Merge remote-tracking branch 'upstream/main' into implementation-pdep-4

Author: MarcoGorelli

.github/workflows/python-dev.yml

@@ -54,7 +54,7 @@ jobs:
  os: [ubuntu-latest, macOS-latest, windows-latest]
 
  name: actions-311-dev
- timeout-minutes: 80
+ timeout-minutes: 120
 
  concurrency:
  #https://github.community/t/concurrecy-not-work-for-push/183068/7
@@ -75,7 +75,7 @@ jobs:
  run: |
  python --version
  python -m pip install --upgrade pip setuptools wheel
- python -m pip install git+https://github.com/numpy/numpy.git
+ python -m pip install -i https://pypi.anaconda.org/scipy-wheels-nightly/simple numpy
  python -m pip install git+https://github.com/nedbat/coveragepy.git
  python -m pip install python-dateutil pytz cython hypothesis==6.52.1 pytest>=6.2.5 pytest-xdist pytest-cov pytest-asyncio>=0.17
  python -m pip list
@@ -84,7 +84,7 @@ jobs:
  - name: Build Pandas
  run: |
  python setup.py build_ext -q -j1
- python -m pip install -e . --no-build-isolation --no-use-pep517
+ python -m pip install -e . --no-build-isolation --no-use-pep517 --no-index
 
  - name: Build Version
  run: |

README.md

@@ -128,8 +128,6 @@ or for installing in [development mode](https://pip.pypa.io/en/latest/cli/pip_in
 python -m pip install -e . --no-build-isolation --no-use-pep517
 ```
 
-If you have `make`, you can also use `make develop` to run the same command.
-
 or alternatively
 
 ```sh

pandas/core/arrays/datetimelike.py

@@ -1275,7 +1275,8 @@ def _add_timedeltalike_scalar(self, other):
 
  # PeriodArray overrides, so we only get here with DTA/TDA
  self = cast("DatetimeArray | TimedeltaArray", self)
- other = Timedelta(other)._as_unit(self._unit)
+ other = Timedelta(other)
+ self, other = self._ensure_matching_resos(other)
  return self._add_timedeltalike(other)
 
  def _add_timedelta_arraylike(self, other: TimedeltaArray):

pandas/core/construction.py

@@ -45,7 +45,6 @@
  maybe_convert_platform,
  maybe_infer_to_datetimelike,
  maybe_upcast,
- sanitize_to_nanoseconds,
 )
 from pandas.core.dtypes.common import (
  is_datetime64_ns_dtype,
@@ -782,7 +781,9 @@ def _try_cast(
  if is_ndarray:
  arr = cast(np.ndarray, arr)
  if arr.dtype != object:
- return sanitize_to_nanoseconds(arr, copy=copy)
+ if copy:
+ return arr.copy()
+ return arr
 
  out = maybe_infer_to_datetimelike(arr)
  if out is arr and copy:

pandas/core/dtypes/cast.py

@@ -1423,12 +1423,7 @@ def maybe_cast_to_datetime(
  return astype_nansafe(value, dtype) # type: ignore[arg-type]
 
  elif isinstance(value, np.ndarray):
- if value.dtype.kind in ["M", "m"]:
- # catch a datetime/timedelta that is not of ns variety
- # and no coercion specified
- value = sanitize_to_nanoseconds(value)
-
- elif value.dtype == _dtype_obj:
+ if value.dtype == _dtype_obj:
  value = maybe_infer_to_datetimelike(value)
 
  elif isinstance(value, list):

pandas/core/generic.py

@@ -5878,7 +5878,7 @@ def pipe(
 
  If you have a function that takes the data as (say) the second
  argument, pass a tuple indicating which keyword expects the
- data. For example, suppose ``f`` takes its data as ``arg2``:
+ data. For example, suppose ``func`` takes its data as ``arg2``:
 
  >>> (df.pipe(h)
  ... .pipe(g, arg1=a)

pandas/core/groupby/grouper.py

@@ -26,7 +26,6 @@
 from pandas.util._decorators import cache_readonly
 from pandas.util._exceptions import find_stack_level
 
-from pandas.core.dtypes.cast import sanitize_to_nanoseconds
 from pandas.core.dtypes.common import (
  is_categorical_dtype,
  is_list_like,
@@ -558,9 +557,12 @@ def __init__(
  raise AssertionError(errmsg)
 
  if isinstance(self.grouping_vector, np.ndarray):
- # if we have a date/time-like grouper, make sure that we have
- # Timestamps like
- self.grouping_vector = sanitize_to_nanoseconds(self.grouping_vector)
+ if self.grouping_vector.dtype.kind in ["m", "M"]:
+ # if we have a date/time-like grouper, make sure that we have
+ # Timestamps like
+ # TODO 2022-10-08 we only have one test that gets here and
+ # values are already in nanoseconds in that case.
+ self.grouping_vector = Series(self.grouping_vector).to_numpy()
 
  def __repr__(self) -> str:
  return f"Grouping({self.name})"

pandas/core/internals/blocks.py

@@ -1983,7 +1983,7 @@ def _catch_deprecated_value_error(err: Exception) -> None:
  # IntervalDtype mismatched 'closed'
  pass
  elif "Timezones don't match" not in str(err):
- raise
+ raise err
 
 
 class DatetimeLikeBlock(NDArrayBackedExtensionBlock):

pandas/tests/frame/test_query_eval.py

@@ -36,45 +36,48 @@ def skip_if_no_pandas_parser(parser):
 
 
 class TestCompat:
- def setup_method(self):
- self.df = DataFrame({"A": [1, 2, 3]})
- self.expected1 = self.df[self.df.A > 0]
- self.expected2 = self.df.A + 1
+ @pytest.fixture
+ def df(self):
+ return DataFrame({"A": [1, 2, 3]})
+
+ @pytest.fixture
+ def expected1(self, df):
+ return df[df.A > 0]
+
+ @pytest.fixture
+ def expected2(self, df):
+ return df.A + 1
 
