DEPS: bump pyarrow version to 0.17.0 pandas-dev#38870 (pandas-dev#41476)

.github/workflows/database.yml

@@ -70,7 +70,7 @@ jobs:
     - uses: conda-incubator/setup-miniconda@v2
       with:
         activate-environment: pandas-dev
-        channel-priority: strict
+        channel-priority: flexible
         environment-file: ${{ matrix.ENV_FILE }}
         use-only-tar-bz2: true
 

ci/deps/actions-37-db-min.yaml

@@ -31,7 +31,8 @@ dependencies:
   - openpyxl
   - pandas-gbq
   - google-cloud-bigquery>=1.27.2 # GH 36436
-  - pyarrow=0.17 # GH 38803
+  - protobuf>=3.12.4
+  - pyarrow=0.17.1 # GH 38803
   - pytables>=3.5.1
   - scipy
   - xarray=0.12.3

ci/deps/actions-37-db.yaml

@@ -31,7 +31,7 @@ dependencies:
   - pandas-gbq
   - google-cloud-bigquery>=1.27.2 # GH 36436
   - psycopg2
-  - pyarrow>=0.15.0
+  - pyarrow>=0.17.0
   - pymysql
   - pytables
   - python-snappy

ci/deps/actions-37-minimum_versions.yaml

@@ -23,7 +23,7 @@ dependencies:
   - pytables=3.5.1
   - python-dateutil=2.7.3
   - pytz=2017.3
-  - pyarrow=0.15
+  - pyarrow=0.17.0
   - scipy=1.2
   - xlrd=1.2.0
   - xlsxwriter=1.0.2

ci/deps/actions-37.yaml

@@ -18,7 +18,7 @@ dependencies:
   - numpy=1.19
   - python-dateutil
   - nomkl
-  - pyarrow=0.15.1
+  - pyarrow
   - pytz
   - s3fs>=0.4.0
   - moto>=1.3.14

ci/deps/azure-macos-37.yaml

@@ -1,6 +1,7 @@
 name: pandas-dev
 channels:
   - defaults
+  - conda-forge
 dependencies:
   - python=3.7.*
 
@@ -21,7 +22,7 @@ dependencies:
   - numexpr
   - numpy=1.17.3
   - openpyxl
-  - pyarrow=0.15.1
+  - pyarrow=0.17.0
   - pytables
   - python-dateutil==2.7.3
   - pytz

ci/deps/azure-windows-37.yaml

@@ -26,7 +26,7 @@ dependencies:
   - numexpr
   - numpy=1.17.*
   - openpyxl
-  - pyarrow=0.15
+  - pyarrow=0.17.0
   - pytables
   - python-dateutil
   - pytz

ci/deps/azure-windows-38.yaml

@@ -25,7 +25,7 @@ dependencies:
   - numpy=1.18.*
   - openpyxl
   - jinja2
-  - pyarrow>=0.15.0
+  - pyarrow>=0.17.0
   - pytables
   - python-dateutil
   - pytz

doc/source/getting_started/install.rst

@@ -358,7 +358,7 @@ PyTables                  3.5.1              HDF5-based reading / writing
 blosc                     1.17.0             Compression for HDF5
 zlib                                         Compression for HDF5
 fastparquet               0.4.0              Parquet reading / writing
-pyarrow                   0.15.0             Parquet, ORC, and feather reading / writing
+pyarrow                   0.17.0             Parquet, ORC, and feather reading / writing
 pyreadstat                                   SPSS files (.sav) reading
 ========================= ================== =============================================================
 

doc/source/whatsnew/v1.3.0.rst

@@ -579,7 +579,7 @@ Optional libraries below the lowest tested version may still work, but are not c
 +-----------------+-----------------+---------+
 | openpyxl        | 3.0.0           |    X    |
 +-----------------+-----------------+---------+
-| pyarrow         | 0.15.0          |         |
+| pyarrow         | 0.17.0          |    X    |
 +-----------------+-----------------+---------+
 | pymysql         | 0.8.1           |    X    |
 +-----------------+-----------------+---------+

environment.yml

@@ -100,7 +100,7 @@ dependencies:
   - odfpy
 
   - fastparquet>=0.3.2  # pandas.read_parquet, DataFrame.to_parquet
-  - pyarrow>=0.15.0  # pandas.read_parquet, DataFrame.to_parquet, pandas.read_feather, DataFrame.to_feather
+  - pyarrow>=0.17.0  # pandas.read_parquet, DataFrame.to_parquet, pandas.read_feather, DataFrame.to_feather
   - python-snappy  # required by pyarrow
 
