enabled = enableTriggers
        }
    } else if (stage.trigger != Trigger.never) {
        triggers.schedule {
            if (stage.trigger == Trigger.weekly) {
                schedulingPolicy = weekly {
                    dayOfWeek = ScheduleTrigger.DAY.Saturday
                    hour = 1
                }
            } else {
                schedulingPolicy = daily {

                        schedulingPolicy = daily {
                            this.hour = triggerHour
                        }
                    } else {
                        schedulingPolicy = weekly {
                            this.dayOfWeek = ScheduleTrigger.DAY.Saturday
                            this.hour = triggerHour
                        }
                    }
                    triggerBuild = always()

                PerformanceTestCoverage(5, PerformanceTestType.per_week, Os.LINUX, numberOfBuckets = 20, oldUuid = "PerformanceTestExperimentLinux"),
                PerformanceTestCoverage(8, PerformanceTestType.per_week, Os.WINDOWS, numberOfBuckets = 5),
                PerformanceTestCoverage(9, PerformanceTestType.per_week, Os.MACOS, numberOfBuckets = 5)
            )
        ),
        Stage(

[unassigned open issue](https://github.com/istio/istio/issues?q=is%3Aissue+is%3Aopen+label%3Aarea%2Fenvironments%2Foperator+no%3Aassignee),
creating a [bug or feature request](../BUGS-AND-FEATURE-REQUESTS.md),
or just coming to the weekly [Environments Working Group](https://github.com/istio/community/blob/master/WORKING-GROUPS.md)
meeting to share your ideas.

            "name": "The Baz"
        }
    ]
}
```

!!! info
    Notice how the `images` key now has a list of image objects.

## Deeply nested models

You can define arbitrarily deeply nested models:

=== "Python 3.10+"

    ```Python hl_lines="7  12  18  21  25"
    {!> ../../../docs_src/body_nested_models/tutorial007_py310.py!}
    ```

=== "Python 3.9+"

* Editor support, including:
    * Completion.
    * Type checks.
* Validation of data:
    * Automatic and clear errors when the data is invalid.
    * Validation even for deeply nested JSON objects.
* <abbr title="also known as: serialization, parsing, marshalling">Conversion</abbr> of input data: coming from the network to Python data and types. Reading from:
    * JSON.
    * Path parameters.

-   You make the change and submit it for the review again.
-   This cycle repeats itself until the PR gets approved.
-   Note: As a friendly reminder, we may reach out to you if the PR is awaiting
    your response for more than 2 weeks.

**4. Approved**

-   Once the PR is approved, it gets `kokoro:force-run` label applied and it
    initiates CI/CD tests.
-   We can't move forward if these tests fail.

> What’s the history of this project? It seems to have come from nowhere to awesome in a few weeks [...]

Here's a little bit of that history.

## Alternatives

Just functions that look the same as the *path operation functions*.

But still, it is very powerful, and allows you to declare arbitrarily deeply nested dependency "graphs" (trees).

!!! tip
    All this might not seem as useful with these simple examples.

    But you will see how useful it is in the chapters about **security**.

    * Use of hierarchical Pydantic models, Python `typing`’s `List` and `Dict`, etc.
    * And validators allow complex data schemas to be clearly and easily defined, checked and documented as JSON Schema.
    * You can have deeply **nested JSON** objects and have them all validated and annotated.
* **Extensible**:
    * Pydantic allows custom data types to be defined or you can extend validation with methods on a model decorated with the validator decorator.