// Rules can either apply to API resources (such as "pods" or "secrets") or non-resource URL paths (such as "/api"),  but not both.
  // +optional
  repeated string nonResourceURLs = 5;
}

// Role is a namespaced, logical grouping of PolicyRules that can be referenced as a unit by a RoleBinding.
message Role {
  // Standard object's metadata.

# Path Parameters and Numeric Validations

In the same way that you can declare more validations and metadata for query parameters with `Query`, you can declare the same type of validations and metadata for path parameters with `Path`.

## Import Path

First, import `Path` from `fastapi`, and import `Annotated`:

=== "Python 3.10+"

    ```Python hl_lines="1  3"
    {!> ../../../docs_src/path_params_numeric_validations/tutorial001_an_py310.py!}
    ```

# Declare Request Example Data

You can declare examples of the data your app can receive.

Here are several ways to do it.

## Extra JSON Schema data in Pydantic models

You can declare `examples` for a Pydantic model that will be added to the generated JSON Schema.

=== "Python 3.10+ Pydantic v2"

    ```Python hl_lines="13-24"
    {!> ../../../docs_src/schema_extra_example/tutorial001_py310.py!}
    ```

    ```

!!! tip
    You can set a dependency override for a dependency used anywhere in your **FastAPI** application.

    The original dependency could be used in a *path operation function*, a *path operation decorator* (when you don't use the return value), a `.include_router()` call, etc.

    FastAPI will still be able to override it.

# Response Headers

## Use a `Response` parameter

You can declare a parameter of type `Response` in your *path operation function* (as you can do for cookies).

And then you can set headers in that *temporal* response object.

```Python hl_lines="1  7-8"
{!../../../docs_src/response_headers/tutorial002.py!}
```

And then you can return any object you need, as you normally would (a `dict`, a database model, etc).

!!! info
    Keep in mind that dataclasses can't do everything Pydantic models can do.

    So, you might still need to use Pydantic models.

    But if you have a bunch of dataclasses laying around, this is a nice trick to use them to power a web API using FastAPI. 🤓

## Dataclasses in `response_model`

You can also use `dataclasses` in the `response_model` parameter:

representative of real-world HTTPS deployment. To get closer to that we can use `HeldCertificate`
to generate a trusted root certificate, an intermediate certificate, and a server certificate.
We use `certificateAuthority(int)` to create certificates that can sign other certificates. The
int specifies how many intermediate certificates are allowed beneath it in the chain.

```java

When defining WebSockets, you normally declare a parameter of type `WebSocket` and with it you can read data from the client and send data to it.

It is provided directly by Starlette, but you can import it from `fastapi`:

```python
from fastapi import WebSocket
```

!!! tip
    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`.

  # minimum number of available replicas to 1, you can update this value as follows:
  #
  # podDisruptionBudget:
  #   minAvailable: 1
  #
  # Or, to allow a maximum of 1 unavailable replica, you can set:
  #
  # podDisruptionBudget:
  #   maxUnavailable: 1
  #

      value: >
        Comparing two approaches to a use case side by side can make it easier to examine the
        differences between them.


        Additionally, it's very useful to us if you can provide a "straw API" — what the
        method signatures would look like, for example, even if the method and class names are still
        in flux. This can make the feature you're suggesting much clearer to us.

  - type: textarea