstabcduvMefwxyzABghijCDNPEFGHIJklmnKLO

35 

36_CORE_SCHEMA_FIELD_TYPES = {'typed-dict-field', 'dataclass-field', 'model-field', 'computed-field'} 42 ctx1opqrstabcduvMefwxyzABghijCDNPEFGHIJklmnKLO

37_FUNCTION_WITH_INNER_SCHEMA_TYPES = {'function-before', 'function-after', 'function-wrap'} 42 ctx1opqrstabcduvMefwxyzABghijCDNPEFGHIJklmnKLO

38_LIST_LIKE_SCHEMA_WITH_ITEMS_TYPES = {'list', 'set', 'frozenset'} 42 ctx1opqrstabcduvMefwxyzABghijCDNPEFGHIJklmnKLO

39 

40 

41def is_core_schema( 42 ctx1opqrstabcduvMefwxyzABghijCDNPEFGHIJklmnKLO

42 schema: CoreSchemaOrField, 

43) -> TypeGuard[CoreSchema]: 

44 return schema['type'] not in _CORE_SCHEMA_FIELD_TYPES 41 ctx1opqrstabcduvMefwxyzABghijCDNEFGHIJklmnKLO

45 

46 

47def is_core_schema_field( 42 ctx1opqrstabcduvMefwxyzABghijCDNPEFGHIJklmnKLO

48 schema: CoreSchemaOrField, 

49) -> TypeGuard[CoreSchemaField]: 

50 return schema['type'] in _CORE_SCHEMA_FIELD_TYPES 41 ctx1opqrstabcduvMefwxyzABghijCDNEFGHIJklmnKLO

51 

52 

53def is_function_with_inner_schema( 42 ctx1opqrstabcduvMefwxyzABghijCDNPEFGHIJklmnKLO

54 schema: CoreSchemaOrField, 

55) -> TypeGuard[FunctionSchemaWithInnerSchema]: 

56 return schema['type'] in _FUNCTION_WITH_INNER_SCHEMA_TYPES 41 ctx1opqrstabcduvMefwxyzABghijCDNEFGHIJklmnKLO

57 

58 

59def is_list_like_schema_with_items_schema( 42 ctx1opqrstabcduvMefwxyzABghijCDNPEFGHIJklmnKLO

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 41 ctx1opqrstabcduvMefwxyzABghijCDNEFGHIJklmnKLO

63 

64 

65def get_type_ref(type_: Any, args_override: tuple[type[Any], ...] | None = None) -> str: 42 ctx1opqrstabcduvMefwxyzABghijCDNPEFGHIJklmnKLO

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_ 42 ctx1opqrstabcduvMefwxyzABghijCDNPEFGHIJklmnKLO

72 

73 args = get_args(type_) if is_generic_alias(type_) else (args_override or ()) 42 ctx1opqrstabcduvMefwxyzABghijCDNPEFGHIJklmnKLO

74 generic_metadata = getattr(type_, '__pydantic_generic_metadata__', None) 42 ctx1opqrstabcduvMefwxyzABghijCDNPEFGHIJklmnKLO

75 if generic_metadata: 42 ctx1opqrstabcduvMefwxyzABghijCDNPEFGHIJklmnKLO

76 origin = generic_metadata['origin'] or origin 42 ctx1opqrstabcduvMefwxyzABghijCDNPEFGHIJklmnKLO

77 args = generic_metadata['args'] or args 42 ctx1opqrstabcduvMefwxyzABghijCDNPEFGHIJklmnKLO

78 

79 module_name = getattr(origin, '__module__', '<No __module__>') 42 ctx1opqrstabcduvMefwxyzABghijCDNPEFGHIJklmnKLO

80 if typing_objects.is_typealiastype(origin): 42 ctx1opqrstabcduvMefwxyzABghijCDNPEFGHIJklmnKLO

81 type_ref = f'{module_name}.{origin.__name__}:{id(origin)}' 41 ctx1opqrstabcduvMefwxyzABghijCDNEFGHIJklmnKLO

82 else: 

83 try: 42 ctx1opqrstabcduvMefwxyzABghijCDNPEFGHIJklmnKLO

84 qualname = getattr(origin, '__qualname__', f'<No __qualname__: {origin}>') 42 ctx1opqrstabcduvMefwxyzABghijCDNPEFGHIJklmnKLO

85 except Exception: 

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

87 type_ref = f'{module_name}.{qualname}:{id(origin)}' 42 ctx1opqrstabcduvMefwxyzABghijCDNPEFGHIJklmnKLO

88 

89 arg_refs: list[str] = [] 42 ctx1opqrstabcduvMefwxyzABghijCDNPEFGHIJklmnKLO

90 for arg in args: 42 ctx1opqrstabcduvMefwxyzABghijCDNPEFGHIJklmnKLO

91 if isinstance(arg, str): 42 ctx1opqrstabcduvMefwxyzABghijCDNPEFGHIJklmnKLO

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)}' 38 ctx1opqrstabcduvefwxyzABghijCDEFGHIJklmnKL

95 else: 

96 arg_ref = f'{_repr.display_as_type(arg)}:{id(arg)}' 42 ctx1opqrstabcduvMefwxyzABghijCDNPEFGHIJklmnKLO

97 arg_refs.append(arg_ref) 42 ctx1opqrstabcduvMefwxyzABghijCDNPEFGHIJklmnKLO

98 if arg_refs: 42 ctx1opqrstabcduvMefwxyzABghijCDNPEFGHIJklmnKLO

99 type_ref = f'{type_ref}[{",".join(arg_refs)}]' 42 ctx1opqrstabcduvMefwxyzABghijCDNPEFGHIJklmnKLO

100 return type_ref 42 ctx1opqrstabcduvMefwxyzABghijCDNPEFGHIJklmnKLO

101 

102 

103def get_ref(s: core_schema.CoreSchema) -> None | str: 42 ctx1opqrstabcduvMefwxyzABghijCDNPEFGHIJklmnKLO

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) 42 ctx1opqrstabcduvMefwxyzABghijCDNPEFGHIJklmnKLO

108 

109 

110def _clean_schema_for_pretty_print(obj: Any, strip_metadata: bool = True) -> Any: # pragma: no cover 42 ctx1opqrstabcduvMefwxyzABghijCDNPEFGHIJklmnKLO

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( 42 ctx1opqrstabcduvMefwxyzABghijCDNPEFGHIJklmnKLO

142 val: Any, 15 ctx1abcdefghijPklmn

143 *, 

144 console: Console | None = None, 42 ctx1opqrstabcduvMefwxyzABghijCDNPEFGHIJklmnKLO

145 max_depth: int | None = None, 42 ctx1opqrstabcduvMefwxyzABghijCDNPEFGHIJklmnKLO

146 strip_metadata: bool = True, 42 ctx1opqrstabcduvMefwxyzABghijCDNPEFGHIJklmnKLO

147) -> None: # pragma: no cover 15 ctx1abcdefghijPklmn

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 42 ctx1opqrstabcduvMefwxyzABghijCDNPEFGHIJklmnKLO