import gzip
from typing import Callable, List

from fastapi import Body, FastAPI, Request, Response
from fastapi.routing import APIRoute


class GzipRequest(Request):
    async def body(self) -> bytes:
        if not hasattr(self, "_body"):
            body = await super().body()
            if "gzip" in self.headers.getlist("Content-Encoding"):
                body = gzip.decompress(body)
            self._body = body
        return self._body

# -*- coding: utf-8 -*-
from xml.etree import cElementTree
from xml.etree.cElementTree import ParseError

if hasattr(cElementTree, 'ParseError'):
    _ETREE_EXCEPTIONS = (ParseError, AttributeError, ValueError, TypeError)
else:
    _ETREE_EXCEPTIONS = (SyntaxError, AttributeError, ValueError, TypeError)

_STS_NS = {'sts': 'https://sts.amazonaws.com/doc/2011-06-15/'}


class STSElement(object):

    return (
        _annotation_is_complex(annotation)
        or _annotation_is_complex(origin)
        or hasattr(origin, "__pydantic_core_schema__")
        or hasattr(origin, "__get_pydantic_core_schema__")
    )


def field_annotation_is_scalar(annotation: Any) -> bool:
    # handle Ellipsis here to make tuple[int, ...] work nicely

    # performance by avoiding unnecessary cloning
    if cloned_types is None:
        cloned_types = _CLONED_TYPES_CACHE

    original_type = field.type_
    if is_dataclass(original_type) and hasattr(original_type, "__pydantic_model__"):
        original_type = original_type.__pydantic_model__
    use_type = original_type
    if lenient_issubclass(original_type, BaseModel):

_API_MODULE = _sys.modules[__name__].bitwise
_tf_api_dir = _os.path.dirname(_os.path.dirname(_API_MODULE.__file__))
_current_module = _sys.modules[__name__]

if not hasattr(_current_module, "__path__"):
  __path__ = [_tf_api_dir]
elif _tf_api_dir not in __path__:
  __path__.append(_tf_api_dir)

# Hook external TensorFlow modules.

# Load tensorflow-io-gcs-filesystem if enabled

_API_MODULE = _sys.modules[__name__].bitwise  # pylint: disable=undefined-variable
_current_module = _sys.modules[__name__]
_tf_api_dir = _os.path.dirname(_os.path.dirname(_API_MODULE.__file__))
if not hasattr(_current_module, "__path__"):
  __path__ = [_tf_api_dir]
elif _tf_api_dir not in __path__:
  __path__.append(_tf_api_dir)

# Hook external TensorFlow modules.

    exclude_unset: bool = False,
    exclude_defaults: bool = False,
    exclude_none: bool = False,
    is_coroutine: bool = True,
) -> Any:
    if field:
        errors = []
        if not hasattr(field, "serialize"):
            # pydantic v1
            response_content = _prepare_response_content(
                response_content,
                exclude_unset=exclude_unset,

    if (hashIndex >= 0) {
      hashStr = url.substring(hashIndex);
      buf.push("&hash=");
      buf.push(encodeURIComponent(hashStr));
      buf.push(hashStr);
    }
  });

  $result.on("click", "a.favorite", function(e) {
    var $favorite = $(this),
        values = $favorite.attr("href").split("#"),
        actionUrl,
        docId;
    if (values.length === 2 && $queryId.length > 0) {
      docId = values[1];

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