Add tests for DateTimeSplitter with country (#486)

* Add callstack field to BrdigeRuntime exception (#483)

* Add exception stack to the error message

* Add callstack field

Co-authored-by: Gani Nazirov <ganaziro@microsoft.com>

* Add callstack field to BrdigeRuntime exception (#483)

* Add exception stack to the error message

* Add callstack field

Co-authored-by: Gani Nazirov <ganaziro@microsoft.com>

* revert "Add callstack field to BrdigeRuntime exception (#483)"

This reverts commit 569ea7b.

* add in DateTimeSplitter tests for country

* add in big tests for more featurizers

Co-authored-by: Gani Nazirov <ganinz@hotmail.com>
Co-authored-by: Gani Nazirov <ganaziro@microsoft.com>

src/python/tests_extended/test_dft_based.py

@@ -25,6 +25,8 @@
 TEST_CASES = {
     'DateTimeSplitter_Simple',
     'DateTimeSplitter_Complex',
+    'DateTimeSplitter_Canada_1day_before_christmas',
+    'DateTimeSplitter_Czech_non_english_holiday',
     'ToKey_SimpleFloat',
     'ToKey_SimpleDouble',
     'ToKey_SimpleString',
@@ -41,6 +43,8 @@
     'ShortGrainDropper',
     'RollingWin_Pivot_Integration',
     'Laglead_Pivot_Integration',
+    'Big_Test1',
+    'Big_Test2'
 }
 
 INSTANCES = {
@@ -62,6 +66,8 @@
                                     'dtAmPmLabel', 'dtDayOfWeekLabel', 'dtIsPaidTimeOff','dtHolidayName'
         ])
     ]),
+    'DateTimeSplitter_Canada_1day_before_christmas' : DateTimeSplitter(prefix='dt', country='Canada') << 'tokens1',
+    'DateTimeSplitter_Czech_non_english_holiday' : DateTimeSplitter(prefix='dt', country='Czech') << 'tokens1',
     'ToKey_SimpleFloat': ToKeyImputer(),
     'ToKey_SimpleDouble': ToKeyImputer(),
     'ToKey_SimpleString': ToKeyImputer(),
@@ -122,6 +128,34 @@
                         horizon=2),
         ForecastingPivot(columns_to_pivot=['colA1'])
     ]),
+    'Big_Test1': Pipeline([
+        TimeSeriesImputer(time_series_column='ts',
+                                filter_columns=['c', 'grain'],
+                                grain_columns=['grain'],
+                                impute_mode='ForwardFill',
+                                filter_mode='Include'),
+        DateTimeSplitter(prefix='dt') << 'ts',
+        LagLeadOperator(columns={'c1': 'c'},
+                           grain_columns=['dtMonthLabel'], 
+                           offsets=[-2, -1],
+                           horizon=1),
+        ForecastingPivot(columns_to_pivot=['c1']),
+        ColumnSelector(drop_columns=['dtHolidayName'])
+    ]),
+    'Big_Test2': Pipeline([
+        TimeSeriesImputer(time_series_column='ts',
+                                filter_columns=['c', 'grain'],
+                                grain_columns=['grain'],
+                                impute_mode='ForwardFill',
+                                filter_mode='Include'),
+        DateTimeSplitter(prefix='dt', country = 'Canada') << 'ts',
+        RollingWindow(columns={'c1': 'c'},
+                           grain_column=['grain'], 
+                           window_calculation='Mean',
+                           max_window_size=2,
+                           horizon=2),
+        ForecastingPivot(columns_to_pivot=['c1'])
+    ])
 }
 
 DATASETS = {
@@ -131,6 +165,12 @@
     'DateTimeSplitter_Complex': pd.DataFrame(data=dict(
                                 tokens1=[217081624, 1751241600, 217081625, 32445842582]
                                )),
+    'DateTimeSplitter_Canada_1day_before_christmas': pd.DataFrame(data=dict(
+                                tokens1=[157161599]
+                               )),
+    'DateTimeSplitter_Czech_non_english_holiday': pd.DataFrame(data=dict(
+                                tokens1=[3911760000, 3834432000, 3985200000]
+                               )),
     'ToKey_SimpleFloat': pd.DataFrame(data=dict(
                                     target=[1.0, 1.0, 1.0, 2.0]
                         )).astype({'target': np.float64}),
@@ -196,7 +236,17 @@
     'Laglead_Pivot_Integration': pd.DataFrame(data=dict(
                                     colA=[1.0, 2.0, 3.0, 4.0],
                                     grainA=["one", "one", "one", "one"]
-                                ))
+                                )),
+    'Big_Test1': pd.DataFrame(data=dict(
+            ts=[217081624, 217081625, 217081627, 217081629],
+            grain=[1970, 1970, 1970, 1970],
+            c=[10, 11, 12, 13]
+        )).astype({'ts': np.int64, 'grain': np.int32, 'c': np.double}),
+    'Big_Test2': pd.DataFrame(data=dict(
+            ts=[0, 86400, 172800],
+            grain=[1970, 1970, 1970],
+            c=[10, 11, 12]
+        )).astype({'ts': np.int64, 'grain': np.int32, 'c': np.double})
 }
 
 def get_file_size(file_path):