ENH: update feather IO for pyarrow 0.17 / Feather V2

doc/source/conf.py

@@ -416,6 +416,7 @@
         "python": ("https://docs.python.org/3/", None),
         "scipy": ("https://docs.scipy.org/doc/scipy/reference/", None),
         "statsmodels": ("https://www.statsmodels.org/devel/", None),
+        "pyarrow": ("https://arrow.apache.org/docs/", None),
     }
 
 # extlinks alias

doc/source/user_guide/io.rst

@@ -4583,17 +4583,15 @@ frames efficient, and to make sharing data across data analysis languages easy.
 Feather is designed to faithfully serialize and de-serialize DataFrames, supporting all of the pandas
 dtypes, including extension dtypes such as categorical and datetime with tz.
 
-Several caveats.
+Several caveats:
 
-* This is a newer library, and the format, though stable, is not guaranteed to be backward compatible
-  to the earlier versions.
 * The format will NOT write an ``Index``, or ``MultiIndex`` for the
   ``DataFrame`` and will raise an error if a non-default one is provided. You
   can ``.reset_index()`` to store the index or ``.reset_index(drop=True)`` to
   ignore it.
 * Duplicate column names and non-string columns names are not supported
-* Non supported types include ``Period`` and actual Python object types. These will raise a helpful error message
-  on an attempt at serialization.
+* Actual Python objects in object dtype columns are not supported. These will
+  raise a helpful error message on an attempt at serialization.
 
 See the `Full Documentation <https://github.com/wesm/feather>`__.
 

doc/source/whatsnew/v1.1.0.rst

@@ -88,7 +88,9 @@ Other enhancements
 - :class:`Series.str` now has a `fullmatch` method that matches a regular expression against the entire string in each row of the series, similar to `re.fullmatch` (:issue:`32806`).
 - :meth:`DataFrame.sample` will now also allow array-like and BitGenerator objects to be passed to ``random_state`` as seeds (:issue:`32503`)
 - :meth:`MultiIndex.union` will now raise `RuntimeWarning` if the object inside are unsortable, pass `sort=False` to suppress this warning (:issue:`33015`)
--
+- The :meth:`DataFrame.to_feather` method now supports additional keyword
+  arguments (e.g. to set the compression) that are added in pyarrow 0.17
+  (:issue:`33422`).
 
 .. ---------------------------------------------------------------------------
 

pandas/core/frame.py

@@ -2058,18 +2058,24 @@ def to_stata(
         writer.write_file()
 
     @deprecate_kwarg(old_arg_name="fname", new_arg_name="path")
-    def to_feather(self, path) -> None:
+    def to_feather(self, path, **kwargs) -> None:
         """
-        Write out the binary feather-format for DataFrames.
+        Write a DataFrame to the binary Feather format.
 
         Parameters
         ----------
         path : str
             String file path.
+        **kwargs :
+            Additional keywords passed to :func:`pyarrow.feather.write_feather`.
+            Starting with pyarrow 0.17, this includes the `compression`,
+            `compression_level`, `chunksize` and `version` keywords.
+
+            .. versionadded:: 1.1.0
         """
         from pandas.io.feather_format import to_feather
 
-        to_feather(self, path)
+        to_feather(self, path, **kwargs)
 
     @Appender(
         """

pandas/io/feather_format.py

@@ -7,15 +7,18 @@
 from pandas.io.common import stringify_path
 
 
-def to_feather(df: DataFrame, path):
+def to_feather(df: DataFrame, path, **kwargs):
     """
-    Write a DataFrame to the feather-format
+    Write a DataFrame to the binary Feather format.
 
     Parameters
     ----------
     df : DataFrame
     path : string file path, or file-like object
+    **kwargs :
+        Additional keywords passed to `pyarrow.feather.write_feather`.
 
+        .. versionadded:: 1.1.0
     """
     import_optional_dependency("pyarrow")
     from pyarrow import feather
@@ -58,7 +61,7 @@ def to_feather(df: DataFrame, path):
     if df.columns.inferred_type not in valid_types:
         raise ValueError("feather must have string column names")
 
-    feather.write_feather(df, path)
+    feather.write_feather(df, path, **kwargs)
 
 
 def read_feather(path, columns=None, use_threads: bool = True):

pandas/tests/io/test_feather.py

@@ -4,6 +4,8 @@
 import numpy as np
 import pytest
 
+import pandas.util._test_decorators as td
+
 import pandas as pd
 import pandas._testing as tm
 
@@ -27,15 +29,15 @@ def check_error_on_write(self, df, exc):
             with tm.ensure_clean() as path:
                 to_feather(df, path)
 
-    def check_round_trip(self, df, expected=None, **kwargs):
+    def check_round_trip(self, df, expected=None, write_kwargs={}, **read_kwargs):
 
         if expected is None:
             expected = df
 
         with tm.ensure_clean() as path:
-            to_feather(df, path)
+            to_feather(df, path, **write_kwargs)
 
-            result = read_feather(path, **kwargs)
+            result = read_feather(path, **read_kwargs)
             tm.assert_frame_equal(result, expected)
 
     def test_error(self):
@@ -71,6 +73,10 @@ def test_basic(self):
                 "dtns": pd.date_range("20130101", periods=3, freq="ns"),
             }
         )
+        if pyarrow_version >= LooseVersion("0.16.1.dev"):
+            df["periods"] = pd.period_range("2013", freq="M", periods=3)
+            df["timedeltas"] = pd.timedelta_range("1 day", periods=3)
+            df["intervals"] = pd.interval_range(0, 3, 3)
 
         assert df.dttz.dtype.tz.zone == "US/Eastern"
         self.check_round_trip(df)
@@ -102,8 +108,8 @@ def test_read_columns(self):
 
     def test_unsupported_other(self):
 
-        # period
-        df = pd.DataFrame({"a": pd.period_range("2013", freq="M", periods=3)})
+        # mixed python objects
+        df = pd.DataFrame({"a": ["a", 1, 2.0]})
         # Some versions raise ValueError, others raise ArrowInvalid.
         self.check_error_on_write(df, Exception)
 
@@ -148,3 +154,8 @@ def test_path_localpath(self):
         df = tm.makeDataFrame().reset_index()
         result = tm.round_trip_localpath(df.to_feather, pd.read_feather)
         tm.assert_frame_equal(df, result)
+
+    @td.skip_if_no("pyarrow", min_version="0.16.1.dev")
+    def test_passthrough_keywords(self):
+        df = tm.makeDataFrame().reset_index()
+        self.check_round_trip(df, write_kwargs=dict(version=1))