- def test_query_default(self):
+ def test_query_default(self, df, expected1, expected2):
 
  # GH 12749
  # this should always work, whether NUMEXPR_INSTALLED or not
- df = self.df
  result = df.query("A>0")
- tm.assert_frame_equal(result, self.expected1)
+ tm.assert_frame_equal(result, expected1)
  result = df.eval("A+1")
- tm.assert_series_equal(result, self.expected2, check_names=False)
+ tm.assert_series_equal(result, expected2, check_names=False)
 
- def test_query_None(self):
+ def test_query_None(self, df, expected1, expected2):
 
- df = self.df
  result = df.query("A>0", engine=None)
- tm.assert_frame_equal(result, self.expected1)
+ tm.assert_frame_equal(result, expected1)
  result = df.eval("A+1", engine=None)
- tm.assert_series_equal(result, self.expected2, check_names=False)
+ tm.assert_series_equal(result, expected2, check_names=False)
 
- def test_query_python(self):
+ def test_query_python(self, df, expected1, expected2):
 
- df = self.df
  result = df.query("A>0", engine="python")
- tm.assert_frame_equal(result, self.expected1)
+ tm.assert_frame_equal(result, expected1)
  result = df.eval("A+1", engine="python")
- tm.assert_series_equal(result, self.expected2, check_names=False)
+ tm.assert_series_equal(result, expected2, check_names=False)
 
- def test_query_numexpr(self):
+ def test_query_numexpr(self, df, expected1, expected2):
 
- df = self.df
  if NUMEXPR_INSTALLED:
  result = df.query("A>0", engine="numexpr")
- tm.assert_frame_equal(result, self.expected1)
+ tm.assert_frame_equal(result, expected1)
  result = df.eval("A+1", engine="numexpr")
- tm.assert_series_equal(result, self.expected2, check_names=False)
+ tm.assert_series_equal(result, expected2, check_names=False)
  else:
  msg = (
  r"'numexpr' is not installed or an unsupported version. "

pandas/tests/io/json/test_json_table_schema_ext_dtype.py

@@ -111,23 +111,36 @@ def test_as_json_table_type_ext_integer_dtype(self):
 
 
 class TestTableOrient:
- def setup_method(self):
- self.da = DateArray([dt.date(2021, 10, 10)])
- self.dc = DecimalArray([decimal.Decimal(10)])
- self.sa = array(["pandas"], dtype="string")
- self.ia = array([10], dtype="Int64")
- self.df = DataFrame(
+ @pytest.fixture
+ def da(self):
+ return DateArray([dt.date(2021, 10, 10)])
+
+ @pytest.fixture
+ def dc(self):
+ return DecimalArray([decimal.Decimal(10)])
+
+ @pytest.fixture
+ def sa(self):
+ return array(["pandas"], dtype="string")
+
+ @pytest.fixture
+ def ia(self):
+ return array([10], dtype="Int64")
+
+ @pytest.fixture
+ def df(self, da, dc, sa, ia):
+ return DataFrame(
  {
- "A": self.da,
- "B": self.dc,
- "C": self.sa,
- "D": self.ia,
+ "A": da,
+ "B": dc,
+ "C": sa,
+ "D": ia,
  }
  )
 
- def test_build_date_series(self):
+ def test_build_date_series(self, da):
 
- s = Series(self.da, name="a")
+ s = Series(da, name="a")
  s.index.name = "id"
  result = s.to_json(orient="table", date_format="iso")
  result = json.loads(result, object_pairs_hook=OrderedDict)
@@ -151,9 +164,9 @@ def test_build_date_series(self):
 
  assert result == expected
 
- def test_build_decimal_series(self):
+ def test_build_decimal_series(self, dc):
 
- s = Series(self.dc, name="a")
+ s = Series(dc, name="a")
  s.index.name = "id"
  result = s.to_json(orient="table", date_format="iso")
  result = json.loads(result, object_pairs_hook=OrderedDict)
@@ -177,8 +190,8 @@ def test_build_decimal_series(self):
 
  assert result == expected
 
- def test_build_string_series(self):
- s = Series(self.sa, name="a")
+ def test_build_string_series(self, sa):
+ s = Series(sa, name="a")
  s.index.name = "id"
  result = s.to_json(orient="table", date_format="iso")
  result = json.loads(result, object_pairs_hook=OrderedDict)
@@ -202,8 +215,8 @@ def test_build_string_series(self):
 
  assert result == expected
 
- def test_build_int64_series(self):
- s = Series(self.ia, name="a")
+ def test_build_int64_series(self, ia):
+ s = Series(ia, name="a")
  s.index.name = "id"
  result = s.to_json(orient="table", date_format="iso")
  result = json.loads(result, object_pairs_hook=OrderedDict)
@@ -227,9 +240,9 @@ def test_build_int64_series(self):
 
  assert result == expected
 
- def test_to_json(self):
+ def test_to_json(self, df):
 
- df = self.df.copy()
+ df = df.copy()
  df.index.name = "idx"
  result = df.to_json(orient="table", date_format="iso")
  result = json.loads(result, object_pairs_hook=OrderedDict)