[RSDK-9631] Add deprecation warnings to DiscoverComponents

[randhid]

This PR adds warnings to client calls and Deprecation docstrings to the discover_components API in the robot client. To my knowledge, this SDK does not have a server side implementation of this API.

I also pre-emptively removed the tests that call this api - let me know if you'd rather keep those.

I don't usually contribute to the python sdk - so here are my local uv run make test warnings and failures - if they matter:

============================================================== FAILURES ===============================================================
____________________________________________________ test_ndarrays_to_flat_tensors ____________________________________________________

    @pytest.mark.filterwarnings("ignore::DeprecationWarning")
    def test_ndarrays_to_flat_tensors():
        output = ndarrays_to_flat_tensors(MockMLModel.INTS_NDARRAYS)
        assert len(output.tensors) == 4
        assert all(name in output.tensors.keys() for name in ["0", "1", "2", "3"])
        assert type(output.tensors["0"].int8_tensor.data) is builtins.bytes
        bytes_buffer = output.tensors["0"].int8_tensor.data
        assert np.array_equal(np.frombuffer(bytes_buffer, dtype=np.int8).reshape(output.tensors["0"].shape), MockMLModel.INT8_NDARRAY)
>       assert np.array_equal(np.array(output.tensors["1"].int16_tensor.data, dtype=np.int16), MockMLModel.INT16_NDARRAY)
E       OverflowError: Python integer 4294967295 out of bounds for int16

tests/test_mlmodel_utils.py:56: OverflowError
========================================================== warnings summary ===========================================================
tests/test_board.py::TestClient::test_stream_ticks
  /opt/homebrew/Cellar/[email protected]/3.13.1/Frameworks/Python.framework/Versions/3.13/lib/python3.13/asyncio/base_events.py:745: RuntimeWarning: coroutine method 'aclose' of 'BoardClient.stream_ticks.<locals>.read' was never awaited
    self._ready.clear()
  Enable tracemalloc to get traceback where the object was allocated.
  See https://docs.pytest.org/en/stable/how-to/capture-warnings.html#resource-warnings for more info.

-- Docs: https://docs.pytest.org/en/stable/how-to/capture-warnings.html
======================================================= short test summary info =======================================================
FAILED tests/test_mlmodel_utils.py::test_ndarrays_to_flat_tensors - OverflowError: Python integer 4294967295 out of bounds for int16
============================================== 1 failed, 645 passed, 1 warning in 12.27s ==============================================
make: *** [test] Error 1

[randhid]

[q] For reviewers - which one is better?