two version of R2R are hereHEADmaster

1 files changed, 92 insertions, 0 deletions

diff --git a/.venv/lib/python3.12/site-packages/pydantic/v1/tools.py b/.venv/lib/python3.12/site-packages/pydantic/v1/tools.py
new file mode 100644
index 00000000..6838a23e
--- /dev/null
+++ b/.venv/lib/python3.12/site-packages/pydantic/v1/tools.py
@@ -0,0 +1,92 @@
+import json
+from functools import lru_cache
+from pathlib import Path
+from typing import TYPE_CHECKING, Any, Callable, Optional, Type, TypeVar, Union
+
+from pydantic.v1.parse import Protocol, load_file, load_str_bytes
+from pydantic.v1.types import StrBytes
+from pydantic.v1.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 pydantic.v1.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 pydantic.v1.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)