TST: Fix DIT tests

trace/tests/conftest.py

@@ -65,7 +65,7 @@ def qapp(qapp_args):
 
 
 @pytest.fixture
-def qtrace(qapp):
+def qtrace(qtbot, qapp):
     """Fixture for an instance of the TraceDisplay. Always uses an instance of
     PyDMApplication.
 
@@ -81,7 +81,7 @@ def qtrace(qapp):
 
     trace.close()
     qapp.processEvents()
-    del trace
+    trace.deleteLater()
 
 
 @pytest.fixture

trace/tests/test_widgets/test_archive_search.py

@@ -21,7 +21,12 @@ def search_wid(qapp):
     """
     # Set PYDM_ARCHIVER_URL so tests have a predictable state
     with patch.dict(os.environ, {"PYDM_ARCHIVER_URL": DUMMY_ARCHIVER_URL}):
-        yield ArchiveSearchWidget()
+        asw = ArchiveSearchWidget()
+        yield asw
+
+    asw.close()
+    qapp.processEvents()
+    asw.deleteLater()
 
 
 def create_dummy_reply(data: bytes = b"", error_code=QNetworkReply.NoError):

trace/tests/test_widgets/test_data_insight_tool.py

@@ -9,8 +9,10 @@
 from qtpy.QtCore import QByteArray
 from qtpy.QtNetwork import QNetworkReply
 
+from pydm.widgets.archiver_time_plot import ArchivePlotCurveItem
+
 from main import TraceDisplay
-from widgets.data_insight_tool import DataInsightTool
+from widgets.data_insight_tool import DataInsightTool, DataVisualizationModel
 
 DUMMY_ARCHIVER_URL = "dummy.archiver.url"
 
@@ -49,33 +51,53 @@
 
 
 @pytest.fixture
-def dit_wid(qtrace: TraceDisplay, monkeypatch, get_test_file):
+def dit_wid(qtrace: TraceDisplay):
     """Fixture for an instance of the DataInsightTool.
 
     Yields
     ------
     An instance of DataInsightTool.
     """
-    # Populate the model with data and give the first curve a unit
-    test_filename = get_test_file("test_file.trc")
-    test_data = json.loads(test_filename.read_text())["curves"]
+    # Set PYDM_ARCHIVER_URL so tests have a predictable state
+    with patch.dict(os.environ, {"PYDM_ARCHIVER_URL": DUMMY_ARCHIVER_URL}):
+        dit = DataInsightTool(qtrace, qtrace.curves_model, qtrace.ui.main_plot)
+        yield dit
 
-    qtrace.curves_model.set_model_curves(test_data)
-    curve_0 = qtrace.curves_model.curve_at_index(0)
-    curve_0.data_buffer = np.array([[6, 7, 8, 9, 10], [100, 101, 102, 103, 104]])
-    curve_0.units = test_data[0]["yAxisName"]
-    curve_1 = qtrace.curves_model.curve_at_index(1)
-    curve_1.data_buffer = np.array([[6, 7, 8, 9, 10], [200, 201, 202, 203, 204]])
+    dit.close()
+    dit.deleteLater()
 
-    def mock_caget(address: str, *args, **kwargs):
-        if address.endswith("EGU") or address.endswith(".DESC"):
-            return address
 
-    monkeypatch.setattr(epics, "caget", mock_caget)
+@pytest.fixture
+def dit_model():
+    """Fixture for an instance of the DataVisualizationModel.
 
-    # Set PYDM_ARCHIVER_URL so tests have a predictable state
-    with patch.dict(os.environ, {"PYDM_ARCHIVER_URL": DUMMY_ARCHIVER_URL}):
-        yield DataInsightTool(qtrace, qtrace.curves_model, qtrace.ui.main_plot)
+    Yields
+    ------
+    An instance of DataVisualizationModel.
+    """
+    dvm = DataVisualizationModel()
+    yield dvm
+    dvm.deleteLater()
+
+
+@pytest.fixture
+def mock_curve():
+    """Fixture for an instance of a mock ArchivePlotCurveItem object with preset
+    values for all attributes the DataVisualizationModel uses.
+
+    Yields
+    ------
+    An instance of ArchivePlotCurveItem.
+    """
+    curve_item = MagicMock(spec=ArchivePlotCurveItem)
+    curve_item.address = "KLYS:LI22:31:KVAC"
+    curve_item.units = "torr"
+    curve_item.min_x.return_value = 6
+    curve_item.max_x.return_value = 10
+    curve_item.getBufferSize.return_value = 5
+    curve_item.data_buffer = np.array([[6, 7, 8, 9, 10], [100, 101, 102, 103, 104]])
+
+    yield curve_item
 
 
 def create_dummy_reply(data: bytes = b"", error_code=QNetworkReply.NoError):
@@ -111,42 +133,48 @@ def test_data_visualization_qtmodeltester(qtmodeltester, dit_wid):
     qtmodeltester.check(dit_wid.data_vis_model, force_py=True)
 
