ai-content-maker/.venv/Lib/site-packages/pydantic/v1/tools.py

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2024-05-03 04:18:51 +03:00
import json
from functools import lru_cache
from pathlib import Path
from typing import TYPE_CHECKING, Any, Callable, Optional, Type, TypeVar, Union
from .parse import Protocol, load_file, load_str_bytes
from .types import StrBytes
from .typing import display_as_type
__all__ = ('parse_file_as', 'parse_obj_as', 'parse_raw_as', 'schema_of', 'schema_json_of')
NameFactory = Union[str, Callable[[Type[Any]], str]]
if TYPE_CHECKING:
from .typing import DictStrAny
def _generate_parsing_type_name(type_: Any) -> str:
return f'ParsingModel[{display_as_type(type_)}]'
@lru_cache(maxsize=2048)
def _get_parsing_type(type_: Any, *, type_name: Optional[NameFactory] = None) -> Any:
from .main import create_model
if type_name is None:
type_name = _generate_parsing_type_name
if not isinstance(type_name, str):
type_name = type_name(type_)
return create_model(type_name, __root__=(type_, ...))
T = TypeVar('T')
def parse_obj_as(type_: Type[T], obj: Any, *, type_name: Optional[NameFactory] = None) -> T:
model_type = _get_parsing_type(type_, type_name=type_name) # type: ignore[arg-type]
return model_type(__root__=obj).__root__
def parse_file_as(
type_: Type[T],
path: Union[str, Path],
*,
content_type: str = None,
encoding: str = 'utf8',
proto: Protocol = None,
allow_pickle: bool = False,
json_loads: Callable[[str], Any] = json.loads,
type_name: Optional[NameFactory] = None,
) -> T:
obj = load_file(
path,
proto=proto,
content_type=content_type,
encoding=encoding,
allow_pickle=allow_pickle,
json_loads=json_loads,
)
return parse_obj_as(type_, obj, type_name=type_name)
def parse_raw_as(
type_: Type[T],
b: StrBytes,
*,
content_type: str = None,
encoding: str = 'utf8',
proto: Protocol = None,
allow_pickle: bool = False,
json_loads: Callable[[str], Any] = json.loads,
type_name: Optional[NameFactory] = None,
) -> T:
obj = load_str_bytes(
b,
proto=proto,
content_type=content_type,
encoding=encoding,
allow_pickle=allow_pickle,
json_loads=json_loads,
)
return parse_obj_as(type_, obj, type_name=type_name)
def schema_of(type_: Any, *, title: Optional[NameFactory] = None, **schema_kwargs: Any) -> 'DictStrAny':
"""Generate a JSON schema (as dict) for the passed model or dynamically generated one"""
return _get_parsing_type(type_, type_name=title).schema(**schema_kwargs)
def schema_json_of(type_: Any, *, title: Optional[NameFactory] = None, **schema_json_kwargs: Any) -> str:
"""Generate a JSON schema (as JSON) for the passed model or dynamically generated one"""
return _get_parsing_type(type_, type_name=title).schema_json(**schema_json_kwargs)