…ray-project#59933)

## Description
The `DefaultAutoscaler2` implementation needs an
`AutoscalingCoordinator` and a way to get all of the
`_NodeResourceSpec`.

Currently, we can't explicitly inject fake implementations of either
dependency. This is problematic because the tests need to assume what
the implementation of each dependency looks like and use brittle mocks.

To solve this:
- Add the `FakeAutoscalingCoordinator` implementation to a new
`fake_autoscaling_coordinator.py` module (you can use the code below)
- `DefaultClusterAutoscalerV2` has two new parameters
`autoscaling_coordinator: Optional[AutoscalingCoordinator] = None` and
`get_node_counts: Callable[[], Dict[_NodeResourceSpec, int]] =
get_node_resource_spec_and_count`. If `autoscaling_coordinator` is None,
you can use the default implementation.
- Update `test_try_scale_up_cluster` to use the explicit seams rather
than mocks. Where possible, assert against the public interface rather
than implementation details


## Related issues
Closes ray-project#59683

---------

Signed-off-by: 400Ping <fourhundredping@gmail.com>
Signed-off-by: Ping <fourhundredping@gmail.com>

…ray-project#59933)

## Description
The `DefaultAutoscaler2` implementation needs an
`AutoscalingCoordinator` and a way to get all of the
`_NodeResourceSpec`.

Currently, we can't explicitly inject fake implementations of either
dependency. This is problematic because the tests need to assume what
the implementation of each dependency looks like and use brittle mocks.

To solve this:
- Add the `FakeAutoscalingCoordinator` implementation to a new
`fake_autoscaling_coordinator.py` module (you can use the code below)
- `DefaultClusterAutoscalerV2` has two new parameters
`autoscaling_coordinator: Optional[AutoscalingCoordinator] = None` and
`get_node_counts: Callable[[], Dict[_NodeResourceSpec, int]] =
get_node_resource_spec_and_count`. If `autoscaling_coordinator` is None,
you can use the default implementation.
- Update `test_try_scale_up_cluster` to use the explicit seams rather
than mocks. Where possible, assert against the public interface rather
than implementation details

## Related issues
Closes ray-project#59683

---------

Signed-off-by: 400Ping <fourhundredping@gmail.com>
Signed-off-by: Ping <fourhundredping@gmail.com>
Signed-off-by: jeffery4011 <jefferyshen1015@gmail.com>

…ray-project#59933)

## Description
The `DefaultAutoscaler2` implementation needs an
`AutoscalingCoordinator` and a way to get all of the
`_NodeResourceSpec`.

Currently, we can't explicitly inject fake implementations of either
dependency. This is problematic because the tests need to assume what
the implementation of each dependency looks like and use brittle mocks.

To solve this:
- Add the `FakeAutoscalingCoordinator` implementation to a new
`fake_autoscaling_coordinator.py` module (you can use the code below)
- `DefaultClusterAutoscalerV2` has two new parameters
`autoscaling_coordinator: Optional[AutoscalingCoordinator] = None` and
`get_node_counts: Callable[[], Dict[_NodeResourceSpec, int]] =
get_node_resource_spec_and_count`. If `autoscaling_coordinator` is None,
you can use the default implementation.
- Update `test_try_scale_up_cluster` to use the explicit seams rather
than mocks. Where possible, assert against the public interface rather
than implementation details


## Related issues
Closes ray-project#59683

---------

Signed-off-by: 400Ping <fourhundredping@gmail.com>
Signed-off-by: Ping <fourhundredping@gmail.com>

…ray-project#59933)

## Description
The `DefaultAutoscaler2` implementation needs an
`AutoscalingCoordinator` and a way to get all of the
`_NodeResourceSpec`.

Currently, we can't explicitly inject fake implementations of either
dependency. This is problematic because the tests need to assume what
the implementation of each dependency looks like and use brittle mocks.