 
-@pytest.mark.parametrize(
-    ["curve_ind", "expected_meta"], ((0, "torr, KLYS:LI22:31:KVAC.DESC"), (1, "KLYS:LI22:41:KVAC.DESC"))
-)
-def test_set_meta_data(dit_wid, curve_ind, expected_meta):
+def test_set_meta_data(dit_wid, mock_curve, monkeypatch):
     """Test DataInsightTool.set_meta_data() is successfully called when the selected
     PV is changed, and that set_meta_data sets the meta data label to the correct value.
 
     Parameters
     ----------
     dit_wid : fixture
         Instance of DataInsightTool for application testing
-    curve_ind : int
-        The index to set as the current index of the PV Selection Combobox
-    expected_meta : str
-        The expected text for the meta data label
+    mock_curve : fixture
+        A mock curve object with preset values for all attributes the DataVisualizationModel uses
+    monkeypatch : fixture
+        To override epics.caget
 
     Expectations
     ------------
     DataInsightTool.meta_data_label should contain the expected text for the given index
     """
-    dit_wid.pv_select_box.setCurrentIndex(curve_ind)
-    assert dit_wid.meta_data_label.text() == expected_meta
+
+    def mock_caget(address: str, *args, **kwargs):
+        if address.endswith("EGU") or address.endswith(".DESC"):
+            return address
+
+    monkeypatch.setattr(epics, "caget", mock_caget)
+
+    dit_wid.data_vis_model.set_all_data(mock_curve, (6, 9))
+    dit_wid.set_meta_data()
+
+    assert dit_wid.meta_data_label.text() == "torr, KLYS:LI22:31:KVAC.DESC"
 
 
 @pytest.mark.parametrize(
     ("extension", "expected_data"),
     ((".csv", CSV_TEST_DATA), (".json", JSON_TEST_DATA)),
 )
-def test_export_data_success(dit_wid, tmp_path, extension, expected_data):
+def test_export_data_success(dit_model, tmp_path, extension, expected_data):
     """Test DataVisualizationModel.export_data() successfully writes a file and it
     matches the expected output.
 
     Parameters
     ----------
-    dit_wid : fixture
-        Instance of DataInsightTool for application testing
+    dit_model : fixture
+        Instance of DataVisualizationModel for application testing
     tmp_path : fixture
          A fixture which will provide a temporary directory unique to each test function
     extension : str
@@ -159,27 +187,30 @@ def test_export_data_success(dit_wid, tmp_path, extension, expected_data):
     DataInsightTool and DataVisualizationModel will make a file with the expected name and content.
     """
     # Construct testcase
-    model_df = dit_wid.data_vis_model.df
-    model_df["Datetime"] = [6, 7, 8, 9, 10]
-    model_df["Datetime"] = model_df["Datetime"].apply(datetime.fromtimestamp, tz=timezone.utc)
-    model_df["Value"] = [100, 101, 102, 103, 104]
-    model_df["Severity"] = ["NaN"] * 5
-    model_df["Source"] = ["Live"] * 5
+    dit_model.address = "KLYS:LI22:31:KVAC"
+    dit_model.unit = "torr"
+    dit_model.description = "KLYS:LI22:31:KVAC.DESC"
+    dit_model.df["Datetime"] = [6, 7, 8, 9, 10]
+    dit_model.df["Datetime"] = dit_model.df["Datetime"].apply(datetime.fromtimestamp, tz=timezone.utc)
+    dit_model.df["Value"] = [100, 101, 102, 103, 104]
+    dit_model.df["Severity"] = ["NaN"] * 5
+    dit_model.df["Source"] = ["Live"] * 5
+
     file = tmp_path / f"test_export_data_success{extension}"
-    dit_wid.data_vis_model.export_data(file, extension)
+    dit_model.export_data(file, extension)
 
     assert file.is_file()
     assert file.read_text() == expected_data
 
 
-def test_export_data_dir(dit_wid, tmp_path):
+def test_export_data_dir(dit_model, tmp_path):
     """Test DataVisualizationModel.export_data() is interrupted when the provided filename
     is a directory.
 
