jobs:
  test:
    strategy:
      matrix:
        os: [ windows-latest, macos-latest ]
        python-version: [ "3.14" ]
        include:
          - os: ubuntu-latest
            python-version: "3.9"
            coverage: coverage
          - os: macos-latest
            python-version: "3.10"
            coverage: coverage
          - os: windows-latest
            python-version: "3.12"
            coverage: coverage

        type: string
        required: false
        default: ""

env:
  UV_SYSTEM_PYTHON: 1

jobs:
  langs:
    runs-on: ubuntu-latest
    outputs:
      langs: ${{ steps.show-langs.outputs.langs }}
      commands: ${{ steps.show-langs.outputs.commands }}
    steps:
      - uses: actions/checkout@v6
      - name: Set up Python

            <groupId>org.jetbrains.teamcity</groupId>
            <artifactId>configs-dsl-kotlin-latest</artifactId>
            <version>${teamcity.dsl.version}</version>
            <scope>compile</scope>
        </dependency>
        <dependency>
            <groupId>org.jetbrains.teamcity</groupId>
            <artifactId>configs-dsl-kotlin-plugins-latest</artifactId>
            <version>1.0-SNAPSHOT</version>
            <type>pom</type>

{* ../../docs_src/dataclasses_/tutorial001_py310.py hl[1,6:11,18:19] *}

Это по-прежнему поддерживается благодаря **Pydantic**, так как в нём есть <a href="https://docs.pydantic.dev/latest/concepts/dataclasses/#use-of-stdlib-dataclasses-with-basemodel" class="external-link" target="_blank">встроенная поддержка `dataclasses`</a>.

{* ../../docs_src/dataclasses_/tutorial001_py310.py hl[1,6:11,18:19] *}

Das ist dank **Pydantic** ebenfalls möglich, da es <a href="https://docs.pydantic.dev/latest/concepts/dataclasses/#use-of-stdlib-dataclasses-with-basemodel" class="external-link" target="_blank">`dataclasses` intern unterstützt</a>.

{* ../../docs_src/dataclasses_/tutorial001_py310.py hl[1,6:11,18:19] *}

This is still supported thanks to **Pydantic**, as it has <a href="https://docs.pydantic.dev/latest/concepts/dataclasses/#use-of-stdlib-dataclasses-with-basemodel" class="external-link" target="_blank">internal support for `dataclasses`</a>.

        triggerName = StageName.PULL_REQUEST_FEEDBACK.uuid,
    ) {
    init {
        id("Promotion_NightlyDocumentation")
        name = "Nightly Documentation"
        description =
            "Promotes the latest successful documentation changes on '${branch.branchName}' from Ready for Nightly as a new nightly documentation snapshot"

        triggers {
            branch.determineNightlyPromotionTriggerHour()?.let { triggerHour ->

{* ../../docs_src/dataclasses_/tutorial001_py310.py hl[1,6:11,18:19] *}

Isso ainda é suportado graças ao **Pydantic**, pois ele tem <a href="https://docs.pydantic.dev/latest/concepts/dataclasses/#use-of-stdlib-dataclasses-with-basemodel" class="external-link" target="_blank">suporte interno para `dataclasses`</a>.

{* ../../docs_src/dataclasses_/tutorial001_py310.py hl[1,6:11,18:19] *}

Esto sigue siendo soportado gracias a **Pydantic**, ya que tiene <a href="https://docs.pydantic.dev/latest/concepts/dataclasses/#use-of-stdlib-dataclasses-with-basemodel" class="external-link" target="_blank">soporte interno para `dataclasses`</a>.

        triggerName = "ReadyforNightly",
    ) {
    init {
        id(NIGHTLY_SNAPSHOT_BUILD_ID)
        name = "Nightly Snapshot"
        description =
            "Promotes the latest successful changes on '${branch.branchName}' from Ready for Nightly as a new nightly snapshot"

        triggers {
            val triggerHour = branch.determineNightlyPromotionTriggerHour() ?: return@triggers