80 lines
2.1 KiB
Python
80 lines
2.1 KiB
Python
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import json
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from functools import lru_cache
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from pathlib import Path
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from typing import Any, Callable, Optional, Type, TypeVar, Union
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from .parse import Protocol, load_file, load_str_bytes
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from .types import StrBytes
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from .typing import display_as_type
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__all__ = ('parse_file_as', 'parse_obj_as', 'parse_raw_as')
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NameFactory = Union[str, Callable[[Type[Any]], str]]
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def _generate_parsing_type_name(type_: Any) -> str:
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return f'ParsingModel[{display_as_type(type_)}]'
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@lru_cache(maxsize=2048)
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def _get_parsing_type(type_: Any, *, type_name: Optional[NameFactory] = None) -> Any:
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from pydantic.main import create_model
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if type_name is None:
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type_name = _generate_parsing_type_name
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if not isinstance(type_name, str):
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type_name = type_name(type_)
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return create_model(type_name, __root__=(type_, ...))
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T = TypeVar('T')
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def parse_obj_as(type_: Type[T], obj: Any, *, type_name: Optional[NameFactory] = None) -> T:
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model_type = _get_parsing_type(type_, type_name=type_name) # type: ignore[arg-type]
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return model_type(__root__=obj).__root__
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def parse_file_as(
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type_: Type[T],
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path: Union[str, Path],
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*,
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content_type: str = None,
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encoding: str = 'utf8',
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proto: Protocol = None,
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allow_pickle: bool = False,
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json_loads: Callable[[str], Any] = json.loads,
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type_name: Optional[NameFactory] = None,
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) -> T:
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obj = load_file(
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path,
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proto=proto,
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content_type=content_type,
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encoding=encoding,
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allow_pickle=allow_pickle,
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json_loads=json_loads,
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)
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return parse_obj_as(type_, obj, type_name=type_name)
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def parse_raw_as(
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type_: Type[T],
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b: StrBytes,
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*,
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content_type: str = None,
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encoding: str = 'utf8',
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proto: Protocol = None,
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allow_pickle: bool = False,
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json_loads: Callable[[str], Any] = json.loads,
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type_name: Optional[NameFactory] = None,
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) -> T:
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obj = load_str_bytes(
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b,
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proto=proto,
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content_type=content_type,
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encoding=encoding,
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allow_pickle=allow_pickle,
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json_loads=json_loads,
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)
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return parse_obj_as(type_, obj, type_name=type_name)
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