For consistency, the same profiles are used across each chart, even if they do not impact a given chart.

Explicitly set values have highest priority, then profile settings, then chart defaults.

As an implementation detail of profiles, the default values for the chart are all nested under `defaults`.
When configuring the chart, you should not include this.

import org.jetbrains.kotlin.fir.symbols.impl.FirConstructorSymbol
import org.jetbrains.kotlin.name.Name

/**
 * [FirNonStaticMembersScope] includes non-static callables and inner classes.
 *
 * Inner classes are included because they are accessible from a value of the outer class. For example:
 *
 * ```
 * class Outer {
 *     inner class Inner
 * }
 *
 * fun foo() {
 *     val outer = Outer()
 *     outer.Inner()
 * }

## Project structure

Mostly a standard Maven project structure. The entry point `settings.kts` defines the TeamCity project.

There are 3 subprojects in the TeamCity project hierarchy: `Check` for Gradle builds, `Promotion` for releasing Gradle versions, `Util` for miscellaneous utilities.

## Develop and verify

system-installed Python packages. \
Instead, an independent Python toolchain is registered, ensuring the right
dependencies are always used. \
See https://github.com/bazelbuild/rules_python/ for more details.

### Specifying the Python version

Note: Only a number of minor Python versions are supported at any given time.

By default, the lowest supported version is used.

  (three value logic: yes, no, don't-care). The requiresOnline
  field in the mojo descriptor has the following semantics:

  [true] Online status is required for this mojo to function
         correctly.

  [false] <<(Default)>> Either status is acceptable for the mojo to
          execute. It doesn't care.

  The majority of mojos will leave the requiresOnline == false,

In the next sections you will see other options, configurations, and additional features.

!!! tip
    The next sections are **not necessarily "advanced"**.

    And it's possible that for your use case, the solution is in one of them.

## Read the Tutorial first

JSON, using the same [JSON Compatible Encoder](../tutorial/encoder.md){.internal-link target=_blank} explained in the tutorial. This is what allows you to return **arbitrary objects**, for example database models.

But if you are certain that the content that you are returning is **serializable with JSON**, you can pass it directly to the response class and avoid the extra overhead that FastAPI would have by passing your return content through the `jsonable_encoder` before passing it to the response...

# Custom Response Classes - File, HTML, Redirect, Streaming, etc.

There are several custom response classes you can use to create an instance and return them directly from your *path operations*.

Read more about it in the [FastAPI docs for Custom Response - HTML, Stream, File, others](https://fastapi.tiangolo.com/advanced/custom-response/).

You can import them directly from `fastapi.responses`:

```python
from fastapi.responses import (
    FileResponse,

      },
      logger = logger,
    )

  /** Runs all tasks that are ready. Used by the test thread only. */
  fun runTasks() {
    advanceUntil(nanoTime)
  }

  /** Advance the simulated clock, then runs tasks that are ready. Used by the test thread only. */
  fun advanceUntil(newTime: Long) {
    taskRunner.assertThreadDoesntHoldLock()

    val address = routePlanner.address
    val pool = routePlanner.pool

    // Connections are created as soon as a policy is set
    setPolicy(pool, address, ConnectionPool.AddressPolicy(2))
    assertThat(pool.connectionCount()).isEqualTo(2)

    // Connections are replaced if they idle out or are evicted from the pool
    evictAllConnections(pool)
    assertThat(pool.connectionCount()).isEqualTo(2)