     Parameters
     ----------
-    dit_wid : fixture
-        Instance of DataInsightTool for application testing
+    dit_model : fixture
+        Instance of DataVisualizationModel for application testing
     tmp_path : fixture
         A fixture which will provide a temporary directory unique to each test function
 
@@ -188,29 +219,28 @@ def test_export_data_dir(dit_wid, tmp_path):
     No files/directories should be made and the logger should give a warning.
     """
     # Construct testcase
-    model_df = dit_wid.data_vis_model.df
-    model_df["Datetime"] = [6, 7, 8, 9, 10]
-    model_df["Datetime"] = model_df["Datetime"].apply(datetime.fromtimestamp, tz=timezone.utc)
-    model_df["Value"] = [100, 101, 102, 103, 104]
-    model_df["Severity"] = ["NaN"] * 5
-    model_df["Source"] = ["Live"] * 5
+    dit_model.df["Datetime"] = [6, 7, 8, 9, 10]
+    dit_model.df["Datetime"] = dit_model.df["Datetime"].apply(datetime.fromtimestamp, tz=timezone.utc)
+    dit_model.df["Value"] = [100, 101, 102, 103, 104]
+    dit_model.df["Severity"] = ["NaN"] * 5
+    dit_model.df["Source"] = ["Live"] * 5
 
     with pytest.raises(IsADirectoryError) as exc_info:
-        dit_wid.data_vis_model.export_data(tmp_path, "")
+        dit_model.export_data(tmp_path, "")
     assert exc_info.type is IsADirectoryError
 
     assert not tmp_path.is_file()
 
 
-def test_export_data_invalid_extension(dit_wid, tmp_path):
+def test_export_data_invalid_extension(dit_model, tmp_path):
     """Test DataVisualizationModel.export_data() is interrupted when the provided filename
     has an extension other than *.csv, *.mat, or *.json . Needed to make a valid file after to prevent
     a recursive loop.
 
     Parameters
     ----------
-    dit_wid : fixture
-        Instance of DataInsightTool for application testing
+    dit_model : fixture
+        Instance of DataVisualizationModel for application testing
     tmp_path : fixture
         A fixture which will provide a temporary directory unique to each test function
 
@@ -219,64 +249,63 @@ def test_export_data_invalid_extension(dit_wid, tmp_path):
     An error should be given when trying to make the *.xlsx file, but *.csv succeeds.
     """
     # Construct testcase
-    model_df = dit_wid.data_vis_model.df
-    model_df["Datetime"] = [6, 7, 8, 9, 10]
-    model_df["Datetime"] = model_df["Datetime"].apply(datetime.fromtimestamp, tz=timezone.utc)
-    model_df["Value"] = [100, 101, 102, 103, 104]
-    model_df["Severity"] = ["NaN"] * 5
-    model_df["Source"] = ["Live"] * 5
+    dit_model.df["Datetime"] = [6, 7, 8, 9, 10]
+    dit_model.df["Datetime"] = dit_model.df["Datetime"].apply(datetime.fromtimestamp, tz=timezone.utc)
+    dit_model.df["Value"] = [100, 101, 102, 103, 104]
+    dit_model.df["Severity"] = ["NaN"] * 5
+    dit_model.df["Source"] = ["Live"] * 5
 
     file_xlsx = tmp_path / "test_export_save_file_invalid_extension.xlsx"
 
     with pytest.raises(ValueError) as exc_info:
-        dit_wid.data_vis_model.export_data(file_xlsx, ".xlsx")
+        dit_model.export_data(file_xlsx, ".xlsx")
     assert exc_info.type is ValueError
     assert not file_xlsx.is_file()
 
 
 @pytest.mark.parametrize(
-    ("curve_ind", "x_range", "expected_data"),
+    ("x_range", "expected_data"),
     (
-        (0, (5, 11), ([6, 7, 8, 9, 10], [100, 101, 102, 103, 104])),
-        (0, (7.5, 9.5), ([8, 9], [102, 103])),
-        (1, (6.5, 9.5), ([7, 8, 9], [201, 202, 203])),
+        ((5, 11), ([6, 7, 8, 9, 10], [100, 101, 102, 103, 104])),
+        ((7.5, 9.5), ([8, 9], [102, 103])),
     ),
 )
-def test_model_set_live_data(dit_wid, curve_ind, x_range, expected_data):
+def test_model_set_live_data(dit_model, x_range, expected_data, mock_curve):
     """Test DataVisualizationModel.set_live_data() stores the correct data from
     the curves_model into its DataFrame.
 
