black==19.10b0 breaks CI #29341
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yeah we likely need to pin the current version of black and update the codebase, care to do a PR? |
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happy to do so or did you already take this on ? |
|
i pinned this but would love to have a PR to patch the codebase and update to the new version i think it’s backwards incompatible so would have to pin but that’s ok |
|
alright we will work on this then ! |
|
I've taken a look at this here: #29508 |
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Code Sampl
Problem description
Currently if using
virtualenvinstead of conda, inPython 3.7.4and pippip 19.3.1the requirements automatically installblack==19.10b0which differs from the conda workflow which install theblack==19.3b0version.Expected Output
Git diff
diff --git a/pandas/core/algorithms.py b/pandas/core/algorithms.py index c70e62377..cc6c23929 100644 --- a/pandas/core/algorithms.py +++ b/pandas/core/algorithms.py @@ -1155,7 +1155,7 @@ class SelectNSeries(SelectN): n = min(n, narr) kth_val = algos.kth_smallest(arr.copy(), n - 1) - ns, = np.nonzero(arr <= kth_val) + (ns,) = np.nonzero(arr <= kth_val) inds = ns[arr[ns].argsort(kind="mergesort")] if self.keep != "all": diff --git a/pandas/core/frame.py b/pandas/core/frame.py index 40efc4c65..7d8cc0b73 100644 --- a/pandas/core/frame.py +++ b/pandas/core/frame.py @@ -4829,7 +4829,7 @@ class DataFrame(NDFrame): duplicated = self.duplicated(subset, keep=keep) if inplace: - inds, = (-duplicated)._ndarray_values.nonzero() + (inds,) = (-duplicated)._ndarray_values.nonzero() new_data = self._data.take(inds) self._update_inplace(new_data) else: diff --git a/pandas/core/generic.py b/pandas/core/generic.py index f88c26c7b..fa43206b8 100644 --- a/pandas/core/generic.py +++ b/pandas/core/generic.py @@ -3613,7 +3613,7 @@ class NDFrame(PandasObject, SelectionMixin): if isinstance(loc, np.ndarray): if loc.dtype == np.bool_: - inds, = loc.nonzero() + (inds,) = loc.nonzero() return self.take(inds, axis=axis) else: return self.take(loc, axis=axis) diff --git a/pandas/core/groupby/grouper.py b/pandas/core/groupby/grouper.py index d7eaaca5a..d6beefbf3 100644 --- a/pandas/core/groupby/grouper.py +++ b/pandas/core/groupby/grouper.py @@ -284,7 +284,11 @@ class Grouping: if self.name is None: self.name = index.names[level] - self.grouper, self._labels, self._group_index = index._get_grouper_for_level( # noqa: E501 + ( + self.grouper, + self._labels, + self._group_index, + ) = index._get_grouper_for_level( # noqa: E501 self.grouper, level ) diff --git a/pandas/core/indexes/base.py b/pandas/core/indexes/base.py index 187c7e2f3..954607a0d 100644 --- a/pandas/core/indexes/base.py +++ b/pandas/core/indexes/base.py @@ -1873,7 +1873,7 @@ class Index(IndexOpsMixin, PandasObject): @cache_readonly def _nan_idxs(self): if self._can_hold_na: - w, = self._isnan.nonzero() + (w,) = self._isnan.nonzero() return w else: return np.array([], dtype=np.int64) diff --git a/pandas/core/indexing.py b/pandas/core/indexing.py index 44c786f00..1315e9d5b 100755 --- a/pandas/core/indexing.py +++ b/pandas/core/indexing.py @@ -320,7 +320,7 @@ class _NDFrameIndexer(_NDFrameIndexerBase): # if