diff --git a/.github/workflows/database.yml b/.github/workflows/database.yml
index a2818c85ffa33..d9e78b197de7a 100644
--- a/.github/workflows/database.yml
+++ b/.github/workflows/database.yml
@@ -99,7 +99,7 @@ jobs:
       run: python ci/print_skipped.py
 
     - name: Upload coverage to Codecov
-      uses: codecov/codecov-action@v1
+      uses: codecov/codecov-action@v2
       with:
         flags: unittests
         name: codecov-pandas
diff --git a/.github/workflows/posix.yml b/.github/workflows/posix.yml
index a132b1486ae12..36d410c3f5c4e 100644
--- a/.github/workflows/posix.yml
+++ b/.github/workflows/posix.yml
@@ -92,7 +92,7 @@ jobs:
       run: python ci/print_skipped.py
 
     - name: Upload coverage to Codecov
-      uses: codecov/codecov-action@v1
+      uses: codecov/codecov-action@v2
       with:
         flags: unittests
         name: codecov-pandas
diff --git a/.github/workflows/python-dev.yml b/.github/workflows/python-dev.yml
index 85ef356e7fa14..94ab2b568b636 100644
--- a/.github/workflows/python-dev.yml
+++ b/.github/workflows/python-dev.yml
@@ -37,7 +37,7 @@ jobs:
     - name: Install dependencies
       run: |
         python -m pip install --upgrade pip setuptools wheel
-        pip install git+https://github.com/numpy/numpy.git
+        pip install -i https://pypi.anaconda.org/scipy-wheels-nightly/simple numpy
         pip install git+https://github.com/pytest-dev/pytest.git
         pip install git+https://github.com/nedbat/coveragepy.git
         pip install cython python-dateutil pytz hypothesis pytest-xdist pytest-cov
@@ -74,7 +74,7 @@ jobs:
         coverage report -m
 
     - name: Upload coverage to Codecov
-      uses: codecov/codecov-action@v1
+      uses: codecov/codecov-action@v2
       with:
         flags: unittests
         name: codecov-pandas
diff --git a/.pre-commit-config.yaml b/.pre-commit-config.yaml
index d580fcf4fc545..e2e6fe51b5f8b 100644
--- a/.pre-commit-config.yaml
+++ b/.pre-commit-config.yaml
@@ -110,7 +110,7 @@ repos:
         entry: python scripts/generate_pip_deps_from_conda.py
         files: ^(environment.yml|requirements-dev.txt)$
         pass_filenames: false
-        additional_dependencies: [pyyaml]
+        additional_dependencies: [pyyaml, toml]
     -   id: sync-flake8-versions
         name: Check flake8 version is synced across flake8, yesqa, and environment.yml
         language: python
diff --git a/ci/deps/actions-37-db.yaml b/ci/deps/actions-37-db.yaml
index cfdcf266236e6..9d680cb8338fd 100644
--- a/ci/deps/actions-37-db.yaml
+++ b/ci/deps/actions-37-db.yaml
@@ -15,7 +15,7 @@ dependencies:
   - beautifulsoup4
   - botocore>=1.11
   - dask
-  - fastparquet>=0.4.0, < 0.7.0
+  - fastparquet>=0.4.0
   - fsspec>=0.7.4, <2021.6.0
   - gcsfs>=0.6.0
   - geopandas
@@ -25,7 +25,7 @@ dependencies:
   - flask
   - nomkl
   - numexpr
-  - numpy=1.17.*
+  - numpy=1.18.*
   - odfpy
   - openpyxl
   - pandas-gbq
diff --git a/ci/deps/actions-38-locale.yaml b/ci/deps/actions-38-locale.yaml
index 34a6860936550..dfed0df77a327 100644
--- a/ci/deps/actions-38-locale.yaml
+++ b/ci/deps/actions-38-locale.yaml
@@ -18,7 +18,7 @@ dependencies:
   - html5lib
   - ipython
   - jinja2
-  - jedi<0.18.0
+  - jedi
   - lxml
   - matplotlib<3.3.0
   - moto
diff --git a/ci/deps/actions-38-numpydev.yaml b/ci/deps/actions-38-numpydev.yaml
index 6eed2daac0c3b..e943053f15600 100644
--- a/ci/deps/actions-38-numpydev.yaml
+++ b/ci/deps/actions-38-numpydev.yaml
@@ -11,11 +11,11 @@ dependencies:
   - hypothesis>=3.58.0
 
   # pandas dependencies
+  - python-dateutil
   - pytz
   - pip
   - pip:
     - cython==0.29.21 # GH#34014
-    - "git+git://github.com/dateutil/dateutil.git"
     - "--extra-index-url https://pypi.anaconda.org/scipy-wheels-nightly/simple"
     - "--pre"
     - "numpy"
diff --git a/ci/deps/azure-windows-38.yaml b/ci/deps/azure-windows-38.yaml
index 902daf102ccda..70aa46e8a5851 100644
--- a/ci/deps/azure-windows-38.yaml
+++ b/ci/deps/azure-windows-38.yaml
@@ -15,7 +15,7 @@ dependencies:
   # pandas dependencies
   - blosc
   - bottleneck
-  - fastparquet>=0.4.0, <0.7.0
+  - fastparquet>=0.4.0
   - flask
   - fsspec>=0.8.0, <2021.6.0
   - matplotlib=3.1.3
diff --git a/doc/source/development/contributing_environment.rst b/doc/source/development/contributing_environment.rst
index bc0a3556b9ac1..7b52bf760b601 100644
--- a/doc/source/development/contributing_environment.rst
+++ b/doc/source/development/contributing_environment.rst
@@ -189,11 +189,8 @@ Creating a Python environment (pip)
 ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
 
 If you aren't using conda for your development environment, follow these instructions.
-You'll need to have at least the :ref:`minimum Python version <install.version>` that pandas supports. If your Python version
-is 3.8.0 (or later), you might need to update your ``setuptools`` to version 42.0.0 (or later)
-in your development environment before installing the build dependencies::
-
-      pip install --upgrade setuptools
+You'll need to have at least the :ref:`minimum Python version <install.version>` that pandas supports.
+You also need to have ``setuptools`` 51.0.0 or later to build pandas.
 
 **Unix**/**macOS with virtualenv**
 
diff --git a/doc/source/whatsnew/index.rst b/doc/source/whatsnew/index.rst
index 08f46a53cf2f1..1978913da4073 100644
--- a/doc/source/whatsnew/index.rst
+++ b/doc/source/whatsnew/index.rst
@@ -16,6 +16,7 @@ Version 1.3
 .. toctree::
    :maxdepth: 2
 
+   v1.3.2
    v1.3.1
    v1.3.0
 
diff --git a/doc/source/whatsnew/v1.3.1.rst b/doc/source/whatsnew/v1.3.1.rst
index 0297aeecf01a6..a57995eb0db9a 100644
--- a/doc/source/whatsnew/v1.3.1.rst
+++ b/doc/source/whatsnew/v1.3.1.rst
@@ -48,4 +48,4 @@ Bug fixes
 Contributors
 ~~~~~~~~~~~~
 
-.. contributors:: v1.3.0..v1.3.1|HEAD
+.. contributors:: v1.3.0..v1.3.1
diff --git a/doc/source/whatsnew/v1.3.2.rst b/doc/source/whatsnew/v1.3.2.rst
new file mode 100644
index 0000000000000..97803856c3d94
--- /dev/null
+++ b/doc/source/whatsnew/v1.3.2.rst
@@ -0,0 +1,50 @@
+.. _whatsnew_132:
+
+What's new in 1.3.2 (August 15, 2021)
+-------------------------------------
+
+These are the changes in pandas 1.3.2. See :ref:`release` for a full changelog
+including other versions of pandas.
