return OptionalEntity.empty();
    }

    /**
     * Gets the path to configuration files. In Docker environments, checks /opt/fess first,
     * then falls back to system property FESS_CONF_PATH, and finally to WEB-INF/conf.
     *
     * @param names the path components to append to the configuration directory
     * @return the Path object pointing to the configuration file or directory
     */

 * body.
 *
 * ### The response body can be consumed only once.
 *
 * This class may be used to stream very large responses. For example, it is possible to use this
 * class to read a response that is larger than the entire memory allocated to the current process.
 * It can even stream a response larger than the total storage on the current device, which is a

 * units away from 0 and 0.499 towards 0. The smallest unit this returns is "µs"; the largest unit
 * it returns is "s". For values in [-499..499] this returns "  0 µs".
 *
 * The returned string attempts to be column-aligned to 6 characters. For negative and large values
 * the returned string may be longer.
 */
fun formatDuration(ns: Long): String {
  val s =
    when {

 * in compliance with the License. You may obtain a copy of the License at
 *
 * http://www.apache.org/licenses/LICENSE-2.0
 *
 * Unless required by applicable law or agreed to in writing, software distributed under the License
 * is distributed on an "AS IS" BASIS, WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express

                    logger.warn("Failed to send error response. error={}", ioe.getMessage());
                }
            }
        }
    }

    /**
     * Sends a Server-Sent Event (SSE) to the client.
     *
     * @param writer the print writer to write the event to
     * @param event the event name
     * @param data the event data to serialize as JSON
     */

  )

  write_action_env_to_bazelrc('GCC_HOST_COMPILER_PATH', gcc_host_compiler_path)


def choose_compiler(environ_cp):
  question = 'Do you want to use Clang to build TensorFlow?'
  yes_reply = 'Clang will be used to compile TensorFlow.'
  no_reply = 'GCC will be used to compile TensorFlow.'
  var = int(
      get_var(
          environ_cp, 'TF_NEED_CLANG', None, True, question, yes_reply, no_reply
      )
  )

        if: env.HAS_SECRETS == 'true'
        with:
          # To be able to commit it needs to fetch the head of the branch, not the
          # merge commit
          ref: ${{ github.head_ref }}
          # And it needs the full history to be able to compute diffs
          fetch-depth: 0
          # A token other than the default GITHUB_TOKEN is needed to be able to trigger CI
          token: ${{ secrets.PRE_COMMIT }}

  * `--admission-control=...,PodSecurityPolicy,...`
* Use authorization to limit users' ability to use specific PodSecurityPolicy objects

**What is the impact?**

A user that is authorized to create pods can make use of any existing PodSecurityPolicy, even ones they are not authorized to use.

**How can I mitigate this prior to installing 1.5.5?**

1. Export existing PodSecurityPolicy objects:

  - If you work for a company that wants to allow you to contribute your work,
    then you'll need to sign a [corporate CLA][].

You generally only need to submit a CLA once, so if you've already submitted
one (even if it was for a different project), you probably don't need to do it
again.

[individual CLA]: https://cla.developers.google.com/about/google-individual
[corporate CLA]: https://cla.developers.google.com/about/google-corporate

    monthly_fee: float
    start_date: datetime


@app.webhooks.post("new-subscription")
def new_subscription(body: Subscription):
    """
    When a new user subscribes to your service we'll send you a POST request with this
    data to the URL that you register for the event `new-subscription` in the dashboard.
    """


@app.get("/users/")
def read_users():