public void testFromFluentFuture() {
    FluentFuture<String> f = FluentFuture.from(SettableFuture.<String>create());
    assertThat(FluentFuture.from(f)).isSameInstanceAs(f);
  }

  public void testFromFluentFuturePassingAsNonFluent() {
    ListenableFuture<String> f = FluentFuture.from(SettableFuture.<String>create());
    assertThat(FluentFuture.from(f)).isSameInstanceAs(f);
  }

from typing import TypeVar

from fastapi import Depends, FastAPI
from fastapi.testclient import TestClient
from typing_extensions import Annotated

app = FastAPI()

T = TypeVar("T")

Dep = Annotated[T, Depends()]


class A:
    pass


class B:
    pass


@app.get("/a")
async def a(dep: Dep[A]):
    return {"cls": dep.__class__.__name__}


@app.get("/b")
async def b(dep: Dep[B]):

            // release notes goes in the root of the docs
            task.from(extension.getReleaseNotes().getRenderedDocumentation());

            // DSL reference goes into dsl/
            task.from(extension.getDslReference().getRenderedDocumentation(), sub -> sub.into("dsl"));

            // Javadocs reference goes into javadoc/
            task.from(extension.getJavadocs().getRenderedDocumentation(), sub -> sub.into("javadoc"));

            spec.getDisplayName().set("DSL");
            spec.getSourceRoots().from(extension.getKotlinDslSource());
            spec.getSourceRoots().from(runtimeExtensions.flatMap(GradleKotlinDslRuntimeGeneratedSources::getGeneratedSources));
            spec.getClasspath().from(extension.getClasspath());
            spec.getClasspath().from(runtimeExtensions.flatMap(GradleKotlinDslRuntimeGeneratedSources::getGeneratedClasses));

from typing import Optional

from dirty_equals import IsDict
from fastapi import Depends, FastAPI, Security
from fastapi.security import OAuth2, OAuth2PasswordRequestFormStrict
from fastapi.testclient import TestClient
from pydantic import BaseModel

app = FastAPI()

reusable_oauth2 = OAuth2(
    flows={
        "password": {
            "tokenUrl": "token",
            "scopes": {"read:users": "Read the users", "write:users": "Create users"},

import pytest
from fastapi import FastAPI, HTTPException
from fastapi.exceptions import RequestValidationError
from fastapi.testclient import TestClient
from starlette.responses import JSONResponse


def http_exception_handler(request, exception):
    return JSONResponse({"exception": "http-exception"})


def request_validation_exception_handler(request, exception):
    return JSONResponse({"exception": "request-validation"})

from fastapi.testclient import TestClient

from docs_src.websockets.tutorial003 import app, html

client = TestClient(app)


def test_get():
    response = client.get("/")
    assert response.text == html


def test_websocket_handle_disconnection():
    with client.websocket_connect("/ws/1234") as connection, client.websocket_connect(
        "/ws/5678"
    ) as connection_two:
        connection.send_text("Hello from 1234")

        };
    }

    private boolean addEdge(Path from, Path p, DefaultModelProblemCollector problems) {
        try {
            dag.addEdge(from.toString(), p.toString());
            return true;
        } catch (Graph.CycleDetectedException e) {
            problems.add(new DefaultModelProblem(
                    "Cycle detected between models at " + from + " and " + p,
                    ModelProblem.Severity.FATAL,

    lenient_issubclass,
)
from fastapi.datastructures import DefaultPlaceholder, DefaultType
from pydantic import BaseModel, create_model
from pydantic.fields import FieldInfo
from typing_extensions import Literal

if TYPE_CHECKING:  # pragma: nocover
    from .routing import APIRoute

# Cache for `create_cloned_field`
_CLONED_TYPES_CACHE: MutableMapping[Type[BaseModel], Type[BaseModel]] = (
    WeakKeyDictionary()
)

import sysconfig

# pylint: disable=g-bad-import-order,protected-access,g-import-not-at-top
from tensorflow.python import pywrap_tensorflow  # pylint: disable=unused-import
from tensorflow.python.tools import module_util as _module_util
from tensorflow.python.platform import tf_logging as _logging
from tensorflow.python.util.lazy_loader import LazyLoader as _LazyLoader
from tensorflow.python.util.lazy_loader import KerasLazyLoader as _KerasLazyLoader