+
+{{ header }}
+
+.. ---------------------------------------------------------------------------
+
+.. _whatsnew_132.regressions:
+
+Fixed regressions
+~~~~~~~~~~~~~~~~~
+- Performance regression in :meth:`DataFrame.isin` and :meth:`Series.isin` for nullable data types (:issue:`42714`)
+- Regression in updating values of :class:`Series` using boolean index, created by using :meth:`DataFrame.pop` (:issue:`42530`)
+- Regression in :meth:`DataFrame.from_records` with empty records (:issue:`42456`)
+- Fixed regression in :meth:`DataFrame.shift` where ``TypeError`` occurred when shifting DataFrame created by concatenation of slices and fills with values (:issue:`42719`)
+- Regression in :meth:`DataFrame.agg` when the ``func`` argument returned lists and ``axis=1`` (:issue:`42727`)
+- Regression in :meth:`DataFrame.drop` does nothing if :class:`MultiIndex` has duplicates and indexer is a tuple or list of tuples (:issue:`42771`)
+- Fixed regression where :func:`read_csv` raised a ``ValueError`` when parameters ``names`` and ``prefix`` were both set to ``None`` (:issue:`42387`)
+- Fixed regression in comparisons between :class:`Timestamp` object and ``datetime64`` objects outside the implementation bounds for nanosecond ``datetime64`` (:issue:`42794`)
+- Fixed regression in :meth:`.Styler.highlight_min` and :meth:`.Styler.highlight_max` where ``pandas.NA`` was not successfully ignored (:issue:`42650`)
+- Fixed regression in :func:`concat` where ``copy=False`` was not honored in ``axis=1`` Series concatenation (:issue:`42501`)
+- Regression in :meth:`Series.nlargest` and :meth:`Series.nsmallest` with nullable integer or float dtype (:issue:`42816`)
+- Fixed regression in :meth:`Series.quantile` with :class:`Int64Dtype` (:issue:`42626`)
+
+.. ---------------------------------------------------------------------------
+
+.. _whatsnew_132.bug_fixes:
+
+Bug fixes
+~~~~~~~~~
+- Bug in :func:`read_excel` modifies the dtypes dictionary when reading a file with duplicate columns (:issue:`42462`)
+- 1D slices over extension types turn into N-dimensional slices over ExtensionArrays (:issue:`42430`)
+- Fixed bug in :meth:`Series.rolling` and :meth:`DataFrame.rolling` not calculating window bounds correctly for the first row when ``center=True`` and ``window`` is an offset that covers all the rows (:issue:`42753`)
+- :meth:`.Styler.hide_columns` now hides the index name header row as well as column headers (:issue:`42101`)
+- :meth:`.Styler.set_sticky` has amended CSS to control the column/index names and ensure the correct sticky positions (:issue:`42537`)
+- Bug in de-serializing datetime indexes in PYTHONOPTIMIZED mode (:issue:`42866`)
+
+.. ---------------------------------------------------------------------------
+
+.. _whatsnew_132.contributors:
+
+Contributors
+~~~~~~~~~~~~
+
+.. contributors:: v1.3.1..v1.3.2|HEAD
diff --git a/environment.yml b/environment.yml
index 500b8148a94d8..e75e56238205b 100644
--- a/environment.yml
+++ b/environment.yml
@@ -99,7 +99,7 @@ dependencies:
   - xlwt
   - odfpy
 
-  - fastparquet>=0.3.2, <0.7.0  # pandas.read_parquet, DataFrame.to_parquet
+  - fastparquet>=0.3.2  # pandas.read_parquet, DataFrame.to_parquet
   - pyarrow>=0.17.0  # pandas.read_parquet, DataFrame.to_parquet, pandas.read_feather, DataFrame.to_feather
   - python-snappy  # required by pyarrow
 
@@ -109,7 +109,7 @@ dependencies:
   - fsspec>=0.7.4, <2021.6.0  # for generic remote file operations
   - gcsfs>=0.6.0  # file IO when using 'gcs://...' path
   - sqlalchemy  # pandas.read_sql, DataFrame.to_sql
-  - xarray  # DataFrame.to_xarray
+  - xarray<0.19  # DataFrame.to_xarray
   - cftime  # Needed for downstream xarray.CFTimeIndex test
   - pyreadstat  # pandas.read_spss
   - tabulate>=0.8.3  # DataFrame.to_markdown
diff --git a/pandas/_libs/tslibs/timestamps.pyx b/pandas/_libs/tslibs/timestamps.pyx
index 88a2706a35aa2..911cf07862acc 100644
--- a/pandas/_libs/tslibs/timestamps.pyx
+++ b/pandas/_libs/tslibs/timestamps.pyx
@@ -270,9 +270,9 @@ cdef class _Timestamp(ABCTimestamp):
         if op == Py_EQ:
             return False
         if op == Py_LE or op == Py_LT:
-            return other.year <= self.year
+            return self.year <= other.year
         if op == Py_GE or op == Py_GT:
-            return other.year >= self.year
+            return self.year >= other.year
 
     cdef bint _can_compare(self, datetime other):
         if self.tzinfo is not None:
diff --git a/pandas/_libs/window/indexers.pyx b/pandas/_libs/window/indexers.pyx
index d188770576e05..197345b3ce6ac 100644
--- a/pandas/_libs/window/indexers.pyx
+++ b/pandas/_libs/window/indexers.pyx
@@ -79,12 +79,11 @@ def calculate_variable_window_bounds(
     else:
         end[0] = 0
     if center:
-        for j in range(0, num_values + 1):
-            if (index[j] == index[0] + index_growth_sign * window_size / 2 and
-               right_closed):
+        end_bound = index[0] + index_growth_sign * window_size / 2
+        for j in range(0, num_values):
+            if (index[j] < end_bound) or (index[j] == end_bound and right_closed):
                 end[0] = j + 1
-                break
-            elif index[j] >= index[0] + index_growth_sign * window_size / 2:
+            elif index[j] >= end_bound:
                 end[0] = j
                 break
 
diff --git a/pandas/core/algorithms.py b/pandas/core/algorithms.py
index a9ca39b89360c..3ab0350f23c5a 100644
--- a/pandas/core/algorithms.py
+++ b/pandas/core/algorithms.py
@@ -27,6 +27,7 @@
     DtypeObj,
     FrameOrSeriesUnion,
     Scalar,
+    final,
 )
 from pandas.util._decorators import doc
 
@@ -1215,12 +1216,15 @@ def __init__(self, obj, n: int, keep: str):
     def compute(self, method: str) -> FrameOrSeriesUnion:
         raise NotImplementedError
 
+    @final
     def nlargest(self):
         return self.compute("nlargest")
 
+    @final
     def nsmallest(self):
         return self.compute("nsmallest")
 
+    @final
     @staticmethod
     def is_valid_dtype_n_method(dtype: DtypeObj) -> bool:
         """
@@ -1259,6 +1263,18 @@ def compute(self, method: str) -> Series:
 
         dropped = self.obj.dropna()
 
+        if is_extension_array_dtype(dropped.dtype):
+            # GH#41816 bc we have dropped NAs above, MaskedArrays can use the
+            #  numpy logic.
+            from pandas.core.arrays import BaseMaskedArray
+
+            arr = dropped._values
+            if isinstance(arr, BaseMaskedArray):
+                ser = type(dropped)(arr._data, index=dropped.index, name=dropped.name)
+
+                result = type(self)(ser, n=self.n, keep=self.keep).compute(method)
+                return result.astype(arr.dtype)
+
         # slow method
         if n >= len(self.obj):
             ascending = method == "nsmallest"
diff --git a/pandas/core/apply.py b/pandas/core/apply.py
index 69e2650a15f16..aae3262893da2 100644
--- a/pandas/core/apply.py
+++ b/pandas/core/apply.py
@@ -691,21 +691,28 @@ def agg(self):
         obj = self.obj
         axis = self.axis
 
+        # TODO: Avoid having to change state
+        self.obj = self.obj if self.axis == 0 else self.obj.T
+        self.axis = 0
+
+        result = None
+        try:
+            result = super().agg()
+        except TypeError as err:
+            exc = TypeError(
+                "DataFrame constructor called with "
+                f"incompatible data and dtype: {err}"
+            )
+            raise exc from err
+        finally:
+            self.obj = obj
+            self.axis = axis
+
         if axis == 1:
-            result = FrameRowApply(
-                obj.T,
-                self.orig_f,
-                self.raw,
-                self.result_type,
-                self.args,
-                self.kwargs,
-            ).agg()
             result = result.T if result is not None else result
-        else:
-            result = super().agg()
 
         if result is None:
-            result = obj.apply(self.orig_f, axis, args=self.args, **self.kwargs)
+            result = self.obj.apply(self.orig_f, axis, args=self.args, **self.kwargs)
 
         return result
 
diff --git a/pandas/core/array_algos/quantile.py b/pandas/core/array_algos/quantile.py
index 32c50ed38eba0..c5e96f32e261f 100644
--- a/pandas/core/array_algos/quantile.py
+++ b/pandas/core/array_algos/quantile.py
@@ -181,5 +181,10 @@ def _quantile_ea_fallback(
     assert res.ndim == 2
     assert res.shape[0] == 1
     res = res[0]
-    out = type(values)._from_sequence(res, dtype=values.dtype)
+    try:
+        out = type(values)._from_sequence(res, dtype=values.dtype)
+    except TypeError:
+        # GH#42626: not able to safely cast Int64
+        # for floating point output
+        out = np.atleast_2d(np.asarray(res, dtype=np.float64))
     return out
diff --git a/pandas/core/arrays/masked.py b/pandas/core/arrays/masked.py
index 3a152bd5889b7..1d78a74db98f0 100644
--- a/pandas/core/arrays/masked.py
+++ b/pandas/core/arrays/masked.py
@@ -417,7 +417,7 @@ def isin(self, values) -> BooleanArray:  # type: ignore[override]
             # see https://github.com/pandas-dev/pandas/pull/38379 for some discussion
             result[self._mask] = values_have_NA
 
-        mask = np.zeros_like(self, dtype=bool)
+        mask = np.zeros(self._data.shape, dtype=bool)
         return BooleanArray(result, mask, copy=False)
 
     def copy(self: BaseMaskedArrayT) -> BaseMaskedArrayT:
diff --git a/pandas/core/generic.py b/pandas/core/generic.py
index da4feb9640626..b92cf9751e4cf 100644
--- a/pandas/core/generic.py
+++ b/pandas/core/generic.py
@@ -96,7 +96,10 @@
     ABCDataFrame,
     ABCSeries,
 )
-from pandas.core.dtypes.inference import is_hashable
+from pandas.core.dtypes.inference import (
+    is_hashable,
+    is_nested_list_like,
+)
 from pandas.core.dtypes.missing import (
     isna,
     notna,
@@ -4184,6 +4187,7 @@ def _drop_axis(
 
         # Case for non-unique axis
         else:
+            is_tuple_labels = is_nested_list_like(labels) or isinstance(labels, tuple)
             labels = ensure_object(com.index_labels_to_array(labels))
             if level is not None:
                 if not isinstance(axis, MultiIndex):
@@ -4193,9 +4197,14 @@ def _drop_axis(
                 # GH 18561 MultiIndex.drop should raise if label is absent
                 if errors == "raise" and indexer.all():
                     raise KeyError(f"{labels} not found in axis")
-            elif isinstance(axis, MultiIndex) and labels.dtype == "object":
+            elif (
+                isinstance(axis, MultiIndex)
+                and labels.dtype == "object"
+                and not is_tuple_labels
+            ):
                 # Set level to zero in case of MultiIndex and label is string,
                 #  because isin can't handle strings for MultiIndexes GH#36293
+                # In case of tuples we get dtype object but have to use isin GH#42771
                 indexer = ~axis.get_level_values(0).isin(labels)
             else:
                 indexer = ~axis.isin(labels)
diff --git a/pandas/core/indexes/datetimes.py b/pandas/core/indexes/datetimes.py
index fbfee9a1f524c..ff9a273267306 100644
--- a/pandas/core/indexes/datetimes.py
+++ b/pandas/core/indexes/datetimes.py
@@ -92,7 +92,8 @@ def _new_DatetimeIndex(cls, d):
