```bash
    docker run -it --rm -v $PWD:/tmp -w /tmp tensorflow/build:2.15-python3.10
    ```

    Once you have the packages installed, you can run a specific unit test in
    bazel by doing as follows:

    ```bash
    export flags="--config=opt -k"
    ```

    If the tests are to be run on the GPU, add CUDA paths to LD_LIBRARY_PATH and
    add the `cuda` option flag

  private var nextQueueName = 10000
  private var coordinatorWaiting = false
  private var coordinatorWakeUpAt = 0L

  /**
   * When we need a new thread to run tasks, we call [Backend.execute]. A few microseconds later we
   * expect a newly-started thread to call [Runnable.run]. We shouldn't request new threads until
   * the already-requested ones are in service, otherwise we might create more threads than we need.
   *

   * True if this task faker has ever had multiple tasks scheduled to run concurrently. Guarded by
   * [TaskRunner.lock].
   */
  var isParallel = false

  /** Number of calls to [TaskRunner.Backend.execute]. Guarded by [TaskRunner.lock]. */
  var executeCallCount = 0

  /** Guarded by [taskRunner]. */
  var nanoTime = 0L
    private set

  /** Backlog of tasks to run. Only one task runs at a time. Guarded by [TaskRunner.lock]. */

    assertThat(log).containsExactly("run@100000")

    taskFaker.advanceUntil(150.µs)
    assertThat(log).containsExactly("run@100000", "run@150000")

    taskFaker.advanceUntil(299.µs)
    assertThat(log).containsExactly("run@100000", "run@150000")

    taskFaker.advanceUntil(300.µs)
    assertThat(log).containsExactly("run@100000", "run@150000", "run@300000")

    taskFaker.assertNoMoreTasks()

### Using your local FastAPI

If you create a Python file that imports and uses FastAPI, and run it with the Python from your local environment, it will use your cloned local FastAPI source code.

And if you update that local FastAPI source code when you run that Python file again, it will use the fresh version of FastAPI you just edited.

```Dockerfile
FROM python:3.9

WORKDIR /code

COPY ./requirements.txt /code/requirements.txt

RUN pip install --no-cache-dir --upgrade -r /code/requirements.txt

COPY ./app /code/app

CMD ["fastapi", "run", "app/main.py", "--port", "80"]

# If running behind a proxy like Nginx or Traefik add --proxy-headers
# CMD ["fastapi", "run", "app/main.py", "--port", "80", "--proxy-headers"]
```

</details>

## What is a Container

### Testing changes

After making changes, you can test your code in 2 ways:

1. Run tests.
- Run `./gradlew :<subproject>:quickTest` where `<subproject>` is the name of the subproject you've changed. 
- For example: `./gradlew :launcher:quickTest`.
2. Install Gradle locally and try out a change in behavior manually. 

        description = "Run cross-version tests against a limited set of versions"
        group = ciGroup
    }

    register("allVersionsCrossVersionTest") {
        description = "Run cross-version tests against all released versions (latest patch release of each)"
        group = ciGroup
    }

    register("allVersionsIntegMultiVersionTest") {

### Separate Program

To achieve this, you will normally have a **separate program** that would make sure your application is run on startup. And in many cases, it would also make sure other components or applications are also run, for example, a database.

### Example Tools to Run at Startup

Some examples of the tools that can do this job are:

* Docker
* Kubernetes
* Docker Compose
* Docker in Swarm Mode

	@(env bash $(PWD)/docs/site-replication/run-multi-site-minio-idp.sh)
	@echo "Running tests for automatic site replication of SSE-C objects"
	@(env bash $(PWD)/docs/site-replication/run-ssec-object-replication.sh)
	@echo "Running tests for automatic site replication of SSE-C objects with SSE-KMS enabled for bucket"
	@(env bash $(PWD)/docs/site-replication/run-sse-kms-object-replication.sh)