   - pyqt>=5.9.2  # pandas.read_clipboard

pandas/compat/_optional.py

@@ -21,7 +21,7 @@
     "odfpy": "1.3.0",
     "openpyxl": "3.0.0",
     "pandas_gbq": "0.12.0",
-    "pyarrow": "0.15.0",
+    "pyarrow": "0.17.0",
     "pytest": "5.0.1",
     "pyxlsb": "1.0.6",
     "s3fs": "0.4.0",

pandas/tests/arrays/interval/test_interval.py

@@ -165,7 +165,7 @@ def test_repr():
 # Arrow interaction
 
 
-pyarrow_skip = td.skip_if_no("pyarrow", min_version="0.16.0")
+pyarrow_skip = td.skip_if_no("pyarrow")
 
 
 @pyarrow_skip

pandas/tests/arrays/masked/test_arrow_compat.py

@@ -6,7 +6,7 @@
 import pandas as pd
 import pandas._testing as tm
 
-pa = pytest.importorskip("pyarrow", minversion="0.15.0")
+pa = pytest.importorskip("pyarrow", minversion="0.17.0")
 
 from pandas.core.arrays._arrow_utils import pyarrow_array_to_numpy_and_mask
 
@@ -21,8 +21,6 @@ def data(request):
 
 
 def test_arrow_array(data):
-    # protocol added in 0.15.0
-
     arr = pa.array(data)
     expected = pa.array(
         data.to_numpy(object, na_value=None),
@@ -31,10 +29,8 @@ def test_arrow_array(data):
     assert arr.equals(expected)
 
 
-@td.skip_if_no("pyarrow", min_version="0.16.0")
+@td.skip_if_no("pyarrow")
 def test_arrow_roundtrip(data):
-    # roundtrip possible from arrow 0.16.0
-
     df = pd.DataFrame({"a": data})
     table = pa.table(df)
     assert table.field("a").type == str(data.dtype.numpy_dtype)
@@ -43,7 +39,7 @@ def test_arrow_roundtrip(data):
     tm.assert_frame_equal(result, df)
 
 
-@td.skip_if_no("pyarrow", min_version="0.16.0")
+@td.skip_if_no("pyarrow")
 def test_arrow_load_from_zero_chunks(data):
     # GH-41040
 
@@ -58,7 +54,7 @@ def test_arrow_load_from_zero_chunks(data):
     tm.assert_frame_equal(result, df)
 
 
-@td.skip_if_no("pyarrow", min_version="0.16.0")
+@td.skip_if_no("pyarrow")
 def test_arrow_from_arrow_uint():
     # https://github.com/pandas-dev/pandas/issues/31896
     # possible mismatch in types
@@ -70,7 +66,7 @@ def test_arrow_from_arrow_uint():
     tm.assert_extension_array_equal(result, expected)
 
 
-@td.skip_if_no("pyarrow", min_version="0.16.0")
+@td.skip_if_no("pyarrow")
 def test_arrow_sliced(data):
     # https://github.com/pandas-dev/pandas/issues/38525
 
@@ -165,7 +161,7 @@ def test_pyarrow_array_to_numpy_and_mask(np_dtype_to_arrays):
     tm.assert_numpy_array_equal(mask, mask_expected_empty)
 
 
-@td.skip_if_no("pyarrow", min_version="0.16.0")
+@td.skip_if_no("pyarrow")
 def test_from_arrow_type_error(request, data):
     # ensure that __from_arrow__ returns a TypeError when getting a wrong
     # array type

pandas/tests/arrays/period/test_arrow_compat.py

@@ -11,7 +11,7 @@
     period_array,
 )
 