there is only one block/type, still have to take split path # unless the block is one-dimensional or it can hold the value if not take_split_path and self.obj._data.blocks: - blk, = self.obj._data.blocks + (blk,) = self.obj._data.blocks if 1 < blk.ndim: # in case of dict, keys are indices val = list(value.values()) if isinstance(value, dict) else value take_split_path = not blk._can_hold_element(val) @@ -1120,7 +1120,7 @@ class _NDFrameIndexer(_NDFrameIndexerBase): if com.is_bool_indexer(key): # A boolean indexer key = check_bool_indexer(labels, key) - inds, = key.nonzero() + (inds,) = key.nonzero() return self.obj.take(inds, axis=axis) else: # A collection of keys @@ -1264,7 +1264,7 @@ class _NDFrameIndexer(_NDFrameIndexerBase): if com.is_bool_indexer(obj): obj = check_bool_indexer(labels, obj) - inds, = obj.nonzero() + (inds,) = obj.nonzero() return inds else: # When setting, missing keys are not allowed, even with .loc: diff --git a/pandas/core/internals/managers.py b/pandas/core/internals/managers.py index c47aaf7c7..db782b455 100644 --- a/pandas/core/internals/managers.py +++ b/pandas/core/internals/managers.py @@ -1868,7 +1868,7 @@ def _stack_arrays(tuples, dtype): def _interleaved_dtype( - blocks: List[Block] + blocks: List[Block], ) -> Optional[Union[np.dtype, ExtensionDtype]]: """Find the common dtype for `blocks`. diff --git a/pandas/io/common.py b/pandas/io/common.py index 0bef14e49..e08fd37e6 100644 --- a/pandas/io/common.py +++ b/pandas/io/common.py @@ -109,7 +109,7 @@ def _is_url(url) -> bool: def _expand_user( - filepath_or_buffer: FilePathOrBuffer[AnyStr] + filepath_or_buffer: FilePathOrBuffer[AnyStr], ) -> FilePathOrBuffer[AnyStr]: """Return the argument with an initial component of ~ or ~user replaced by that user's home directory. @@ -139,7 +139,7 @@ def _validate_header_arg(header) -> None: def _stringify_path( - filepath_or_buffer: FilePathOrBuffer[AnyStr] + filepath_or_buffer: FilePathOrBuffer[AnyStr], ) -> FilePathOrBuffer[AnyStr]: """Attempt to convert a path-like object to a string. diff --git a/pandas/io/parsers.py b/pandas/io/parsers.py index 058d65b94..4ff988acf 100755 --- a/pandas/io/parsers.py +++ b/pandas/io/parsers.py @@ -1918,7 +1918,12 @@ class CParserWrapper(ParserBase): else: if len(self._reader.header) > 1: # we have a multi index in the columns - self.names, self.index_names, self.col_names, passed_names = self._extract_multi_indexer_columns( # noqa: E501 + ( + self.names, + self.index_names, + self.col_names, + passed_names, + ) = self._extract_multi_indexer_columns( # noqa: E501 self._reader.header, self.index_names, self.col_names, passed_names ) else: @@ -2307,7 +2312,12 @@ class PythonParser(ParserBase): # The original set is stored in self.original_columns. if len(self.columns) > 1: # we are processing a multi index column - self.columns, self.index_names, self.col_names, _ = self._extract_multi_indexer_columns( # noqa: E501 + ( + self.columns, + self.index_names, + self.col_names, + _, + ) = self._extract_multi_indexer_columns( # noqa: E501 self.columns, self.index_names, self.col_names ) # Update list of original names to include all indices. diff --git a/pandas/io/stata.py b/pandas/io/stata.py