                 # These are already stored in our DatetimeArray; if they are
                 #  also in the pickle and don't match, we have a problem.
                 if key in d:
-                    assert d.pop(key) == getattr(dta, key)
+                    assert d[key] == getattr(dta, key)
+                    d.pop(key)
         result = cls._simple_new(dta, **d)
     else:
         with warnings.catch_warnings():
diff --git a/pandas/core/internals/blocks.py b/pandas/core/internals/blocks.py
index 6275fe39558a3..78ebfad4e3ae9 100644
--- a/pandas/core/internals/blocks.py
+++ b/pandas/core/internals/blocks.py
@@ -1557,6 +1557,16 @@ def _slice(self, slicer):
 
         return self.values[slicer]
 
+    @final
+    def getitem_block_index(self, slicer: slice) -> ExtensionBlock:
+        """
+        Perform __getitem__-like specialized to slicing along index.
+        """
+        # GH#42787 in principle this is equivalent to values[..., slicer], but we don't
+        # require subclasses of ExtensionArray to support that form (for now).
+        new_values = self.values[slicer]
+        return type(self)(new_values, self._mgr_locs, ndim=self.ndim)
+
     def fillna(
         self, value, limit=None, inplace: bool = False, downcast=None
     ) -> list[Block]:
diff --git a/pandas/core/internals/construction.py b/pandas/core/internals/construction.py
index 5e327adfb8905..8987dd5adf5d3 100644
--- a/pandas/core/internals/construction.py
+++ b/pandas/core/internals/construction.py
@@ -761,6 +761,14 @@ def to_arrays(
                 # i.e. numpy structured array
                 columns = ensure_index(data.dtype.names)
                 arrays = [data[name] for name in columns]
+
+                if len(data) == 0:
+                    # GH#42456 the indexing above results in list of 2D ndarrays
+                    # TODO: is that an issue with numpy?
+                    for i, arr in enumerate(arrays):
+                        if arr.ndim == 2:
+                            arrays[i] = arr[:, 0]
+
                 return arrays, columns
         return [], ensure_index([])
 
diff --git a/pandas/core/internals/managers.py b/pandas/core/internals/managers.py
index 1c4fb98ee16bb..ea22cdaa89299 100644
--- a/pandas/core/internals/managers.py
+++ b/pandas/core/internals/managers.py
@@ -386,10 +386,14 @@ def shift(self: T, periods: int, axis: int, fill_value) -> T:
             # We only get here with fill_value not-lib.no_default
             ncols = self.shape[0]
             if periods > 0:
-                indexer = [-1] * periods + list(range(ncols - periods))
+                indexer = np.array(
+                    [-1] * periods + list(range(ncols - periods)), dtype=np.intp
+                )
             else:
                 nper = abs(periods)
-                indexer = list(range(nper, ncols)) + [-1] * nper
+                indexer = np.array(
+                    list(range(nper, ncols)) + [-1] * nper, dtype=np.intp
+                )
             result = self.reindex_indexer(
                 self.items,
                 indexer,
@@ -1184,8 +1188,8 @@ def insert(self, loc: int, item: Hashable, value: ArrayLike) -> None:
             warnings.warn(
                 "DataFrame is highly fragmented.  This is usually the result "
                 "of calling `frame.insert` many times, which has poor performance.  "
-                "Consider using pd.concat instead.  To get a de-fragmented frame, "
-                "use `newframe = frame.copy()`",
+                "Consider joining all columns at once using pd.concat(axis=1) "
+                "instead.  To get a de-fragmented frame, use `newframe = frame.copy()`",
                 PerformanceWarning,
                 stacklevel=5,
             )
diff --git a/pandas/core/reshape/concat.py b/pandas/core/reshape/concat.py
index b49622f4ac36a..3f524a2da0011 100644
--- a/pandas/core/reshape/concat.py
+++ b/pandas/core/reshape/concat.py
@@ -505,7 +505,7 @@ def get_result(self):
                 cons = sample._constructor_expanddim
 
                 index, columns = self.new_axes
-                df = cons(data, index=index)
+                df = cons(data, index=index, copy=self.copy)
                 df.columns = columns
                 return df.__finalize__(self, method="concat")
 
diff --git a/pandas/core/series.py b/pandas/core/series.py
index 2c191a2cc9a68..ddbf4350a63c1 100644
--- a/pandas/core/series.py
+++ b/pandas/core/series.py
@@ -1228,14 +1228,15 @@ def _maybe_update_cacher(
             # a copy
             if ref is None:
                 del self._cacher
+            elif len(self) == len(ref) and self.name in ref.columns:
+                # GH#42530 self.name must be in ref.columns
+                # to ensure column still in dataframe
+                # otherwise, either self or ref has swapped in new arrays
+                ref._maybe_cache_changed(cacher[0], self)
             else:
-                if len(self) == len(ref):
-                    # otherwise, either self or ref has swapped in new arrays
-                    ref._maybe_cache_changed(cacher[0], self)
-                else:
-                    # GH#33675 we have swapped in a new array, so parent
-                    #  reference to self is now invalid
-                    ref._item_cache.pop(cacher[0], None)
+                # GH#33675 we have swapped in a new array, so parent
+                #  reference to self is now invalid
+                ref._item_cache.pop(cacher[0], None)
 
         super()._maybe_update_cacher(clear=clear, verify_is_copy=verify_is_copy)
 
diff --git a/pandas/io/formats/style.py b/pandas/io/formats/style.py
index 660ca9c58a5b0..7ab2b9dec20c8 100644
--- a/pandas/io/formats/style.py
+++ b/pandas/io/formats/style.py
@@ -1473,24 +1473,24 @@ def set_sticky(
         may produce strange behaviour due to CSS controls with missing elements.
         """
         if axis in [0, "index"]:
-            axis, obj, tag, pos = 0, self.data.index, "tbody", "left"
+            axis, obj = 0, self.data.index
             pixel_size = 75 if not pixel_size else pixel_size
         elif axis in [1, "columns"]:
-            axis, obj, tag, pos = 1, self.data.columns, "thead", "top"
+            axis, obj = 1, self.data.columns
             pixel_size = 25 if not pixel_size else pixel_size
         else:
             raise ValueError("`axis` must be one of {0, 1, 'index', 'columns'}")
 
+        props = "position:sticky; background-color:white;"
         if not isinstance(obj, pd.MultiIndex):
             # handling MultiIndexes requires different CSS
-            props = "position:sticky; background-color:white;"
 
             if axis == 1:
                 # stick the first <tr> of <head> and, if index names, the second <tr>
                 # if self._hide_columns then no <thead><tr> here will exist: no conflict
                 styles: CSSStyles = [
                     {
-                        "selector": "thead tr:first-child",
+                        "selector": "thead tr:nth-child(1) th",
                         "props": props + "top:0px; z-index:2;",
                     }
                 ]
@@ -1500,7 +1500,7 @@ def set_sticky(
                     )
                     styles.append(
                         {
-                            "selector": "thead tr:nth-child(2)",
+                            "selector": "thead tr:nth-child(2) th",
                             "props": props
                             + f"top:{pixel_size}px; z-index:2; height:{pixel_size}px; ",
                         }
@@ -1511,34 +1511,67 @@ def set_sticky(
                 # but <th> will exist in <thead>: conflict with initial element
                 styles = [
                     {
-                        "selector": "tr th:first-child",
+                        "selector": "thead tr th:nth-child(1)",
+                        "props": props + "left:0px; z-index:3 !important;",
+                    },
+                    {
+                        "selector": "tbody tr th:nth-child(1)",
                         "props": props + "left:0px; z-index:1;",
-                    }
+                    },
                 ]
 
-            return self.set_table_styles(styles, overwrite=False)
-
         else:
+            # handle the MultiIndex case
             range_idx = list(range(obj.nlevels))
+            levels = sorted(levels) if levels else range_idx
 
-        levels = sorted(levels) if levels else range_idx
-        for i, level in enumerate(levels):
-            self.set_table_styles(
-                [
-                    {
-                        "selector": f"{tag} th.level{level}",
-                        "props": f"position: sticky; "
-                        f"{pos}: {i * pixel_size}px; "
-                        f"{f'height: {pixel_size}px; ' if axis == 1 else ''}"
-                        f"{f'min-width: {pixel_size}px; ' if axis == 0 else ''}"
-                        f"{f'max-width: {pixel_size}px; ' if axis == 0 else ''}"
-                        f"background-color: white;",
-                    }
-                ],
-                overwrite=False,
-            )
+            if axis == 1:
+                styles = []
+                for i, level in enumerate(levels):
+                    styles.append(
+                        {
+                            "selector": f"thead tr:nth-child({level+1}) th",
+                            "props": props
+                            + (
+                                f"top:{i * pixel_size}px; height:{pixel_size}px; "
+                                "z-index:2;"
+                            ),
+                        }
+                    )
+                if not all(name is None for name in self.index.names):
+                    styles.append(
+                        {
+                            "selector": f"thead tr:nth-child({obj.nlevels+1}) th",
+                            "props": props
+                            + (
+                                f"top:{(i+1) * pixel_size}px; height:{pixel_size}px; "
+                                "z-index:2;"
+                            ),
+                        }
+                    )
 
-        return self
+            else:
+                styles = []
+                for i, level in enumerate(levels):
+                    props_ = props + (
+                        f"left:{i * pixel_size}px; "
+                        f"min-width:{pixel_size}px; "
+                        f"max-width:{pixel_size}px; "
+                    )
+                    styles.extend(
+                        [
+                            {
+                                "selector": f"thead tr th:nth-child({level+1})",
+                                "props": props_ + "z-index:3 !important;",
+                            },
+                            {
+                                "selector": f"tbody tr th.level{level}",
+                                "props": props_ + "z-index:1;",
+                            },
+                        ]
+                    )
+
+        return self.set_table_styles(styles, overwrite=False)
 
     def set_table_styles(
         self,
@@ -2312,15 +2345,15 @@ def highlight_max(
         Styler.highlight_quantile: Highlight values defined by a quantile with a style.
