tests: reduce hypothesis examples and ranges in dataset tests

- test_datasaver_1d: add max_examples=10, reduce n_points max 100 -> 50
- test_datasaver_arrays_of_different_length: add max_examples=10
  (was default 100)
- test_datasaver_array_parameters_channel (2 files): reduce N max
  500 -> 100
- test_datasaver_array_parameters_array: reduce N max 500 -> 100
- test_cache_1d: reduce max_examples from 10 to 5 (16 parametrize
  combos make this inherently expensive)

All tests verify correctness of data shapes and storage, not
performance at scale. Reduced ranges still provide good coverage.

Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com>

Author: jenshnielsen

tests/dataset/measurement/test_measurement_context_manager.py

@@ -1113,7 +1113,7 @@ def test_datasaver_arrayparams(
     deadline=None,
     suppress_health_check=(HealthCheck.function_scoped_fixture,),
 )
-@given(N=hst.integers(min_value=5, max_value=500))
+@given(N=hst.integers(min_value=5, max_value=100))
 @pytest.mark.parametrize("bg_writing", [True, False])
 @pytest.mark.parametrize("storage_type", ["numeric", "array"])
 @pytest.mark.usefixtures("experiment")
@@ -1633,7 +1633,7 @@ def test_datasaver_parameter_with_setpoints_reg_but_missing(
     deadline=None,
     suppress_health_check=(HealthCheck.function_scoped_fixture,),
 )
-@given(N=hst.integers(min_value=5, max_value=500))
+@given(N=hst.integers(min_value=5, max_value=100))
 @pytest.mark.usefixtures("experiment")
 @pytest.mark.parametrize("storage_type", ["numeric", "array"])
 @pytest.mark.parametrize("bg_writing", [True, False])
@@ -2166,7 +2166,7 @@ def test_datasaver_2d_multi_parameters_array(
 @pytest.mark.usefixtures("experiment")
 @pytest.mark.parametrize("bg_writing", [True, False])
 @pytest.mark.parametrize("storage_type", ["numeric", "array"])
-@settings(deadline=None)
+@settings(deadline=None, max_examples=10)
 @given(Ns=hst.lists(hst.integers(2, 10), min_size=2, max_size=5))
 def test_datasaver_arrays_of_different_length(storage_type, Ns, bg_writing) -> None:
     """

tests/dataset/measurement/test_shapes.py

@@ -11,9 +11,13 @@
     from pytest import LogCaptureFixture
 
 
-@given(n_points=hst.integers(min_value=1, max_value=100))
+@given(n_points=hst.integers(min_value=1, max_value=50))
 @example(n_points=5)
-@settings(deadline=None, suppress_health_check=(HealthCheck.function_scoped_fixture,))
+@settings(
+    deadline=None,
+    max_examples=10,
+    suppress_health_check=(HealthCheck.function_scoped_fixture,),
+)
 def test_datasaver_1d(
     experiment, DAC, DMM, caplog: "LogCaptureFixture", n_points
 ) -> None:

tests/dataset/test__get_data_from_ds.py

@@ -156,7 +156,7 @@ def test_datasaver_multidimarrayparameter_as_numeric(
     deadline=None,
     suppress_health_check=(HealthCheck.function_scoped_fixture,),
 )
-@given(N=hst.integers(min_value=5, max_value=500))
+@given(N=hst.integers(min_value=5, max_value=100))
 @pytest.mark.parametrize("bg_writing", [True, False])
 @pytest.mark.parametrize("storage_type", ["numeric", "array"])
 @pytest.mark.usefixtures("experiment")

tests/dataset/test_data_set_cache.py

@@ -191,7 +191,7 @@ def test_cache_standalone(
 @pytest.mark.parametrize("in_memory_cache", [True, False])
 @settings(
     deadline=None,
-    max_examples=10,
+    max_examples=5,
     suppress_health_check=(HealthCheck.function_scoped_fixture,),
 )
 @given(n_points=hst.integers(min_value=1, max_value=11))