similar, and get the two parts `items` and `read`. Many applications do that to
    group and organize permissions, you could do it as well in your application, just
    know that that it is application specific, it's not part of the specification.


    grant_type: the OAuth2 spec says it is required and MUST be the fixed string "password".

    ) -> Optional[HTTPAuthorizationCredentials]:
        authorization = request.headers.get("Authorization")
        scheme, credentials = get_authorization_scheme_param(authorization)
        if not (authorization and scheme and credentials):
            if self.auto_error:
                raise HTTPException(
                    status_code=HTTP_403_FORBIDDEN, detail="Not authenticated"
                )
            else:

        if (
            key in main_dict
            and isinstance(main_dict[key], dict)
            and isinstance(value, dict)
        ):
            deep_dict_update(main_dict[key], value)
        elif (
            key in main_dict
            and isinstance(main_dict[key], list)
            and isinstance(update_dict[key], list)
        ):

# See the License for the specific language governing permissions and
# limitations under the License.
# ==============================================================================

"""Extracts ResultStore links from a log containing Bazel invocations.

The links and the invocations' status can then be printed out, or output in the
form of JUnit-based XML.
"""
import argparse

            dependency.

            The term "scope" comes from the OAuth2 specification, it seems to be
            intentionaly vague and interpretable. It normally refers to permissions,
            in cases to roles.

            These scopes are integrated with OpenAPI (and the API docs at `/docs`).
            So they are visible in the OpenAPI specification.
            )
            """
        ),

Example: squash_testlogs.py /tf/pkg/testlogs /tf/pkg/merged.xml

Recursively find all the JUnit test.xml files in one directory, and merge any
of them that contain failures into one file. The TensorFlow DevInfra team
uses this to generate a simple overview of an entire pip and nonpip test
invocation, since the normal logs that Bazel creates are too large for the
internal invocation viewer.
"""
import collections
import os
import re

    # to be read from files and other types, but I'm not even sure it's a good idea
    # to support it as a first class "feature"
    assert is_bytes_sequence_annotation(Union[List[str], List[bytes]])


def test_is_uploadfile_sequence_annotation():
    # For coverage
    # TODO: in theory this would allow declaring types that could be lists of UploadFile

        max_length: Optional[int] = None,
        pattern: Optional[str] = None,
        regex: Annotated[
            Optional[str],
            deprecated(
                "Deprecated in FastAPI 0.100.0 and Pydantic v2, use `pattern` instead."
            ),
        ] = None,
        discriminator: Union[str, None] = None,
        strict: Union[bool, None] = _Unset,
        multiple_of: Union[float, None] = _Unset,

    correct_password_bytes = b"swordfish"
    is_correct_password = secrets.compare_digest(
        current_password_bytes, correct_password_bytes
    )
    if not (is_correct_username and is_correct_password):
        raise HTTPException(
            status_code=status.HTTP_401_UNAUTHORIZED,
            detail="Incorrect username or password",
            headers={"WWW-Authenticate": "Basic"},
        )

from fastapi.security import OAuth2PasswordBearer, OAuth2PasswordRequestForm
from jose import JWTError, jwt
from passlib.context import CryptContext
from pydantic import BaseModel

# to get a string like this run:
# openssl rand -hex 32
SECRET_KEY = "09d25e094faa6ca2556c818166b7a9563b93f7099f6f0f4caa6cf63b88e8d3e7"
ALGORITHM = "HS256"
ACCESS_TOKEN_EXPIRE_MINUTES = 30


fake_users_db = {
    "johndoe": {
        "username": "johndoe",