         """
 
-        def f(data: FrameOrSeries, props: str) -> np.ndarray:
-            return np.where(data == np.nanmax(data.to_numpy()), props, "")
-
         if props is None:
             props = f"background-color: {color};"
         # error: Argument 1 to "apply" of "Styler" has incompatible type
         # "Callable[[FrameOrSeries, str], ndarray]"; expected "Callable[..., Styler]"
         return self.apply(
-            f, axis=axis, subset=subset, props=props  # type: ignore[arg-type]
+            partial(_highlight_value, op="max"),  # type: ignore[arg-type]
+            axis=axis,
+            subset=subset,
+            props=props,
         )
 
     def highlight_min(
@@ -2363,15 +2396,15 @@ def highlight_min(
         Styler.highlight_quantile: Highlight values defined by a quantile with a style.
         """
 
-        def f(data: FrameOrSeries, props: str) -> np.ndarray:
-            return np.where(data == np.nanmin(data.to_numpy()), props, "")
-
         if props is None:
             props = f"background-color: {color};"
         # error: Argument 1 to "apply" of "Styler" has incompatible type
         # "Callable[[FrameOrSeries, str], ndarray]"; expected "Callable[..., Styler]"
         return self.apply(
-            f, axis=axis, subset=subset, props=props  # type: ignore[arg-type]
+            partial(_highlight_value, op="min"),  # type: ignore[arg-type]
+            axis=axis,
+            subset=subset,
+            props=props,
         )
 
     def highlight_between(
@@ -2870,3 +2903,13 @@ def _highlight_between(
         else np.full(data.shape, True, dtype=bool)
     )
     return np.where(g_left & l_right, props, "")
+
+
+def _highlight_value(data: FrameOrSeries, op: str, props: str) -> np.ndarray:
+    """
+    Return an array of css strings based on the condition of values matching an op.
+    """
+    value = getattr(data, op)(skipna=True)
+    if isinstance(data, DataFrame):  # min/max must be done twice to return scalar
+        value = getattr(value, op)(skipna=True)
+    return np.where(data == value, props, "")
diff --git a/pandas/io/formats/style_render.py b/pandas/io/formats/style_render.py
index 616b89f9e519f..97a05329507c9 100644
--- a/pandas/io/formats/style_render.py
+++ b/pandas/io/formats/style_render.py
@@ -356,6 +356,7 @@ def _translate_header(
             self.data.index.names
             and com.any_not_none(*self.data.index.names)
             and not self.hide_index_
+            and not self.hide_columns_
         ):
             index_names = [
                 _element(
diff --git a/pandas/io/parquet.py b/pandas/io/parquet.py
index b7523fada07d0..5671cce1b966d 100644
--- a/pandas/io/parquet.py
+++ b/pandas/io/parquet.py
@@ -309,14 +309,17 @@ def write(
     def read(
         self, path, columns=None, storage_options: StorageOptions = None, **kwargs
     ):
+        parquet_kwargs: dict[str, Any] = {}
         use_nullable_dtypes = kwargs.pop("use_nullable_dtypes", False)
+        if Version(self.api.__version__) >= Version("0.7.0"):
+            # We are disabling nullable dtypes for fastparquet pending discussion
+            parquet_kwargs["pandas_nulls"] = False
         if use_nullable_dtypes:
             raise ValueError(
                 "The 'use_nullable_dtypes' argument is not supported for the "
                 "fastparquet engine"
             )
         path = stringify_path(path)
-        parquet_kwargs = {}
         handles = None
         if is_fsspec_url(path):
             fsspec = import_optional_dependency("fsspec")
@@ -337,6 +340,7 @@ def read(
                 path, "rb", is_text=False, storage_options=storage_options
             )
             path = handles.handle
+
         parquet_file = self.api.ParquetFile(path, **parquet_kwargs)
 
         result = parquet_file.to_pandas(columns=columns, **kwargs)
@@ -470,7 +474,8 @@ def read_parquet(
 
     use_nullable_dtypes : bool, default False
         If True, use dtypes that use ``pd.NA`` as missing value indicator
-        for the resulting DataFrame (only applicable for ``engine="pyarrow"``).
+        for the resulting DataFrame. (only applicable for the ``pyarrow``
+        engine)
         As new dtypes are added that support ``pd.NA`` in the future, the
         output with this option will change to use those dtypes.
         Note: this is an experimental option, and behaviour (e.g. additional
diff --git a/pandas/io/parsers/python_parser.py b/pandas/io/parsers/python_parser.py
index 13f2d62399418..42e9db75847eb 100644
--- a/pandas/io/parsers/python_parser.py
+++ b/pandas/io/parsers/python_parser.py
@@ -4,6 +4,7 @@
     abc,
     defaultdict,
 )
+from copy import copy
 import csv
 from io import StringIO
 import re
@@ -81,7 +82,7 @@ def __init__(self, f: FilePathOrBuffer | list, **kwds):
         self.verbose = kwds["verbose"]
         self.converters = kwds["converters"]
 
-        self.dtype = kwds["dtype"]
+        self.dtype = copy(kwds["dtype"])
         self.thousands = kwds["thousands"]
         self.decimal = kwds["decimal"]
 
@@ -432,7 +433,6 @@ def _infer_columns(self):
                                 and self.dtype.get(col) is None
                             ):
                                 self.dtype.update({col: self.dtype.get(old_col)})
-
                         this_columns[i] = col
                         counts[col] = cur_count + 1
                 elif have_mi_columns:
diff --git a/pandas/io/parsers/readers.py b/pandas/io/parsers/readers.py
index 06bdbe3054a15..c639a4a9d494e 100644
--- a/pandas/io/parsers/readers.py
+++ b/pandas/io/parsers/readers.py
@@ -1302,7 +1302,12 @@ def _refine_defaults_read(
     if delimiter and (sep is not lib.no_default):
         raise ValueError("Specified a sep and a delimiter; you can only specify one.")
 
-    if names is not lib.no_default and prefix is not lib.no_default:
+    if (
+        names is not None
+        and names is not lib.no_default
+        and prefix is not None
+        and prefix is not lib.no_default
+    ):
         raise ValueError("Specified named and prefix; you can only specify one.")
