warning for sparse

pandas/compat/pickle_compat.py

@@ -5,10 +5,14 @@
 import copy
 import pickle as pkl
 import sys
-from typing import Any
+from typing import TYPE_CHECKING
+import warnings
 
 from pandas import Index
 
+if TYPE_CHECKING:
+    from pandas._typing import FrameOrSeries
+
 
 def load_reduce(self):
     stack = self.stack
@@ -55,19 +59,38 @@ def load_reduce(self):
         raise
 
 
+_sparse_msg = """\
+
+Loading a saved '{cls}' as a {new} with sparse values.
+'{cls}' is now removed. You should re-save this dataset in its new format.
+"""
+
+
 class _LoadSparseSeries:
     # To load a SparseSeries as a Series[Sparse]
-    def __new__(cls) -> Any:
+    def __new__(cls) -> FrameOrSeries:
         from pandas import Series
 
+        warnings.warn(
+            _sparse_msg.format(cls="SparseSeries", new="Series"),
+            FutureWarning,
+            stacklevel=6,
+        )
+
         return Series()
 
 
 class _LoadSparseFrame:
     # To load a SparseDataFrame as a DataFrame[Sparse]
-    def __new__(cls) -> Any:
+    def __new__(cls) -> FrameOrSeries:
         from pandas import DataFrame
 
+        warnings.warn(
+            _sparse_msg.format(cls="SparseDataFrame", new="DataFrame"),
+            FutureWarning,
+            stacklevel=6,
+        )
+
         return DataFrame()
 
 

pandas/tests/io/test_pickle.py

@@ -228,6 +228,32 @@ def test_pickle_path_localpath():
     tm.assert_frame_equal(df, result)
 
 
+def test_legacy_sparse_warning(datapath):
+    """
+
+    Generated with
+
+    >>> df = pd.DataFrame({"A": [1, 2, 3, 4], "B": [0, 0, 1, 1]}).to_sparse()
+    >>> df.to_pickle("pandas/tests/io/data/sparseframe-0.20.3.pickle.gz",
+    ...              compression="gzip")
+
+    >>> s = df['B']
+    >>> s.to_pickle("pandas/tests/io/data/sparseseries-0.20.3.pickle.gz",
+    ...             compression="gzip")
+    """
+    with tm.assert_produces_warning(FutureWarning):
+        simplefilter("ignore", DeprecationWarning)  # from boto
+        pd.read_pickle(
+            datapath("io", "data", "sparseseries-0.20.3.pickle.gz"), compression="gzip"
+        )
+
+    with tm.assert_produces_warning(FutureWarning):
+        simplefilter("ignore", DeprecationWarning)  # from boto
+        pd.read_pickle(
+            datapath("io", "data", "sparseframe-0.20.3.pickle.gz"), compression="gzip"
+        )
+
+
 # ---------------------
 # test pickle compression
 # ---------------------