-pyarrow_skip = pyarrow_skip = td.skip_if_no("pyarrow", min_version="0.16.0")
+pyarrow_skip = td.skip_if_no("pyarrow", min_version="0.17.0")
 
 
 @pyarrow_skip

pandas/tests/arrays/string_/test_string.py

@@ -437,7 +437,7 @@ def test_fillna_args(dtype, request):
         arr.fillna(value=1)
 
 
-@td.skip_if_no("pyarrow", min_version="0.15.0")
+@td.skip_if_no("pyarrow")
 def test_arrow_array(dtype):
     # protocol added in 0.15.0
     import pyarrow as pa
@@ -451,7 +451,7 @@ def test_arrow_array(dtype):
     assert arr.equals(expected)
 
 
-@td.skip_if_no("pyarrow", min_version="0.16.0")
+@td.skip_if_no("pyarrow")
 def test_arrow_roundtrip(dtype, dtype_object):
     # roundtrip possible from arrow 1.0.0
     import pyarrow as pa
@@ -467,7 +467,7 @@ def test_arrow_roundtrip(dtype, dtype_object):
     assert result.loc[2, "a"] is pd.NA
 
 
-@td.skip_if_no("pyarrow", min_version="0.16.0")
+@td.skip_if_no("pyarrow")
 def test_arrow_load_from_zero_chunks(dtype, dtype_object):
     # GH-41040
     import pyarrow as pa

pandas/tests/io/test_feather.py

@@ -6,14 +6,12 @@
 
 import pandas as pd
 import pandas._testing as tm
-from pandas.util.version import Version
 
 from pandas.io.feather_format import read_feather, to_feather  # isort:skip
 
 pyarrow = pytest.importorskip("pyarrow")
 
 
-pyarrow_version = Version(pyarrow.__version__)
 filter_sparse = pytest.mark.filterwarnings("ignore:The Sparse")
 
 
@@ -89,12 +87,11 @@ def test_basic(self):
                 ),
             }
         )
-        if pyarrow_version >= Version("0.17.0"):
-            df["periods"] = pd.period_range("2013", freq="M", periods=3)
-            df["timedeltas"] = pd.timedelta_range("1 day", periods=3)
-            # TODO temporary disable due to regression in pyarrow 0.17.1
-            # https://github.com/pandas-dev/pandas/issues/34255
-            # df["intervals"] = pd.interval_range(0, 3, 3)
+        df["periods"] = pd.period_range("2013", freq="M", periods=3)
+        df["timedeltas"] = pd.timedelta_range("1 day", periods=3)
+        # TODO temporary disable due to regression in pyarrow 0.17.1
+        # https://github.com/pandas-dev/pandas/issues/34255
+        # df["intervals"] = pd.interval_range(0, 3, 3)
 
         assert df.dttz.dtype.tz.zone == "US/Eastern"
         self.check_round_trip(df)

pandas/tests/io/test_parquet.py

@@ -17,6 +17,10 @@
     PY38,
     is_platform_windows,
 )
+from pandas.compat.pyarrow import (
+    pa_version_under1p0,
+    pa_version_under2p0,
+)
 import pandas.util._test_decorators as td
 
 import pandas as pd
@@ -653,8 +657,6 @@ def test_categorical(self, pa):
     )
     def test_s3_roundtrip_explicit_fs(self, df_compat, s3_resource, pa, s3so):
         s3fs = pytest.importorskip("s3fs")
-        if Version(pyarrow.__version__) <= Version("0.17.0"):
-            pytest.skip()
         s3 = s3fs.S3FileSystem(**s3so)
         kw = {"filesystem": s3}
         check_round_trip(
@@ -666,8 +668,6 @@ def test_s3_roundtrip_explicit_fs(self, df_compat, s3_resource, pa, s3so):
         )
 