 
     kwds["names"] = None if names is lib.no_default else names
diff --git a/pandas/plotting/_matplotlib/tools.py b/pandas/plotting/_matplotlib/tools.py
index 9bfa24b6371ab..ebe336bd55c97 100644
--- a/pandas/plotting/_matplotlib/tools.py
+++ b/pandas/plotting/_matplotlib/tools.py
@@ -414,8 +414,12 @@ def handle_shared_axes(
             except IndexError:
                 # if gridspec is used, ax.rowNum and ax.colNum may different
                 # from layout shape. in this case, use last_row logic
+                if compat.mpl_ge_3_4_0():
+                    is_last_row = lambda x: x.get_subplotspec().is_last_row()
+                else:
+                    is_last_row = lambda x: x.is_last_row()
                 for ax in axarr:
-                    if ax.is_last_row():
+                    if is_last_row(ax):
                         continue
                     if sharex or _has_externally_shared_axis(ax, "x"):
                         _remove_labels_from_axis(ax.xaxis)
diff --git a/pandas/tests/apply/test_frame_apply.py b/pandas/tests/apply/test_frame_apply.py
index 995f404dc49d3..c34447764b311 100644
--- a/pandas/tests/apply/test_frame_apply.py
+++ b/pandas/tests/apply/test_frame_apply.py
@@ -671,13 +671,14 @@ def test_apply_dup_names_multi_agg():
     tm.assert_frame_equal(result, expected)
 
 
-def test_apply_nested_result_axis_1():
+@pytest.mark.parametrize("op", ["apply", "agg"])
+def test_apply_nested_result_axis_1(op):
     # GH 13820
     def apply_list(row):
         return [2 * row["A"], 2 * row["C"], 2 * row["B"]]
 
     df = DataFrame(np.zeros((4, 4)), columns=list("ABCD"))
-    result = df.apply(apply_list, axis=1)
+    result = getattr(df, op)(apply_list, axis=1)
     expected = Series(
         [[0.0, 0.0, 0.0], [0.0, 0.0, 0.0], [0.0, 0.0, 0.0], [0.0, 0.0, 0.0]]
     )
diff --git a/pandas/tests/extension/base/getitem.py b/pandas/tests/extension/base/getitem.py
index 96833a2e49fa1..ac181af7875b5 100644
--- a/pandas/tests/extension/base/getitem.py
+++ b/pandas/tests/extension/base/getitem.py
@@ -425,3 +425,23 @@ def test_item(self, data):
 
         with pytest.raises(ValueError, match=msg):
             s.item()
+
+    def test_ellipsis_index(self):
+        # GH42430 1D slices over extension types turn into N-dimensional slices over
+        #  ExtensionArrays
+        class CapturingStringArray(pd.arrays.StringArray):
+            """Extend StringArray to capture arguments to __getitem__"""
+
+            def __getitem__(self, item):
+                self.last_item_arg = item
+                return super().__getitem__(item)
+
+        df = pd.DataFrame(
+            {"col1": CapturingStringArray(np.array(["hello", "world"], dtype=object))}
+        )
+        _ = df.iloc[:1]
+
+        # String comparison because there's no native way to compare slices.
+        # Before the fix for GH42430, last_item_arg would get set to the 2D slice
+        # (Ellipsis, slice(None, 1, None))
+        self.assert_equal(str(df["col1"].array.last_item_arg), "slice(None, 1, None)")
diff --git a/pandas/tests/extension/decimal/test_decimal.py b/pandas/tests/extension/decimal/test_decimal.py
index 7a3f88d0d6c41..99d92a5bbf774 100644
--- a/pandas/tests/extension/decimal/test_decimal.py
+++ b/pandas/tests/extension/decimal/test_decimal.py
@@ -261,18 +261,7 @@ def test_dataframe_constructor_with_dtype():
     tm.assert_frame_equal(result, expected)
 
 
-@pytest.mark.parametrize(
-    "frame",
-    [
-        pytest.param(
-            True,
-            marks=pytest.mark.xfail(
-                reason="pd.concat call inside NDFrame.astype reverts the dtype"
-            ),
-        ),
-        False,
-    ],
-)
+@pytest.mark.parametrize("frame", [True, False])
 def test_astype_dispatches(frame):
     # This is a dtype-specific test that ensures Series[decimal].astype
     # gets all the way through to ExtensionArray.astype
diff --git a/pandas/tests/frame/constructors/test_from_records.py b/pandas/tests/frame/constructors/test_from_records.py
index 35ad9f3e9693b..2322d5f995964 100644
--- a/pandas/tests/frame/constructors/test_from_records.py
+++ b/pandas/tests/frame/constructors/test_from_records.py
@@ -457,3 +457,16 @@ def test_from_records_empty_with_nonempty_fields_gh3682(self):
         b = a[:0]
         df2 = DataFrame.from_records(b, index="id")
         tm.assert_frame_equal(df2, df.iloc[:0])
+
+    def test_from_records_empty2(self):
+        # GH#42456
+        dtype = [("prop", int)]
+        shape = (0, len(dtype))
+        arr = np.empty(shape, dtype=dtype)
+
+        result = DataFrame.from_records(arr)
+        expected = DataFrame({"prop": np.array([], dtype=int)})
+        tm.assert_frame_equal(result, expected)
+
+        alt = DataFrame(arr)
+        tm.assert_frame_equal(alt, expected)
diff --git a/pandas/tests/frame/methods/test_astype.py b/pandas/tests/frame/methods/test_astype.py
index 1f1991214aad0..775a5a38768e6 100644
--- a/pandas/tests/frame/methods/test_astype.py
+++ b/pandas/tests/frame/methods/test_astype.py
@@ -23,6 +23,7 @@
     option_context,
 )
 import pandas._testing as tm
+from pandas.core.arrays.integer import coerce_to_array
 
 
 def _check_cast(df, v):
@@ -726,3 +727,32 @@ def test_astype_categorical_to_string_missing(self):
         cat = df.astype("category")
         result = cat.astype(str)
         tm.assert_frame_equal(result, expected)
+
+
+class IntegerArrayNoCopy(pd.core.arrays.IntegerArray):
+    # GH 42501
+
+    @classmethod
+    def _from_sequence(cls, scalars, *, dtype=None, copy=False):
+        values, mask = coerce_to_array(scalars, dtype=dtype, copy=copy)
+        return IntegerArrayNoCopy(values, mask)
+
+    def copy(self):
+        assert False
+
+
+class Int16DtypeNoCopy(pd.Int16Dtype):
+    # GH 42501
+
+    @classmethod
+    def construct_array_type(cls):
+        return IntegerArrayNoCopy
+
+
+def test_frame_astype_no_copy():
+    # GH 42501
+    df = DataFrame({"a": [1, 4, None, 5], "b": [6, 7, 8, 9]}, dtype=object)
+    result = df.astype({"a": Int16DtypeNoCopy()}, copy=False)
+
+    assert result.a.dtype == pd.Int16Dtype()
+    assert np.shares_memory(df.b.values, result.b.values)
diff --git a/pandas/tests/frame/methods/test_drop.py b/pandas/tests/frame/methods/test_drop.py
index b3eeab9db4ad5..87139b3a1f8b9 100644
--- a/pandas/tests/frame/methods/test_drop.py
+++ b/pandas/tests/frame/methods/test_drop.py
@@ -456,6 +456,17 @@ def test_drop_with_non_unique_multiindex(self):
         expected = DataFrame([2], index=MultiIndex.from_arrays([["y"], ["j"]]))
         tm.assert_frame_equal(result, expected)
 
+    @pytest.mark.parametrize("indexer", [("a", "a"), [("a", "a")]])
+    def test_drop_tuple_with_non_unique_multiindex(self, indexer):
+        # GH#42771
+        idx = MultiIndex.from_product([["a", "b"], ["a", "a"]])
+        df = DataFrame({"x": range(len(idx))}, index=idx)
+        result = df.drop(index=[("a", "a")])
+        expected = DataFrame(
+            {"x": [2, 3]}, index=MultiIndex.from_tuples([("b", "a"), ("b", "a")])
+        )
+        tm.assert_frame_equal(result, expected)
+
     def test_drop_with_duplicate_columns(self):
         df = DataFrame(
             [[1, 5, 7.0], [1, 5, 7.0], [1, 5, 7.0]], columns=["bar", "a", "a"]
diff --git a/pandas/tests/frame/methods/test_shift.py b/pandas/tests/frame/methods/test_shift.py
index 0474206aec06f..9df5f79aa7d19 100644
--- a/pandas/tests/frame/methods/test_shift.py
+++ b/pandas/tests/frame/methods/test_shift.py
@@ -183,6 +183,32 @@ def test_shift_axis1_multiple_blocks(self, using_array_manager):
 
         tm.assert_frame_equal(result, expected)
 
+    @td.skip_array_manager_not_yet_implemented  # TODO(ArrayManager) axis=1 support
+    def test_shift_axis1_multiple_blocks_with_int_fill(self):
+        # GH#42719
+        df1 = DataFrame(np.random.randint(1000, size=(5, 3)))
+        df2 = DataFrame(np.random.randint(1000, size=(5, 2)))
+        df3 = pd.concat([df1.iloc[:4, 1:3], df2.iloc[:4, :]], axis=1)
+        result = df3.shift(2, axis=1, fill_value=np.int_(0))
+        assert len(df3._mgr.blocks) == 2
+
+        expected = df3.take([-1, -1, 0, 1], axis=1)
+        expected.iloc[:, :2] = np.int_(0)
+        expected.columns = df3.columns
+
+        tm.assert_frame_equal(result, expected)
+
+        # Case with periods < 0
+        df3 = pd.concat([df1.iloc[:4, 1:3], df2.iloc[:4, :]], axis=1)
+        result = df3.shift(-2, axis=1, fill_value=np.int_(0))
+        assert len(df3._mgr.blocks) == 2
+
+        expected = df3.take([2, 3, -1, -1], axis=1)
+        expected.iloc[:, -2:] = np.int_(0)
+        expected.columns = df3.columns
+
+        tm.assert_frame_equal(result, expected)
+
     @pytest.mark.filterwarnings("ignore:tshift is deprecated:FutureWarning")
     def test_tshift(self, datetime_frame):
         # TODO: remove this test when tshift deprecation is enforced
diff --git a/pandas/tests/io/excel/test_readers.py b/pandas/tests/io/excel/test_readers.py
index d40fb3ce4a135..1f081ee2dbe33 100644
--- a/pandas/tests/io/excel/test_readers.py
+++ b/pandas/tests/io/excel/test_readers.py
@@ -576,8 +576,12 @@ def test_reader_dtype_str(self, read_ext, dtype, expected):
     def test_dtype_mangle_dup_cols(self, read_ext, dtypes, exp_value):
         # GH#35211
         basename = "df_mangle_dup_col_dtypes"
-        result = pd.read_excel(basename + read_ext, dtype={"a": str, **dtypes})
+        dtype_dict = {"a": str, **dtypes}
+        dtype_dict_copy = dtype_dict.copy()
+        # GH#42462
+        result = pd.read_excel(basename + read_ext, dtype=dtype_dict)
         expected = DataFrame({"a": ["1"], "a.1": [exp_value]})
+        assert dtype_dict == dtype_dict_copy, "dtype dict changed"
         tm.assert_frame_equal(result, expected)
 
