FastAPI will use the `response_model` parameter (that includes dataclasses) to convert the response.

You can combine `dataclasses` with other type annotations in many different combinations to form complex data structures.

Check the in-code annotation tips above to see more specific details.

## Learn More { #learn-more }

            CONTEXT: ${{ runner.os }}-py${{ matrix.python-version }}
        with:
          mode: simulation
          run: coverage run -m pytest tests/ --codspeed
      # Do not store coverage for all possible combinations to avoid file size max errors in Smokeshow
      - name: Store coverage files
        if: matrix.coverage == 'coverage'
        uses: actions/upload-artifact@v5
        with:

        <dslContextParameter.branch>master</dslContextParameter.branch>
        <project.build.sourceEncoding>UTF-8</project.build.sourceEncoding>
        <!-- https://kotlinlang.org/docs/maven.html#enable-incremental-compilation -->
        <kotlin.compiler.incremental>true</kotlin.compiler.incremental>
    </properties>
    <groupId>Gradle_Check</groupId>
    <artifactId>Gradle_Check_dsl</artifactId>
    <version>1.0-SNAPSHOT</version>

# Set lld as the linker.
common:cuda_clang --host_linkopt="-fuse-ld=lld"
common:cuda_clang --host_linkopt="-lm"
common:cuda_clang --linkopt="-fuse-ld=lld"
common:cuda_clang --linkopt="-lm"

# Set up compilation CUDA version and paths and use the CUDA Clang toolchain.
common:cuda_clang_official --config=cuda_clang
common:cuda_clang_official --config=cuda_version

# Build with nvcc for CUDA and clang for host