* It takes each **request** that comes to your application.
* It can then do something to that **request** or run any needed code.
* Then it passes the **request** to be processed by the rest of the application (by some *path operation*).
* It then takes the **response** generated by the application (by some *path operation*).

### `HTMLResponse` { #htmlresponse }

Takes some text or bytes and returns an HTML response, as you read above.

### `PlainTextResponse` { #plaintextresponse }

Takes some text or bytes and returns a plain text response.

{* ../../docs_src/custom_response/tutorial005_py39.py hl[2,7,9] *}

### `JSONResponse` { #jsonresponse }

Takes some data and returns an `application/json` encoded response.

## Mounting a **FastAPI** application { #mounting-a-fastapi-application }

"Mounting" means adding a completely "independent" application in a specific path, that then takes care of handling everything under that path, with the _path operations_ declared in that sub-application.

### Top-level application { #top-level-application }

    }
  }

  /**
   * Generates test cases for the given combination of scenario and timeouts. For methods that take
   * an explicit timeout value, all of the given timeoutsToUse result in individual test cases. For
   * methods that do not take an explicit timeout value, a single test case is generated only if the
   * implicit timeout of that method matches the given timeoutsToUse. For example, enter() is

///

### What is "Mounting" { #what-is-mounting }

"Mounting" means adding a complete "independent" application in a specific path, that then takes care of handling all the sub-paths.

This is different from using an `APIRouter` as a mounted application is completely independent. The OpenAPI and docs from your main application won't include anything from the mounted application, etc.

Item ID: {{ id }}
```

{% endraw %}

...it will show the `id` taken from the "context" `dict` you passed:

```Python
{"id": id}
```

For example, with an ID of `42`, this would render:

```html
Item ID: 42
```

### Template `url_for` Arguments { #template-url-for-arguments }

That extra info will be added as-is to the output **JSON Schema** for that model, and it will be used in the API docs.

You can use the attribute `model_config` that takes a `dict` as described in <a href="https://docs.pydantic.dev/latest/api/config/" class="external-link" target="_blank">Pydantic's docs: Configuration</a>.

def baseVersion = gradleModule.identity.version.map { it.baseVersion.version }

dependencies {
    baseline("gradle:gradle:${compatibilityBaselineVersion}@zip")

    // This transform takes the Gradle zip distribution,
    // and unzips the Gradle jar files that it contains in a directory
    registerTransform(ExplodeZipAndFindJars) {
        from.attribute(ARTIFACT_TYPE, 'zip')

Let's start with a simple example:

{* ../../docs_src/python_types/tutorial001_py39.py *}

Calling this program outputs:

```
John Doe
```

The function does the following:

* Takes a `first_name` and `last_name`.
* Converts the first letter of each one to upper case with `title()`.

    ImmutableSet.Builder<BigInteger> testBigIntegersBuilder = ImmutableSet.builder();

    // The values here look like 111...11101...010 in binary, where the initial 111...1110 takes
    // up exactly as many bits as can be represented in the significand (24 for float, 53 for
    // double). That final 0 should be rounded up to 1 because the remaining bits make that number
    // slightly nearer.