     def test_s3_roundtrip(self, df_compat, s3_resource, pa, s3so):
-        if Version(pyarrow.__version__) <= Version("0.17.0"):
-            pytest.skip()
         # GH #19134
         s3so = {"storage_options": s3so}
         check_round_trip(
@@ -698,14 +698,12 @@ def test_s3_roundtrip_for_dir(
         # These are added to back of dataframe on read. In new API category dtype is
         # only used if partition field is string, but this changed again to use
         # category dtype for all types (not only strings) in pyarrow 2.0.0
-        pa10 = (Version(pyarrow.__version__) >= Version("1.0.0")) and (
-            Version(pyarrow.__version__) < Version("2.0.0")
-        )
         if partition_col:
-            if pa10:
-                partition_col_type = "int32"
-            else:
-                partition_col_type = "category"
+            partition_col_type = (
+                "int32"
+                if (not pa_version_under1p0) and pa_version_under2p0
+                else "category"
+            )
 
             expected_df[partition_col] = expected_df[partition_col].astype(
                 partition_col_type
@@ -795,7 +793,7 @@ def test_write_with_schema(self, pa):
         out_df = df.astype(bool)
         check_round_trip(df, pa, write_kwargs={"schema": schema}, expected=out_df)
 
-    @td.skip_if_no("pyarrow", min_version="0.15.0")
+    @td.skip_if_no("pyarrow")
     def test_additional_extension_arrays(self, pa):
         # test additional ExtensionArrays that are supported through the
         # __arrow_array__ protocol
@@ -806,22 +804,10 @@ def test_additional_extension_arrays(self, pa):
                 "c": pd.Series(["a", None, "c"], dtype="string"),
             }
         )
-        if Version(pyarrow.__version__) >= Version("0.16.0"):
-            expected = df
-        else:
-            # de-serialized as plain int / object
-            expected = df.assign(
-                a=df.a.astype("int64"), b=df.b.astype("int64"), c=df.c.astype("object")
-            )
-        check_round_trip(df, pa, expected=expected)
+        check_round_trip(df, pa)
 
         df = pd.DataFrame({"a": pd.Series([1, 2, 3, None], dtype="Int64")})
-        if Version(pyarrow.__version__) >= Version("0.16.0"):
-            expected = df
-        else:
-            # if missing values in integer, currently de-serialized as float
-            expected = df.assign(a=df.a.astype("float64"))
-        check_round_trip(df, pa, expected=expected)
+        check_round_trip(df, pa)
 
     @td.skip_if_no("pyarrow", min_version="1.0.0")
     def test_pyarrow_backed_string_array(self, pa):
@@ -831,7 +817,7 @@ def test_pyarrow_backed_string_array(self, pa):
         df = pd.DataFrame({"a": pd.Series(["a", None, "c"], dtype="arrow_string")})
         check_round_trip(df, pa, expected=df)
 
-    @td.skip_if_no("pyarrow", min_version="0.16.0")
+    @td.skip_if_no("pyarrow")
     def test_additional_extension_types(self, pa):
         # test additional ExtensionArrays that are supported through the
         # __arrow_array__ protocol + by defining a custom ExtensionType
@@ -844,7 +830,7 @@ def test_additional_extension_types(self, pa):
         )
         check_round_trip(df, pa)
 
-    @td.skip_if_no("pyarrow", min_version="0.16.0")
+    @td.skip_if_no("pyarrow")
     def test_use_nullable_dtypes(self, pa):
         import pyarrow.parquet as pq
 
@@ -880,7 +866,7 @@ def test_timestamp_nanoseconds(self, pa):
         check_round_trip(df, pa, write_kwargs={"version": "2.0"})
 
     def test_timezone_aware_index(self, pa, timezone_aware_date_list):
-        if Version(pyarrow.__version__) >= Version("2.0.0"):
+        if not pa_version_under2p0:
             # temporary skip this test until it is properly resolved
             # https://github.com/pandas-dev/pandas/issues/37286
             pytest.skip()

requirements-dev.txt

@@ -65,7 +65,7 @@ xlsxwriter
 xlwt
 odfpy
 fastparquet>=0.3.2
-pyarrow>=0.15.0
+pyarrow>=0.17.0
 python-snappy
 pyqt5>=5.9.2
 tables>=3.5.1