index 07475f224..8e5fa48d4 100644 --- a/pandas/io/stata.py +++ b/pandas/io/stata.py @@ -614,7 +614,7 @@ def _cast_to_stata_types(data): data[col] = data[col].astype(np.int32) else: data[col] = data[col].astype(np.float64) - if data[col].max() >= 2 ** 53 or data[col].min() <= -2 ** 53: + if data[col].max() >= 2 ** 53 or data[col].min() <= -(2 ** 53): ws = precision_loss_doc % ("int64", "float64") elif dtype in (np.float32, np.float64): value = data[col].max() diff --git a/pandas/tests/arrays/sparse/test_array.py b/pandas/tests/arrays/sparse/test_array.py index f9bb4981d..755cbfb71 100644 --- a/pandas/tests/arrays/sparse/test_array.py +++ b/pandas/tests/arrays/sparse/test_array.py @@ -658,12 +658,16 @@ class TestSparseArray: dense = np.array([np.nan, 0, 3, 4, 0, 5, np.nan, np.nan, 0]) sparse = SparseArray(dense) - res = sparse[4:,] # noqa: E231 + res = sparse[ + 4:, + ] # noqa: E231 exp = SparseArray(dense[4:,]) # noqa: E231 tm.assert_sp_array_equal(res, exp) sparse = SparseArray(dense, fill_value=0) - res = sparse[4:,] # noqa: E231 + res = sparse[ + 4:, + ] # noqa: E231 exp = SparseArray(dense[4:,], fill_value=0) # noqa: E231 tm.assert_sp_array_equal(res, exp) @@ -823,11 +827,11 @@ class TestSparseArray: # Tests regression #21172. sa = pd.SparseArray([float("nan"), float("nan"), 1, 0, 0, 2, 0, 0, 0, 3, 0, 0]) expected = np.array([2, 5, 9], dtype=np.int32) - result, = sa.nonzero() + (result,) = sa.nonzero() tm.assert_numpy_array_equal(expected, result) sa = pd.SparseArray([0, 0, 1, 0, 0, 2, 0, 0, 0, 3, 0, 0]) - result, = sa.nonzero() + (result,) = sa.nonzero() tm.assert_numpy_array_equal(expected, result) diff --git a/pandas/tests/dtypes/test_inference.py b/pandas/tests/dtypes/test_inference.py index 62fb118f7..7d5b1891c 100644 --- a/pandas/tests/dtypes/test_inference.py +++ b/pandas/tests/dtypes/test_inference.py @@ -505,7 +505,7 @@ class TestInference: result = lib.maybe_convert_numeric(case, set(), coerce_numeric=coerce) tm.assert_almost_equal(result, expected) - @pytest.mark.parametrize("value", [-2 ** 63 - 1, 2 ** 64]) + @pytest.mark.parametrize("value", [-(2 ** 63) - 1, 2 ** 64]) def test_convert_int_overflow(self, value): # see gh-18584 arr = np.array([value], dtype=object) diff --git a/pandas/tests/frame/test_constructors.py b/pandas/tests/frame/test_constructors.py index aa00cf234..f193f97ae 100644 --- a/pandas/tests/frame/test_constructors.py +++ b/pandas/tests/frame/test_constructors.py @@ -245,9 +245,9 @@ class TestDataFrameConstructors: np.array([2 ** 64], dtype=object), np.array([2 ** 65]), [2 ** 64 + 1], - np.array([-2 ** 63 - 4], dtype=object), - np.array([-2 ** 64 - 1]), - [-2 ** 65 - 2], + np.array([-(2 ** 63) - 4], dtype=object), + np.array([-(2 ** 64) - 1]), + [-(2 ** 65) - 2], ], ) def test_constructor_int_overflow(self, values): diff --git a/pandas/tests/indexes/period/test_construction.py b/pandas/tests/indexes/period/test_construction.py index 8c75fbbae..1973cb7f4 100644 --- a/pandas/tests/indexes/period/test_construction.py +++ b/pandas/tests/indexes/period/test_construction.py @@ -434,7 +434,7 @@ class TestPeriodIndex: with tm.assert_produces_warning(FutureWarning) as m: PeriodIndex(start="2000", periods=2) - warning, = m + (warning,) = m