     def test_reader_spaces(self, read_ext):
diff --git a/pandas/tests/io/formats/style/test_highlight.py b/pandas/tests/io/formats/style/test_highlight.py
index a681d7c65a190..1b579a43370a2 100644
--- a/pandas/tests/io/formats/style/test_highlight.py
+++ b/pandas/tests/io/formats/style/test_highlight.py
@@ -2,10 +2,10 @@
 import pytest
 
 from pandas import (
+    NA,
     DataFrame,
     IndexSlice,
 )
-import pandas._testing as tm
 
 pytest.importorskip("jinja2")
 
@@ -55,9 +55,7 @@ def test_highlight_minmax_basic(df, f):
     }
     if f == "highlight_min":
         df = -df
-    with tm.assert_produces_warning(RuntimeWarning):
-        # All-NaN slice encountered
-        result = getattr(df.style, f)(axis=1, color="red")._compute().ctx
+    result = getattr(df.style, f)(axis=1, color="red")._compute().ctx
     assert result == expected
 
 
@@ -78,6 +76,26 @@ def test_highlight_minmax_ext(df, f, kwargs):
     assert result == expected
 
 
+@pytest.mark.parametrize("f", ["highlight_min", "highlight_max"])
+@pytest.mark.parametrize("axis", [None, 0, 1])
+def test_highlight_minmax_nulls(f, axis):
+    # GH 42750
+    expected = {
+        (1, 0): [("background-color", "yellow")],
+        (1, 1): [("background-color", "yellow")],
+    }
+    if axis == 1:
+        expected.update({(2, 1): [("background-color", "yellow")]})
+
+    if f == "highlight_max":
+        df = DataFrame({"a": [NA, 1, None], "b": [np.nan, 1, -1]})
+    else:
+        df = DataFrame({"a": [NA, -1, None], "b": [np.nan, -1, 1]})
+
+    result = getattr(df.style, f)(axis=axis)._compute().ctx
+    assert result == expected
+
+
 @pytest.mark.parametrize(
     "kwargs",
     [
diff --git a/pandas/tests/io/formats/style/test_html.py b/pandas/tests/io/formats/style/test_html.py
index 4e71cb4c46626..4e1db69177534 100644
--- a/pandas/tests/io/formats/style/test_html.py
+++ b/pandas/tests/io/formats/style/test_html.py
@@ -281,26 +281,32 @@ def test_sticky_basic(styler, index, columns, index_name):
     if columns:
         styler.set_sticky(axis=1)
 
-    res = styler.set_uuid("").to_html()
-
-    css_for_index = (
-        "tr th:first-child {\n  position: sticky;\n  background-color: white;\n  "
-        "left: 0px;\n  z-index: 1;\n}"
+    left_css = (
+        "#T_ {0} {{\n  position: sticky;\n  background-color: white;\n"
+        "  left: 0px;\n  z-index: {1};\n}}"
     )
-    assert (css_for_index in res) is index
-
-    css_for_cols_1 = (
-        "thead tr:first-child {\n  position: sticky;\n  background-color: white;\n  "
-        "top: 0px;\n  z-index: 2;\n"
+    top_css = (
+        "#T_ {0} {{\n  position: sticky;\n  background-color: white;\n"
+        "  top: {1}px;\n  z-index: {2};\n{3}}}"
     )
-    css_for_cols_1 += "  height: 25px;\n}" if index_name else "}"
-    assert (css_for_cols_1 in res) is columns
 
-    css_for_cols_2 = (
-        "thead tr:nth-child(2) {\n  position: sticky;\n  background-color: white;\n  "
-        "top: 25px;\n  z-index: 2;\n  height: 25px;\n}"
+    res = styler.set_uuid("").to_html()
+
+    # test index stickys over thead and tbody
+    assert (left_css.format("thead tr th:nth-child(1)", "3 !important") in res) is index
+    assert (left_css.format("tbody tr th:nth-child(1)", "1") in res) is index
+
+    # test column stickys including if name row
+    assert (
+        top_css.format("thead tr:nth-child(1) th", "0", "2", "  height: 25px;\n") in res
+    ) is (columns and index_name)
+    assert (
+        top_css.format("thead tr:nth-child(2) th", "25", "2", "  height: 25px;\n")
+        in res
+    ) is (columns and index_name)
+    assert (top_css.format("thead tr:nth-child(1) th", "0", "2", "") in res) is (
+        columns and not index_name
     )
-    assert (css_for_cols_2 in res) is (index_name and columns)
 
 
 @pytest.mark.parametrize("index", [False, True])
@@ -311,73 +317,30 @@ def test_sticky_mi(styler_mi, index, columns):
     if columns:
         styler_mi.set_sticky(axis=1)
 
-    res = styler_mi.set_uuid("").to_html()
-    assert (
-        (
-            dedent(
-                """\
-        #T_ tbody th.level0 {
-          position: sticky;
-          left: 0px;
-          min-width: 75px;
-          max-width: 75px;
-          background-color: white;
-        }
-        """
-            )
-            in res
-        )
-        is index
+    left_css = (
+        "#T_ {0} {{\n  position: sticky;\n  background-color: white;\n"
+        "  left: {1}px;\n  min-width: 75px;\n  max-width: 75px;\n  z-index: {2};\n}}"
     )
-    assert (
-        (
-            dedent(
-                """\
-        #T_ tbody th.level1 {
-          position: sticky;
-          left: 75px;
-          min-width: 75px;
-          max-width: 75px;
-          background-color: white;
-        }
-        """
-            )
-            in res
-        )
-        is index
+    top_css = (
+        "#T_ {0} {{\n  position: sticky;\n  background-color: white;\n"
+        "  top: {1}px;\n  height: 25px;\n  z-index: {2};\n}}"
     )
+
+    res = styler_mi.set_uuid("").to_html()
+
+    # test the index stickys for thead and tbody over both levels
     assert (
-        (
-            dedent(
-                """\
-        #T_ thead th.level0 {
-          position: sticky;
-          top: 0px;
-          height: 25px;
-          background-color: white;
-        }
-        """
-            )
-            in res
-        )
-        is columns
-    )
+        left_css.format("thead tr th:nth-child(1)", "0", "3 !important") in res
+    ) is index
+    assert (left_css.format("tbody tr th.level0", "0", "1") in res) is index
     assert (
-        (
-            dedent(
-                """\
-        #T_ thead th.level1 {
-          position: sticky;
-          top: 25px;
-          height: 25px;
-          background-color: white;
-        }
-        """
-            )
-            in res
-        )
-        is columns
-    )
+        left_css.format("thead tr th:nth-child(2)", "75", "3 !important") in res
+    ) is index
+    assert (left_css.format("tbody tr th.level1", "75", "1") in res) is index
+
+    # test the column stickys for each level row
+    assert (top_css.format("thead tr:nth-child(1) th", "0", "2") in res) is columns
+    assert (top_css.format("thead tr:nth-child(2) th", "25", "2") in res) is columns
 
 
 @pytest.mark.parametrize("index", [False, True])
@@ -388,43 +351,29 @@ def test_sticky_levels(styler_mi, index, columns):
     if columns:
         styler_mi.set_sticky(axis=1, levels=[1])
 
-    res = styler_mi.set_uuid("").to_html()
-    assert "#T_ tbody th.level0 {" not in res
-    assert "#T_ thead th.level0 {" not in res
-    assert (
-        (
-            dedent(
-                """\
-        #T_ tbody th.level1 {
-          position: sticky;
-          left: 0px;
-          min-width: 75px;
-          max-width: 75px;
-          background-color: white;
-        }
-        """
-            )
-            in res
-        )
-        is index
+    left_css = (
+        "#T_ {0} {{\n  position: sticky;\n  background-color: white;\n"
+        "  left: {1}px;\n  min-width: 75px;\n  max-width: 75px;\n  z-index: {2};\n}}"
     )
-    assert (
-        (
-            dedent(
-                """\
-        #T_ thead th.level1 {
-          position: sticky;
-          top: 0px;
-          height: 25px;
-          background-color: white;
-        }
-        """
-            )
-            in res
-        )
-        is columns
+    top_css = (
+        "#T_ {0} {{\n  position: sticky;\n  background-color: white;\n"
+        "  top: {1}px;\n  height: 25px;\n  z-index: {2};\n}}"
     )
 
+    res = styler_mi.set_uuid("").to_html()
+
+    # test no sticking of level0
+    assert "#T_ thead tr th:nth-child(1)" not in res
+    assert "#T_ tbody tr th.level0" not in res
+    assert "#T_ thead tr:nth-child(1) th" not in res
+
+    # test sticking level1
+    assert (
+        left_css.format("thead tr th:nth-child(2)", "0", "3 !important") in res
+    ) is index
+    assert (left_css.format("tbody tr th.level1", "0", "1") in res) is index
+    assert (top_css.format("thead tr:nth-child(2) th", "0", "2") in res) is columns
+
 
 def test_sticky_raises(styler):
     with pytest.raises(ValueError, match="`axis` must be"):
diff --git a/pandas/tests/io/formats/style/test_style.py b/pandas/tests/io/formats/style/test_style.py
index f2c2f673909d4..99c725ed8df69 100644
--- a/pandas/tests/io/formats/style/test_style.py
+++ b/pandas/tests/io/formats/style/test_style.py
@@ -1109,7 +1109,7 @@ def test_hide_column_headers(self):
 
         self.df.index.name = "some_name"
         ctx = self.df.style.hide_columns()._translate(True, True)
-        assert len(ctx["head"]) == 1  # only a single row for index names: no col heads
+        assert len(ctx["head"]) == 0  # no header for index names, changed in #42101
 
     def test_hide_single_index(self):
         # GH 14194
diff --git a/pandas/tests/io/parser/common/test_common_basic.py b/pandas/tests/io/parser/common/test_common_basic.py
index a1c76e2740dbe..b2e528aa5f8d5 100644
--- a/pandas/tests/io/parser/common/test_common_basic.py
+++ b/pandas/tests/io/parser/common/test_common_basic.py
@@ -764,15 +764,24 @@ def test_read_table_delim_whitespace_non_default_sep(all_parsers, delimiter):
 
 
 @pytest.mark.parametrize("func", ["read_csv", "read_table"])
-@pytest.mark.parametrize("prefix", [None, "x"])
-@pytest.mark.parametrize("names", [None, ["a"]])
-def test_names_and_prefix_not_lib_no_default(all_parsers, names, prefix, func):
+def test_names_and_prefix_not_None_raises(all_parsers, func):
     # GH#39123
     f = StringIO("a,b\n1,2")
     parser = all_parsers
     msg = "Specified named and prefix; you can only specify one."
