ARROW-6683: [Python] Test for fastparquet <-> pyarrow cross-compatibility

python/pyarrow/tests/test_parquet.py

@@ -3345,3 +3345,42 @@ def test_filter_before_validate_schema(tempdir):
     # read single file using filter
     table = pq.read_table(tempdir, filters=[[('A', '==', 0)]])
     assert table.column('B').equals(pa.chunked_array([[1, 2, 3]]))
+
+
+@pytest.mark.pandas
+@pytest.mark.fastparquet
+@pytest.mark.filterwarnings("ignore:RangeIndex:DeprecationWarning")
+def test_fastparquet_cross_compatibility(tempdir):
+    fp = pytest.importorskip('fastparquet')
+
+    df = pd.DataFrame(
+        {
+            "a": list("abc"),
+            "b": list(range(1, 4)),
+            "c": np.arange(4.0, 7.0, dtype="float64"),
+            "d": [True, False, True],
+            "e": pd.date_range("20130101", periods=3),
+            "f": pd.Categorical(["a", "b", "a"]),
+            # fastparquet writes list as BYTE_ARRAY JSON, so no roundtrip
+            # "g": [[1, 2], None, [1, 2, 3]],
+        }
+    )
+    table = pa.table(df)
+
+    # Arrow -> fastparquet
+    file_arrow = str(tempdir / "cross_compat_arrow.parquet")
+    pq.write_table(table, file_arrow, compression=None)
+
+    fp_file = fp.ParquetFile(file_arrow)
+    df_fp = fp_file.to_pandas()
+    tm.assert_frame_equal(df, df_fp)
+
+    # Fastparquet -> arrow
+    file_fastparquet = str(tempdir / "cross_compat_fastparquet.parquet")
+    fp.write(file_fastparquet, df)
+
+    table_fp = pq.read_pandas(file_fastparquet)
+    # for fastparquet written file, categoricals comes back as strings
+    # (no arrow schema in parquet metadata)
+    df['f'] = df['f'].astype(object)
+    tm.assert_frame_equal(table_fp.to_pandas(), df)