assert 'freq="A-DEC"' in str(warning.message) def test_constructor(self): diff --git a/pandas/tests/indexing/multiindex/test_getitem.py b/pandas/tests/indexing/multiindex/test_getitem.py index 4f95e6bd2..519a1eb5b 100644 --- a/pandas/tests/indexing/multiindex/test_getitem.py +++ b/pandas/tests/indexing/multiindex/test_getitem.py @@ -108,7 +108,7 @@ def test_series_getitem_indexing_errors( def test_series_getitem_corner_generator( - multiindex_year_month_day_dataframe_random_data + multiindex_year_month_day_dataframe_random_data, ): s = multiindex_year_month_day_dataframe_random_data["A"] result = s[(x > 0 for x in s)] diff --git a/pandas/tests/indexing/multiindex/test_xs.py b/pandas/tests/indexing/multiindex/test_xs.py index 99f343c2f..40483ffec 100644 --- a/pandas/tests/indexing/multiindex/test_xs.py +++ b/pandas/tests/indexing/multiindex/test_xs.py @@ -211,7 +211,7 @@ def test_xs_level_series_ymd(multiindex_year_month_day_dataframe_random_data): def test_xs_level_series_slice_not_implemented( - multiindex_year_month_day_dataframe_random_data + multiindex_year_month_day_dataframe_random_data, ): # this test is not explicitly testing .xs functionality # TODO: move to another module or refactor diff --git a/pandas/tests/indexing/test_callable.py b/pandas/tests/indexing/test_callable.py index aa73bd728..81dedfdc7 100644 --- a/pandas/tests/indexing/test_callable.py +++ b/pandas/tests/indexing/test_callable.py @@ -17,10 +17,14 @@ class TestIndexingCallable: res = df.loc[lambda x: x.A > 2] tm.assert_frame_equal(res, df.loc[df.A > 2]) - res = df.loc[lambda x: x.A > 2,] # noqa: E231 + res = df.loc[ + lambda x: x.A > 2, + ] # noqa: E231 tm.assert_frame_equal(res, df.loc[df.A > 2,]) # noqa: E231 - res = df.loc[lambda x: x.A > 2,] # noqa: E231 + res = df.loc[ + lambda x: x.A > 2, + ] # noqa: E231 tm.assert_frame_equal(res, df.loc[df.A > 2,]) # noqa: E231 res = df.loc[lambda x: x.B == "b", :] @@ -90,7 +94,9 @@ class TestIndexingCallable: res = df.loc[lambda x: ["A", "C"]] tm.assert_frame_equal(res, df.loc[["A", "C"]]) - res = df.loc[lambda x: ["A", "C"],] # noqa: E231 + res = df.loc[ + lambda x: ["A", "C"], + ] # noqa: E231 tm.assert_frame_equal(res, df.loc[["A", "C"],]) # noqa: E231 res = df.loc[lambda x: ["A", "C"], :] diff --git a/pandas/tests/io/parser/test_index_col.py b/pandas/tests/io/parser/test_index_col.py index 4dfb8d3bd..812255999 100644 --- a/pandas/tests/io/parser/test_index_col.py +++ b/pandas/tests/io/parser/test_index_col.py @@ -22,8 +22,8 @@ KORD4,19990127, 21:00:00, 21:18:00, -0.9900, 2.0100, 3.6000, 0.0000, 270.0000 KORD5,19990127, 22:00:00, 21:56:00, -0.5900, 1.7100, 5.1000, 0.0000, 290.0000 KORD6,19990127, 23:00:00, 22:56:00, -0.5900, 1.7100, 4.6000, 0.0000, 280.0000""" # noqa header = ( - "ID,date,NominalTime,ActualTime,TDew,TAir,Windspeed,Precip,WindDir\n" - ) # noqa + "ID,date,NominalTime,ActualTime,TDew,TAir,Windspeed,Precip,WindDir\n" # noqa + ) if with_header: data = header + no_header diff --git a/pandas/tests/reductions/test_reductions.py b/pandas/tests/reductions/test_reductions.py index 05ebff438..9bd6fb41c 100644 --- a/pandas/tests/reductions/test_reductions.py +++ b/pandas/tests/reductions/test_reductions.py @@ -179,8 +179,8 @@ class TestIndexReductions: [ (0, 400, 3), (500, 0, -6), - (-10 ** 6, 10 ** 6, 4), - (10 ** 6, -10 ** 6, -4), + (-(10 ** 6), 10 ** 6, 4), + (10 ** 6, -(10 ** 6), -4), (0, 10, 20), ], ) diff --git a/pandas/tests/test_algos.py b/pandas/tests/test_algos.py index 9dd88fd5d..885428e51 100644 --- a/pandas/tests/test_algos.py +++ b/pandas/tests/test_algos.py @@ -216,10 +216,10 @@ class TestFactorize: tm.assert_numpy_array_equal(uniques, exp_uniques) def test_int64_factorize(self, writable): - data = np.array([2 ** 63 - 1, -2 ** 63, 2 ** 63 - 1], dtype=np.int64) + data = np.array([2 ** 63 - 1, -(2 ** 63), 2 ** 63 - 1], dtype=np.int64) data.setflags(write=writable) exp_labels = np.array([0, 1, 0], dtype=np.intp) - exp_uniques = np.array([2 ** 63 - 1, -2 ** 63], dtype=np.int64) + exp_uniques = np.array([2 ** 63 - 1, -(2 ** 63)], dtype=np.int64) labels, uniques = algos.factorize(data) tm.assert_numpy_array_equal(labels, exp_labels) @@ -258,7 +258,7 @@ class TestFactorize: "data", [ np.array([0, 1, 0], dtype="u8"), - np.array([-2 ** 63, 1, -2 ** 63], dtype="i8"), + np.array([-(2 ** 63), 1, -(2 ** 63)], dtype="i8"), np.array(["__nan__", "foo", "__nan__"], dtype="object"), ], ) @@ -275,8 +275,8 @@ class TestFactorize: [ (np.array([0, 1, 0, 2], dtype="u8"), 0), (np.array([1, 0, 1, 2], dtype="u8"), 1), - (np.array([-2 ** 63, 1, -2 ** 63, 0], dtype="i8"), -2 ** 63), - (np.array([1, -2 ** 63, 1, 0], dtype="i8"), 1), + (np.array([-(2 ** 63), 1, -(2 ** 63), 0], dtype="i8"), -(2 ** 63)), + (np.array([1, -(2 ** 63), 1, 0], dtype="i8"), 1), (np.array(["a", "", "a", "b"], dtype=object), "a"), (np.array([(), ("a", 1), (), ("a", 2)], dtype=object), ()), (np.array([("a", 1), (), ("a", 1), ("a", 2)], dtype=object), ("a", 1)), diff --git a/pandas/tests/test_nanops.py b/pandas/tests/test_nanops.py index 49d1777df..e6cff5c26 100644 --- a/pandas/tests/test_nanops.py +++ b/pandas/tests/test_nanops.py @@ -302,7 +302,7 @@ class TestnanopsDataFrame: # In the previous implementation mean can overflow for int dtypes, it # is now consistent with numpy - for a in [2 ** 55, -2 ** 55, 20150515061816532]: + for a in [2 ** 55, -(2 ** 55), 20150515061816532]: s = Series(a, index=range(500), dtype=np.int64) result = s.mean() np_result = s.values.mean()Output of
pd.show_versions()INSTALLED VERSIONS
commit : 0de9955
python : 3.7.4.final.0
python-bits : 64
OS : Darwin
OS-release : 18.7.0
machine : x86_64
processor : i386
byteorder : little
LC_ALL : en_US.UTF-8
LANG : en_US.UTF-8
LOCALE : en_US.UTF-8
pandas : 0.26.0.dev0+734.g0de99558b
numpy : 1.17.3
pytz : 2019.3
dateutil : 2.8.0
pip : 19.3.1
setuptools : 41.6.0
Cython : 0.29.14
pytest : 5.2.2
hypothesis : 4.42.6
sphinx : 2.2.1
blosc : 1.8.1
feather : None
xlsxwriter : None
lxml.etree : 4.4.1
html5lib : 1.0.1
pymysql : None
psycopg2 : None
jinja2 : 2.10.3
IPython : 7.9.0
pandas_datareader: None
bs4 : 4.7.1
bottleneck : 1.2.1
fastparquet : 0.3.2
gcsfs : None
lxml.etree : 4.4.1
matplotlib : 3.1.1
numexpr : 2.7.0
odfpy : None
openpyxl : 3.0.0
pandas_gbq : None
pyarrow : 0.15.1
pytables : None
s3fs : None
scipy : 1.3.1
sqlalchemy : None
tables : 3.6.1
xarray : None
xlrd : None
xlwt : None
xlsxwriter : None
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