FIX-modin-project#6624: Add FutureWarnings for first/last/bool (m…

…odin-project#6625)

Signed-off-by: Anatoly Myachev <anatoly.myachev@intel.com>

modin/pandas/base.py

@@ -1130,6 +1130,11 @@ def bool(self):  # noqa: RT01, D200
         """
         Return the bool of a single element `BasePandasDataset`.
         """
+        warnings.warn(
+            f"{type(self).__name__}.bool is now deprecated and will be removed "
+            + "in future version of pandas",
+            FutureWarning,
+        )
         shape = self.shape
         if shape != (1,) and shape != (1, 1):
             raise ValueError(
@@ -1757,6 +1762,11 @@ def first(self, offset):  # noqa: PR01, RT01, D200
         """
         Select initial periods of time series data based on a date offset.
         """
+        warnings.warn(
+            "first is deprecated and will be removed in a future version. "
+            + "Please create a mask and filter using `.loc` instead",
+            FutureWarning,
+        )
         return self._create_or_update_from_compiler(
             self._query_compiler.first(offset=to_offset(offset))
         )
@@ -1913,6 +1923,12 @@ def last(self, offset):  # noqa: PR01, RT01, D200
         """
         Select final periods of time series data based on a date offset.
         """
+        warnings.warn(
+            "last is deprecated and will be removed in a future version. "
+            + "Please create a mask and filter using `.loc` instead",
+            FutureWarning,
+        )
+
         return self._create_or_update_from_compiler(
             self._query_compiler.last(offset=to_offset(offset))
         )

modin/pandas/test/dataframe/test_default.py

@@ -53,7 +53,19 @@
 # Our configuration in pytest.ini requires that we explicitly catch all
 # instances of defaulting to pandas, but some test modules, like this one,
 # have too many such instances.
-pytestmark = pytest.mark.filterwarnings(default_to_pandas_ignore_string)
+pytestmark = [
+    pytest.mark.filterwarnings(default_to_pandas_ignore_string),
+    # IGNORE FUTUREWARNINGS MARKS TO CLEANUP OUTPUT
+    pytest.mark.filterwarnings(
+        "ignore:.*bool is now deprecated and will be removed:FutureWarning"
+    ),
+    pytest.mark.filterwarnings(
+        "ignore:first is deprecated and will be removed:FutureWarning"
+    ),
+    pytest.mark.filterwarnings(
+        "ignore:last is deprecated and will be removed:FutureWarning"
+    ),
+]
 
 
 @pytest.mark.parametrize(
@@ -188,9 +200,12 @@ def test_bfill(data):
 def test_bool(data):
     modin_df = pd.DataFrame(data)
 
-    with pytest.raises(ValueError):
-        modin_df.bool()
-        modin_df.__bool__()
+    with pytest.warns(
+        FutureWarning, match="bool is now deprecated and will be removed"
+    ):
+        with pytest.raises(ValueError):
+            modin_df.bool()
+            modin_df.__bool__()
 
     single_bool_pandas_df = pandas.DataFrame([True])
     single_bool_modin_df = pd.DataFrame([True])
@@ -446,7 +461,9 @@ def test_first():
     pandas_df = pandas.DataFrame(
         {"A": list(range(400)), "B": list(range(400))}, index=i
     )
-    df_equals(modin_df.first("3D"), pandas_df.first("3D"))
+    with pytest.warns(FutureWarning, match="first is deprecated and will be removed"):
+        modin_result = modin_df.first("3D")
+    df_equals(modin_result, pandas_df.first("3D"))
     df_equals(modin_df.first("20D"), pandas_df.first("20D"))
 
 
@@ -522,7 +539,9 @@ def test_last():
     pandas_df = pandas.DataFrame(
         {"A": list(range(400)), "B": list(range(400))}, index=pandas_index
     )
-    df_equals(modin_df.last("3D"), pandas_df.last("3D"))
+    with pytest.warns(FutureWarning, match="last is deprecated and will be removed"):
+        modin_result = modin_df.last("3D")
+    df_equals(modin_result, pandas_df.last("3D"))
     df_equals(modin_df.last("20D"), pandas_df.last("20D"))
 
 

modin/pandas/test/test_series.py

@@ -89,7 +89,19 @@
 # have too many such instances.
 # TODO(https://github.com/modin-project/modin/issues/3655): catch all instances
 # of defaulting to pandas.
-pytestmark = pytest.mark.filterwarnings(default_to_pandas_ignore_string)
+pytestmark = [
+    pytest.mark.filterwarnings(default_to_pandas_ignore_string),
+    # IGNORE FUTUREWARNINGS MARKS TO CLEANUP OUTPUT
+    pytest.mark.filterwarnings(
+        "ignore:.*bool is now deprecated and will be removed:FutureWarning"
+    ),
+    pytest.mark.filterwarnings(
+        "ignore:first is deprecated and will be removed:FutureWarning"
+    ),
+    pytest.mark.filterwarnings(
+        "ignore:last is deprecated and will be removed:FutureWarning"
+    ),
+]
 
 NPartitions.put(4)
 
@@ -1237,8 +1249,11 @@ def test_bfill(data):
 def test_bool(data):
     modin_series, _ = create_test_series(data)
 
-    with pytest.raises(ValueError):
-        modin_series.bool()
+    with pytest.warns(
+        FutureWarning, match="bool is now deprecated and will be removed"
+    ):
+        with pytest.raises(ValueError):
+            modin_series.bool()
     with pytest.raises(ValueError):
         modin_series.__bool__()
 
@@ -2034,7 +2049,9 @@ def test_first():
     i = pd.date_range("2010-04-09", periods=400, freq="2D")
     modin_series = pd.Series(list(range(400)), index=i)
     pandas_series = pandas.Series(list(range(400)), index=i)
-    df_equals(modin_series.first("3D"), pandas_series.first("3D"))
+    with pytest.warns(FutureWarning, match="first is deprecated and will be removed"):
+        modin_result = modin_series.first("3D")
+    df_equals(modin_result, pandas_series.first("3D"))
     df_equals(modin_series.first("20D"), pandas_series.first("20D"))
 
 
@@ -2277,7 +2294,9 @@ def test_last():
     pandas_index = pandas.date_range("2010-04-09", periods=400, freq="2D")
     modin_series = pd.Series(list(range(400)), index=modin_index)
     pandas_series = pandas.Series(list(range(400)), index=pandas_index)
-    df_equals(modin_series.last("3D"), pandas_series.last("3D"))
+    with pytest.warns(FutureWarning, match="last is deprecated and will be removed"):
+        modin_result = modin_series.last("3D")
+    df_equals(modin_result, pandas_series.last("3D"))
     df_equals(modin_series.last("20D"), pandas_series.last("20D"))