     with pytest.raises(ValueError, match=msg):
-        getattr(parser, func)(f, names=names, prefix=prefix)
+        getattr(parser, func)(f, names=["a", "b"], prefix="x")
+
+
+@pytest.mark.parametrize("func", ["read_csv", "read_table"])
+@pytest.mark.parametrize("prefix, names", [(None, ["x0", "x1"]), ("x", None)])
+def test_names_and_prefix_explicit_None(all_parsers, names, prefix, func):
+    # GH42387
+    f = StringIO("a,b\n1,2")
+    expected = DataFrame({"x0": ["a", "1"], "x1": ["b", "2"]})
+    parser = all_parsers
+    result = getattr(parser, func)(f, names=names, sep=",", prefix=prefix, header=None)
+    tm.assert_frame_equal(result, expected)
 
 
 def test_dict_keys_as_names(all_parsers):
diff --git a/pandas/tests/io/parser/dtypes/test_dtypes_basic.py b/pandas/tests/io/parser/dtypes/test_dtypes_basic.py
index bc20f1d1eea5f..0b59e877cd9a1 100644
--- a/pandas/tests/io/parser/dtypes/test_dtypes_basic.py
+++ b/pandas/tests/io/parser/dtypes/test_dtypes_basic.py
@@ -245,8 +245,12 @@ def test_dtype_mangle_dup_cols(all_parsers, dtypes, exp_value):
     # GH#35211
     parser = all_parsers
     data = """a,a\n1,1"""
-    result = parser.read_csv(StringIO(data), dtype={"a": str, **dtypes})
+    dtype_dict = {"a": str, **dtypes}
+    # GH#42462
+    dtype_dict_copy = dtype_dict.copy()
+    result = parser.read_csv(StringIO(data), dtype=dtype_dict)
     expected = DataFrame({"a": ["1"], "a.1": [exp_value]})
+    assert dtype_dict == dtype_dict_copy, "dtype dict changed"
     tm.assert_frame_equal(result, expected)
 
 
diff --git a/pandas/tests/io/test_parquet.py b/pandas/tests/io/test_parquet.py
index d100c584b698a..914f68b90ad37 100644
--- a/pandas/tests/io/test_parquet.py
+++ b/pandas/tests/io/test_parquet.py
@@ -575,6 +575,47 @@ def test_write_column_index_nonstring(self, pa):
         msg = r"parquet must have string column names"
         self.check_error_on_write(df, engine, ValueError, msg)
 
+    def test_use_nullable_dtypes(self, engine):
+        import pyarrow.parquet as pq
+
+        if engine == "fastparquet":
+            # We are manually disabling fastparquet's
+            # nullable dtype support pending discussion
+            pytest.skip("Fastparquet nullable dtype support is disabled")
+
+        table = pyarrow.table(
+            {
+                "a": pyarrow.array([1, 2, 3, None], "int64"),
+                "b": pyarrow.array([1, 2, 3, None], "uint8"),
+                "c": pyarrow.array(["a", "b", "c", None]),
+                "d": pyarrow.array([True, False, True, None]),
+                # Test that nullable dtypes used even in absence of nulls
+                "e": pyarrow.array([1, 2, 3, 4], "int64"),
+            }
+        )
+        with tm.ensure_clean() as path:
+            # write manually with pyarrow to write integers
+            pq.write_table(table, path)
+            result1 = read_parquet(path, engine=engine)
+            result2 = read_parquet(path, engine=engine, use_nullable_dtypes=True)
+
+        assert result1["a"].dtype == np.dtype("float64")
+        expected = pd.DataFrame(
+            {
+                "a": pd.array([1, 2, 3, None], dtype="Int64"),
+                "b": pd.array([1, 2, 3, None], dtype="UInt8"),
+                "c": pd.array(["a", "b", "c", None], dtype="string"),
+                "d": pd.array([True, False, True, None], dtype="boolean"),
+                "e": pd.array([1, 2, 3, 4], dtype="Int64"),
+            }
+        )
+        if engine == "fastparquet":
+            # Fastparquet doesn't support string columns yet
+            # Only int and boolean
+            result2 = result2.drop("c", axis=1)
+            expected = expected.drop("c", axis=1)
+        tm.assert_frame_equal(result2, expected)
+
 
 @pytest.mark.filterwarnings("ignore:CategoricalBlock is deprecated:DeprecationWarning")
 class TestParquetPyArrow(Base):
@@ -829,35 +870,6 @@ def test_additional_extension_types(self, pa):
         )
         check_round_trip(df, pa)
 
-    @td.skip_if_no("pyarrow")
-    def test_use_nullable_dtypes(self, pa):
-        import pyarrow.parquet as pq
-
-        table = pyarrow.table(
-            {
-                "a": pyarrow.array([1, 2, 3, None], "int64"),
-                "b": pyarrow.array([1, 2, 3, None], "uint8"),
-                "c": pyarrow.array(["a", "b", "c", None]),
-                "d": pyarrow.array([True, False, True, None]),
-            }
-        )
-        with tm.ensure_clean() as path:
-            # write manually with pyarrow to write integers
-            pq.write_table(table, path)
-            result1 = read_parquet(path)
-            result2 = read_parquet(path, use_nullable_dtypes=True)
-
-        assert result1["a"].dtype == np.dtype("float64")
-        expected = pd.DataFrame(
-            {
-                "a": pd.array([1, 2, 3, None], dtype="Int64"),
-                "b": pd.array([1, 2, 3, None], dtype="UInt8"),
-                "c": pd.array(["a", "b", "c", None], dtype="string"),
-                "d": pd.array([True, False, True, None], dtype="boolean"),
-            }
-        )
-        tm.assert_frame_equal(result2, expected)
-
     def test_timestamp_nanoseconds(self, pa):
         # with version 2.0, pyarrow defaults to writing the nanoseconds, so
         # this should work without error
@@ -928,7 +940,9 @@ def test_duplicate_columns(self, fp):
     def test_bool_with_none(self, fp):
         df = pd.DataFrame({"a": [True, None, False]})
         expected = pd.DataFrame({"a": [1.0, np.nan, 0.0]}, dtype="float16")
-        check_round_trip(df, fp, expected=expected)
+        # Fastparquet bug in 0.7.1 makes it so that this dtype becomes
+        # float64
+        check_round_trip(df, fp, expected=expected, check_dtype=False)
 
     def test_unsupported(self, fp):
 
@@ -1049,7 +1063,7 @@ def test_timezone_aware_index(self, fp, timezone_aware_date_list):
         expected.index.name = "index"
         check_round_trip(df, fp, expected=expected)
 
-    def test_use_nullable_dtypes_not_supported(self, fp):
+    def test_use_nullable_dtypes_not_supported(self, monkeypatch, fp):
         df = pd.DataFrame({"a": [1, 2]})
 
         with tm.ensure_clean() as path:
diff --git a/pandas/tests/scalar/timestamp/test_comparisons.py b/pandas/tests/scalar/timestamp/test_comparisons.py
index 555067f2aba1a..ee36223eb2496 100644
--- a/pandas/tests/scalar/timestamp/test_comparisons.py
+++ b/pandas/tests/scalar/timestamp/test_comparisons.py
@@ -266,6 +266,19 @@ def test_timestamp_compare_oob_dt64(self):
         assert Timestamp.max < other + us
         # Note: numpy gets the reversed comparison wrong
 
+        # GH-42794
+        other = datetime(9999, 9, 9)
+        assert Timestamp.min < other
+        assert other > Timestamp.min
+        assert Timestamp.max < other
+        assert other > Timestamp.max
+
+        other = datetime(1, 1, 1)
+        assert Timestamp.max > other
+        assert other < Timestamp.max
+        assert Timestamp.min > other
+        assert other < Timestamp.min
+
     def test_compare_zerodim_array(self):
         # GH#26916
         ts = Timestamp.now()
diff --git a/pandas/tests/series/indexing/test_setitem.py b/pandas/tests/series/indexing/test_setitem.py
index 13054062defb4..2ad3aee99d147 100644
--- a/pandas/tests/series/indexing/test_setitem.py
+++ b/pandas/tests/series/indexing/test_setitem.py
@@ -8,6 +8,7 @@
 
 from pandas import (
     Categorical,
+    DataFrame,
     DatetimeIndex,
     Index,
     MultiIndex,
@@ -906,3 +907,17 @@ def val(self):
     def is_inplace(self, obj):
