You can return a `RedirectResponse` directly:

```Python hl_lines="2  9"
{!../../../docs_src/custom_response/tutorial006.py!}
```

---

Or you can use it in the `response_class` parameter:


```Python hl_lines="2  7  9"
{!../../../docs_src/custom_response/tutorial006b.py!}
```

    // Running at time 50, the pool returns that nothing can be evicted until time 150.
    assertThat(pool.closeConnections(50L)).isEqualTo(100L)
    assertThat(pool.connectionCount()).isEqualTo(1)
    assertThat(c1.socket().isClosed).isFalse()

    // Running at time 60, the pool returns that nothing can be evicted until time 150.
    assertThat(pool.closeConnections(60L)).isEqualTo(90L)

* Many PRs don't have tests, you can **remind** them to add tests, or you can even **suggest** some tests yourself. That's one of the things that consume most time and you can help a lot with that.

* Then also comment what you tried, that way I'll know that you checked it. 🤓

## Create a Pull Request

  //
  // List/watch requests for CertificateSigningRequests can filter on this field using a "spec.signerName=NAME" fieldSelector.
  //
  // Well-known Kubernetes signers are:
  //  1. "kubernetes.io/kube-apiserver-client": issues client certificates that can be used to authenticate to kube-apiserver.
  //   Requests for this signer are never auto-approved by kube-controller-manager, can be issued by the "csrsigning" controller in kube-controller-manager.

### Concurrency + Parallelism: Web + Machine Learning

With **FastAPI** you can take the advantage of concurrency that is very common for web development (the same main attraction of NodeJS).

But you can also exploit the benefits of parallelism and multiprocessing (having multiple processes running in parallel) for **CPU bound** workloads like those in Machine Learning systems.

    once you get into the running container so `bazel` can find the `tensorflow`
    workspace).

    you can do this by using the following command. As an example-

    ```bash
    docker run -it --rm -v $PWD:/tmp -w /tmp tensorflow/build:2.15-python3.10
    ```

    Once you have the packages installed, you can run a specific unit test in
    bazel by doing as follows:

    ```bash

message RollingUpdateDeployment {
  // The maximum number of pods that can be unavailable during the update.
  // Value can be an absolute number (ex: 5) or a percentage of desired pods (ex: 10%).
  // Absolute number is calculated from percentage by rounding down.
  // This can not be 0 if MaxSurge is 0.
  // By default, a fixed value of 1 is used.
  // Example: when this is set to 30%, the old RC can be scaled down to 70% of desired pods

message RollingUpdateDeployment {
  // The maximum number of pods that can be unavailable during the update.
  // Value can be an absolute number (ex: 5) or a percentage of desired pods (ex: 10%).
  // Absolute number is calculated from percentage by rounding down.
  // This can not be 0 if MaxSurge is 0.
  // Defaults to 25%.
  // Example: when this is set to 30%, the old ReplicaSet can be scaled down to 70% of desired pods

Let's see a very simple example. It will be so simple that it is not very useful, for now.

But this way we can focus on how the **Dependency Injection** system works.

### Create a dependency, or "dependable"

Let's first focus on the dependency.

It is just a function that can take all the same parameters that a *path operation function* can take:

=== "Python 3.10+"

    ```Python hl_lines="8-9"

This will let **FastAPI** know that this parameter is required.

### Required with `None`

You can declare that a parameter can accept `None`, but that it's still required. This would force clients to send a value, even if the value is `None`.

To do that, you can declare that `None` is a valid type but still use `...` as the default:

=== "Python 3.10+"

    ```Python hl_lines="9"