     Parameters
     ----------
-    dit_wid : fixture
-        Instance of DataInsightTool for application testing
+    dit_model : fixture
+        Instance of DataVisualizationModel for application testing
     curve_ind : int
         The index corresponding to a curve in the curves_model
     expected_data : tuple
         The expected data to be stored in the Datetime and Value columns of the DataFrame
+    mock_curve : fixture
+        A mock curve object with preset values for all attributes the DataVisualizationModel uses
 
     Expectations
     ------------
     DataVisualizationModel.df contains the expected Datetime and Value values for the given curve.
     """
-    curve_item = dit_wid.curves_model.curve_at_index(curve_ind)
-    mod = dit_wid.data_vis_model
-    mod.set_live_data(curve_item, x_range)
 
-    assert mod.df["Datetime"].apply(datetime.timestamp).to_list() == expected_data[0]
-    assert mod.df["Value"].to_list() == expected_data[1]
+    dit_model.set_live_data(mock_curve, x_range)
+
+    assert dit_model.df["Datetime"].apply(datetime.timestamp).to_list() == expected_data[0]
+    assert dit_model.df["Value"].to_list() == expected_data[1]
 
 
-def test_model_get_archive_data_success(qtbot, dit_wid, mock_logger):
+def test_model_get_archive_data_success(qtbot, dit_model, mock_logger):
     """Test DataVisualizationModel.get_archive_data() stores the correct data from
     the Archiver Appliance into its DataFrame.
 
     Parameters
     ----------
     qtbot : fixture
         pytest-qt window for widget testing
-    dit_wid : fixture
-        Instance of DataInsightTool for application testing
+    dit_model : fixture
+        Instance of DataVisualizationModel for application testing
     mock_logger : fixture
         A fixture used for mocking the logger's warning and error methods
 
@@ -286,29 +315,28 @@ def test_model_get_archive_data_success(qtbot, dit_wid, mock_logger):
     called, and DataVisualizationModel.df contains the expected Datetime and Value
     values for the given curve.
     """
+    mock_logger.debug.reset_mock()
     reply_str = json.dumps(ARCH_TEST_DATA).encode()
     reply = create_dummy_reply(data=reply_str)
 
-    mod = dit_wid.data_vis_model
-
-    with qtbot.waitSignal(mod.reply_recieved, timeout=100):
-        mod.recieve_archive_reply(reply)
+    with qtbot.waitSignal(dit_model.reply_recieved, timeout=100):
+        dit_model.recieve_archive_reply(reply)
 
     mock_logger.debug.assert_not_called()
-    assert mod.df["Datetime"].apply(datetime.timestamp).to_list() == [1, 2, 3, 4, 5]
-    assert mod.df["Value"].to_list() == [95, 96, 97, 98, 99]
+    assert dit_model.df["Datetime"].apply(datetime.timestamp).to_list() == [1, 2, 3, 4, 5]
+    assert dit_model.df["Value"].to_list() == [95, 96, 97, 98, 99]
 
 
-def test_model_get_archive_data_error(qtbot, dit_wid, mock_logger):
+def test_model_get_archive_data_error(qtbot, dit_model, mock_logger):
     """Test DataVisualizationModel.get_archive_data() does nothing when an error
     is recieved from the Archiver Appliance.
 
     Parameters
     ----------
     qtbot : fixture
         pytest-qt window for widget testing
-    dit_wid : fixture
-        Instance of DataInsightTool for application testing
+    dit_model : fixture
+        Instance of DataVisualizationModel for application testing
     mock_logger : fixture
         A fixture used for mocking the logger's warning and error methods
 
@@ -317,8 +345,9 @@ def test_model_get_archive_data_error(qtbot, dit_wid, mock_logger):
     DataVisualizationModel.recieve_archive_reply is emitted, logger.debug is called,
     and DataVisualizationModel.df does not contain any extra data.
     """
+    mock_logger.debug.reset_mock()
     error_reply = create_dummy_reply(error_code=QNetworkReply.UnknownServerError)
 
-    with qtbot.waitSignal(dit_wid.data_vis_model.reply_recieved, timeout=100):
-        dit_wid.data_vis_model.recieve_archive_reply(error_reply)
+    with qtbot.waitSignal(dit_model.reply_recieved, timeout=100):
+        dit_model.recieve_archive_reply(error_reply)
     mock_logger.debug.assert_called_once()