To solve this:
- Add the `FakeAutoscalingCoordinator` implementation to a new
`fake_autoscaling_coordinator.py` module (you can use the code below)
- `DefaultClusterAutoscalerV2` has two new parameters
`autoscaling_coordinator: Optional[AutoscalingCoordinator] = None` and
`get_node_counts: Callable[[], Dict[_NodeResourceSpec, int]] =
get_node_resource_spec_and_count`. If `autoscaling_coordinator` is None,
you can use the default implementation.
- Update `test_try_scale_up_cluster` to use the explicit seams rather
than mocks. Where possible, assert against the public interface rather
than implementation details


## Related issues
Closes ray-project#59683

---------

Signed-off-by: 400Ping <fourhundredping@gmail.com>
Signed-off-by: Ping <fourhundredping@gmail.com>

…ray-project#59933)

## Description
The `DefaultAutoscaler2` implementation needs an
`AutoscalingCoordinator` and a way to get all of the
`_NodeResourceSpec`.

Currently, we can't explicitly inject fake implementations of either
dependency. This is problematic because the tests need to assume what
the implementation of each dependency looks like and use brittle mocks.

To solve this:
- Add the `FakeAutoscalingCoordinator` implementation to a new
`fake_autoscaling_coordinator.py` module (you can use the code below)
- `DefaultClusterAutoscalerV2` has two new parameters
`autoscaling_coordinator: Optional[AutoscalingCoordinator] = None` and
`get_node_counts: Callable[[], Dict[_NodeResourceSpec, int]] =
get_node_resource_spec_and_count`. If `autoscaling_coordinator` is None,
you can use the default implementation.
- Update `test_try_scale_up_cluster` to use the explicit seams rather
than mocks. Where possible, assert against the public interface rather
than implementation details


## Related issues
Closes ray-project#59683

---------

Signed-off-by: 400Ping <fourhundredping@gmail.com>
Signed-off-by: Ping <fourhundredping@gmail.com>

…ray-project#59933)

## Description
The `DefaultAutoscaler2` implementation needs an
`AutoscalingCoordinator` and a way to get all of the
`_NodeResourceSpec`.

Currently, we can't explicitly inject fake implementations of either
dependency. This is problematic because the tests need to assume what
the implementation of each dependency looks like and use brittle mocks.

To solve this:
- Add the `FakeAutoscalingCoordinator` implementation to a new
`fake_autoscaling_coordinator.py` module (you can use the code below)
- `DefaultClusterAutoscalerV2` has two new parameters
`autoscaling_coordinator: Optional[AutoscalingCoordinator] = None` and
`get_node_counts: Callable[[], Dict[_NodeResourceSpec, int]] =
get_node_resource_spec_and_count`. If `autoscaling_coordinator` is None,
you can use the default implementation.
- Update `test_try_scale_up_cluster` to use the explicit seams rather
than mocks. Where possible, assert against the public interface rather
than implementation details

## Related issues
Closes ray-project#59683

---------

Signed-off-by: 400Ping <fourhundredping@gmail.com>
Signed-off-by: Ping <fourhundredping@gmail.com>
Signed-off-by: peterxcli <peterxcli@gmail.com>

…ray-project#59933)

## Description
The `DefaultAutoscaler2` implementation needs an
`AutoscalingCoordinator` and a way to get all of the
`_NodeResourceSpec`.

Currently, we can't explicitly inject fake implementations of either
dependency. This is problematic because the tests need to assume what
the implementation of each dependency looks like and use brittle mocks.

To solve this:
- Add the `FakeAutoscalingCoordinator` implementation to a new
`fake_autoscaling_coordinator.py` module (you can use the code below)
- `DefaultClusterAutoscalerV2` has two new parameters
`autoscaling_coordinator: Optional[AutoscalingCoordinator] = None` and
`get_node_counts: Callable[[], Dict[_NodeResourceSpec, int]] =
get_node_resource_spec_and_count`. If `autoscaling_coordinator` is None,
you can use the default implementation.
- Update `test_try_scale_up_cluster` to use the explicit seams rather
than mocks. Where possible, assert against the public interface rather
than implementation details

## Related issues
Closes ray-project#59683

---------

Signed-off-by: 400Ping <fourhundredping@gmail.com>
Signed-off-by: Ping <fourhundredping@gmail.com>
Signed-off-by: peterxcli <peterxcli@gmail.com>