namespace tensorflow {
namespace parallel_device {

using TensorHandlePtr = tensorflow::Safe_TFE_TensorHandlePtr;

class ParallelTensor;
class DeviceThread;

// Forwards operations to `devices`, maintaining ParallelTensor with components
// placed on each underlying device.
class ParallelDevice {
 public:
  // Eager async execution is only supported when remote eager is not in use
  // (b/157523095).

 * changed. This provides binary compatibility for users who compiled against the old signatures.
 */
@Beta
@ElementTypesAreNonnullByDefault
abstract class GraphsBridgeMethods {

  @SuppressWarnings("PreferredInterfaceType")
  public static <N> Graph<N> transitiveClosure(Graph<N> graph) {
    return Graphs.transitiveClosure(graph);
  }

# `Request` class

You can declare a parameter in a *path operation function* or dependency to be of type `Request` and then you can access the raw request object directly, without any validation, etc.

You can import it directly from `fastapi`:

```python
from fastapi import Request
```

/// tip

from typing import Annotated

from fastapi import FastAPI, Path
from pydantic import BaseModel

app = FastAPI()


class Item(BaseModel):
    name: str
    description: str | None = None
    price: float
    tax: float | None = None


@app.put("/items/{item_id}")
async def update_item(
    item_id: Annotated[int, Path(title="The ID of the item to get", ge=0, le=1000)],
    q: str | None = None,
    item: Item | None = None,

from typing import Annotated

from fastapi import Depends, FastAPI

app = FastAPI()


fake_items_db = [{"item_name": "Foo"}, {"item_name": "Bar"}, {"item_name": "Baz"}]


class CommonQueryParams:
    def __init__(self, q: str | None = None, skip: int = 0, limit: int = 100):
        self.q = q
        self.skip = skip
        self.limit = limit


@app.get("/items/")

 *
 * @author Jared Levy
 * @author Robert Konigsberg
 * @author Mike Bostock
 * @author Louis Wasserman
 * @since 2.0
 */
@GwtCompatible(emulated = true)
@ElementTypesAreNonnullByDefault
public final class Multimaps {
  private Multimaps() {}

  /**
   * Returns a {@code Collector} accumulating entries into a {@code Multimap} generated from the

from datetime import datetime

from fastapi import FastAPI
from fastapi.encoders import jsonable_encoder
from pydantic import BaseModel

fake_db = {}


class Item(BaseModel):
    title: str
    timestamp: datetime
    description: str | None = None


app = FastAPI()


@app.put("/items/{id}")
def update_item(id: str, item: Item):
    json_compatible_item_data = jsonable_encoder(item)

plugins {
  kotlin("jvm")
  id("com.github.johnrengelman.shadow")
}

tasks.compileJava {
  options.isWarnings = false
}

tasks.jar {
  manifest {
    attributes("Main-Class" to "okhttp3.sample.SampleServer")
  }
}

dependencies {
  implementation(projects.mockwebserver)
}

tasks.shadowJar {
  mergeServiceFiles()

👉, 👆 ⚙️ `TestClient` `with` 📄, 🔗*️⃣:

```Python hl_lines="27-31"
{!../../docs_src/app_testing/tutorial002.py!}
```

/// note

🌅 ℹ, ✅ 💃 🧾 <a href="https://www.starlette.io/testclient/#testing-websocket-sessions" class="external-link" target="_blank">🔬 *️⃣ </a>.

# `HTTPConnection` class

When you want to define dependencies that should be compatible with both HTTP and WebSockets, you can define a parameter that takes an `HTTPConnection` instead of a `Request` or a `WebSocket`.

You can import it from `fastapi.requests`:

```python
from fastapi.requests import HTTPConnection
```