HttpURLConnection.HTTP_NO_CONTENT, HttpURLConnection.HTTP_RESET -> {
        builder.body("") // We forbid bodies for 204 and 205.
      }
    }
    server.enqueue(builder.build())
    if (responseCode == HttpURLConnection.HTTP_CLIENT_TIMEOUT) {
      // 408's are a bit of an outlier because we may repeat the request if we encounter this
      // response code. In this scenario, there are 2 responses: the initial 408 and then the 200

TLS (HTTPS) uses the specific port `443` by default. So that's the port we would need.

As only one process can be listening on this port, the process that would do it would be the **TLS Termination Proxy**.

    lock.assertHeld()

    // If this connection is not accepting new exchanges, we're done.
    if (calls.size >= allocationLimit || noNewExchanges) return false

    // If the non-host fields of the address don't overlap, we're done.
    if (!this.route.address.equalsNonHost(address)) return false

    // If the host exactly matches, we're done: this connection can carry the address.

```

By declaring a *path operation function* parameter with the type being the `Request` **FastAPI** will know to pass the `Request` in that parameter.

!!! tip
    Note that in this case, we are declaring a path parameter beside the request parameter.

    So, the path parameter will be extracted, validated, converted to the specified type and annotated with OpenAPI.

# function as an implicit first `if` for every automation in the file.

# You can define multiple automations in a .cm file, but each automation name should be unique
# within the file.  We keep each automation (or very closely related group of automations) in
# its own file.

on:
  - pr_created
  - commit
  - comment_added

automations:

  # Label changes by affected platforms (in blue)

Let's continue from the previous example. We wanted to **annotate the function with one type** but return something that includes **more data**.

We want FastAPI to keep **filtering** the data using the response model.

In the previous example, because the classes were different, we had to use the `response_model` parameter. But that also means that we don't get the support from the editor and tools checking the function return type.

    ```

But that is still not that useful.

Let's make it give us the current user.

## Create a user model

First, let's create a Pydantic user model.

The same way we use Pydantic to declare bodies, we can use it anywhere else:

=== "Python 3.10+"

    ```Python hl_lines="5  12-16"
    {!> ../../../docs_src/security/tutorial002_an_py310.py!}
    ```

=== "Python 3.9+"

        // The elements in the list are so small that they can't even be divided into {expectedBucketNumber}.
        // For example, how do you split [0,0,0,0,0] into 3 buckets?
        // In this case, we simply put the elements into these buckets evenly.
        return list.chunked(list.size / expectedBucketNumber, smallElementAggregateFunction)
    }

    val largestElement = list.removeFirst()!!

          if (rule.startsWith(EXCEPTION_RULE_MARKER)) {
            rule = rule.substring(1)
            // We use '\n' for end of value.
            totalExceptionRuleBytes += rule.size + 1
            sortedExceptionRules.add(rule)
          } else {
            totalRuleBytes += rule.size + 1 // We use '\n' for end of value.
            sortedRules.add(rule)
          }
        }
      }

    🚥 🚫 🚚, ⚫️ `None` 🔢, 📥 👥 🚚 `"World"` 🔢 💲 ⚙️.

⤴️ 👆 💪 🤙 👈 🐍 📋:

<div class="termy">

```console
// Here we don't set the env var yet
$ python main.py

// As we didn't set the env var, we get the default value

Hello World from Python

// But if we create an environment variable first
$ export MY_NAME="Wade Wilson"

// And then call the program again
$ python main.py