from fastapi import Body, FastAPI
from fastapi.testclient import TestClient
from pydantic import BaseModel

app = FastAPI()

media_type = "application/vnd.api+json"


# NOTE: These are not valid JSON:API resources
# but they are fine for testing requestBody with custom media_type
class Product(BaseModel):
    name: str
    price: float


class Shop(BaseModel):
    name: str


@app.post("/products")

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
import subprocess
import sys
from junitparser import JUnitXml

result = JUnitXml()
try:

    collected using form data (instead of JSON) and that it should have the specific
    fields `username` and `password`.

    All the initialization parameters are extracted from the request.

    Read more about it in the
    [FastAPI docs for Simple OAuth2 with Password and Bearer](https://fastapi.tiangolo.com/tutorial/security/simple-oauth2/).

    ## Example

    ```python

        raise fastapi.exceptions.FastAPIError(
            "Invalid args for response field! Hint: "
            f"check that {type_} is a valid Pydantic field type. "
            "If you are using a return type annotation that is not a valid Pydantic "
            "field (e.g. Union[Response, dict, None]) you can disable generating the "
            "response model from the type annotation with the path operation decorator "

          f'Bazel invocations.\n'
          f'ResultStore contains individual representations of each target '
          f'that were run/built during the invocation.\n'
          f'These results are generally easier to read than looking through '
          f'the entire build log:\n')
  i = 1
  for url, invocation_results in result_store_dict.items():
    line_str = f'Invocation #{i} ({invocation_results["status"]}):\n'

            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.
            )
            """
        ),
    ] = None,
    use_cache: Annotated[
        bool,
        Doc(

TensorFlow via the command `import tensorflow as tf`.

The primary function of this module is to import all of the public TensorFlow
interfaces into a single place. The interfaces themselves are located in
sub-modules, as described below.

Note that the file `__init__.py` in the TensorFlow source code tree is actually
only a placeholder to enable test cases to run. The TensorFlow build replaces

    The code before yield and the code after yield should be run in the same contextvar
    context, so that request_state_context_var.reset(contextvar_token).

    If they are run in a different context, that raises an error.
    """
    response = client.get("/user")
    assert response.json() == "deadpond"

            )
        else:
            return None

    def _create_credentials_fetcher(self):
        method = self.METHOD

        def fetch_credentials():
            # HTTP headers are case insensitive filter out
            # all duplicate headers and pick one.
            headers = {}
            headers['content-type'] = 'application/x-www-form-urlencoded'

    comment_id: Union[str, None] = None,
    body: Union[str, None] = None,
) -> Dict[str, Any]:
    headers = {"Authorization": f"token {settings.input_token.get_secret_value()}"}
    # some fields are only used by one query, but GraphQL allows unused variables, so
    # keep them here for simplicity
    variables = {
        "after": after,
        "category_id": category_id,