         # This is specific to the 4 cases currently implemented for this class.
         return obj.dtype.kind != "i"
+
+
+def test_setitem_with_bool_indexer():
+    # GH#42530
+
+    df = DataFrame({"a": [1, 2, 3], "b": [4, 5, 6]})
+    result = df.pop("b")
+    result[[True, False, False]] = 9
+    expected = Series(data=[9, 5, 6], name="b")
+    tm.assert_series_equal(result, expected)
+
+    df.loc[[True, False, False], "a"] = 10
+    expected = DataFrame({"a": [10, 2, 3]})
+    tm.assert_frame_equal(df, expected)
diff --git a/pandas/tests/series/methods/test_clip.py b/pandas/tests/series/methods/test_clip.py
index e4803a9cd3038..620f529b522ae 100644
--- a/pandas/tests/series/methods/test_clip.py
+++ b/pandas/tests/series/methods/test_clip.py
@@ -1,3 +1,5 @@
+from datetime import datetime
+
 import numpy as np
 import pytest
 
@@ -128,6 +130,15 @@ def test_clip_with_datetimes(self):
         )
         tm.assert_series_equal(result, expected)
 
+    def test_clip_with_timestamps_and_oob_datetimes(self):
+        # GH-42794
+        ser = Series([datetime(1, 1, 1), datetime(9999, 9, 9)])
+
+        result = ser.clip(lower=Timestamp.min, upper=Timestamp.max)
+        expected = Series([Timestamp.min, Timestamp.max], dtype="object")
+
+        tm.assert_series_equal(result, expected)
+
     def test_clip_pos_args_deprecation(self):
         # https://github.com/pandas-dev/pandas/issues/41485
         ser = Series([1, 2, 3])
diff --git a/pandas/tests/series/methods/test_nlargest.py b/pandas/tests/series/methods/test_nlargest.py
index 3af06145b9fcd..0efb0663a0327 100644
--- a/pandas/tests/series/methods/test_nlargest.py
+++ b/pandas/tests/series/methods/test_nlargest.py
@@ -211,3 +211,19 @@ def test_nlargest_boolean(self, data, expected):
         result = ser.nlargest(1)
         expected = Series(expected)
         tm.assert_series_equal(result, expected)
+
+    def test_nlargest_nullable(self, any_nullable_numeric_dtype):
+        # GH#42816
+        dtype = any_nullable_numeric_dtype
+        arr = np.random.randn(10).astype(dtype.lower(), copy=False)
+
+        ser = Series(arr.copy(), dtype=dtype)
+        ser[1] = pd.NA
+        result = ser.nlargest(5)
+
+        expected = (
+            Series(np.delete(arr, 1), index=ser.index.delete(1))
+            .nlargest(5)
+            .astype(dtype)
+        )
+        tm.assert_series_equal(result, expected)
diff --git a/pandas/tests/series/methods/test_quantile.py b/pandas/tests/series/methods/test_quantile.py
index 461c81bc3b44f..84bfe8524634b 100644
--- a/pandas/tests/series/methods/test_quantile.py
+++ b/pandas/tests/series/methods/test_quantile.py
@@ -217,3 +217,9 @@ def test_quantile_empty(self):
         res = s.quantile([0.5])
         exp = Series([pd.NaT], index=[0.5])
         tm.assert_series_equal(res, exp)
+
+    @pytest.mark.parametrize("dtype", [int, float, "Int64"])
+    def test_quantile_dtypes(self, dtype):
+        result = Series([1, 2, 3], dtype=dtype).quantile(np.arange(0, 1, 0.25))
+        expected = Series(np.arange(1, 3, 0.5), index=np.arange(0, 1, 0.25))
+        tm.assert_series_equal(result, expected)
diff --git a/pandas/tests/test_downstream.py b/pandas/tests/test_downstream.py
index ea95f90d3a2cb..e34ca9e7f9e27 100644
--- a/pandas/tests/test_downstream.py
+++ b/pandas/tests/test_downstream.py
@@ -69,6 +69,21 @@ def test_oo_optimizable():
     subprocess.check_call([sys.executable, "-OO", "-c", "import pandas"])
 
 
+def test_oo_optimized_datetime_index_unpickle():
+    # GH 42866
+    subprocess.check_call(
+        [
+            sys.executable,
+            "-OO",
+            "-c",
+            (
+                "import pandas as pd, pickle; "
+                "pickle.loads(pickle.dumps(pd.date_range('2021-01-01', periods=1)))"
+            ),
+        ]
+    )
+
+
 @tm.network
 # Cython import warning
 @pytest.mark.filterwarnings("ignore:pandas.util.testing is deprecated")
diff --git a/pandas/tests/window/test_rolling.py b/pandas/tests/window/test_rolling.py
index 77ca482936298..5bf2df0208ddc 100644
--- a/pandas/tests/window/test_rolling.py
+++ b/pandas/tests/window/test_rolling.py
@@ -220,6 +220,36 @@ def test_datetimelike_centered_selections(
     tm.assert_frame_equal(result, expected, check_dtype=False)
 
 
+@pytest.mark.parametrize(
+    "window,closed,expected",
+    [
+        ("3s", "right", [3.0, 3.0, 3.0]),
+        ("3s", "both", [3.0, 3.0, 3.0]),
+        ("3s", "left", [3.0, 3.0, 3.0]),
+        ("3s", "neither", [3.0, 3.0, 3.0]),
+        ("2s", "right", [3.0, 2.0, 2.0]),
+        ("2s", "both", [3.0, 3.0, 3.0]),
+        ("2s", "left", [1.0, 3.0, 3.0]),
+        ("2s", "neither", [1.0, 2.0, 2.0]),
+    ],
+)
+def test_datetimelike_centered_offset_covers_all(
+    window, closed, expected, frame_or_series
+):
+    # GH 42753
+
+    index = [
+        Timestamp("20130101 09:00:01"),
+        Timestamp("20130101 09:00:02"),
+        Timestamp("20130101 09:00:02"),
+    ]
+    df = frame_or_series([1, 1, 1], index=index)
+
+    result = df.rolling(window, closed=closed, center=True).sum()
+    expected = frame_or_series(expected, index=index)
+    tm.assert_equal(result, expected)
+
+
 def test_even_number_window_alignment():
     # see discussion in GH 38780
     s = Series(range(3), index=date_range(start="2020-01-01", freq="D", periods=3))
diff --git a/pyproject.toml b/pyproject.toml
index 86b255ab6bf58..0d1aefb9d4b55 100644
--- a/pyproject.toml
+++ b/pyproject.toml
@@ -2,7 +2,7 @@
 # Minimum requirements for the build system to execute.
 # See https://github.com/scipy/scipy/pull/12940 for the AIX issue.
 requires = [
-    "setuptools>=38.6.0",
+    "setuptools>=51.0.0",
     "wheel",
     "Cython>=0.29.21,<3",  # Note: sync with setup.py
     # Numpy requirements for different OS/architectures
diff --git a/requirements-dev.txt b/requirements-dev.txt
index 712c9a4b89273..3b40c9c300ace 100644
--- a/requirements-dev.txt
+++ b/requirements-dev.txt
@@ -64,7 +64,7 @@ xlrd
 xlsxwriter
 xlwt
 odfpy
-fastparquet>=0.3.2, <0.7.0
+fastparquet>=0.3.2
 pyarrow>=0.17.0
 python-snappy
 pyqt5>=5.9.2
@@ -73,7 +73,7 @@ s3fs>=0.4.0
 fsspec>=0.7.4, <2021.6.0
 gcsfs>=0.6.0
 sqlalchemy
-xarray
+xarray<0.19
 cftime
 pyreadstat
 tabulate>=0.8.3
@@ -81,3 +81,4 @@ natsort
 git+https://github.com/pydata/pydata-sphinx-theme.git@master
 numpydoc < 1.2
 pandas-dev-flaker==0.2.0
+setuptools>=51.0.0
diff --git a/scripts/generate_pip_deps_from_conda.py b/scripts/generate_pip_deps_from_conda.py
index 1ad9ec03925a0..ec4b6c81f764c 100755
--- a/scripts/generate_pip_deps_from_conda.py
+++ b/scripts/generate_pip_deps_from_conda.py
@@ -13,17 +13,18 @@
     $ python scripts/generate_pip_deps_from_conda.py --compare
 """
 import argparse
-import os
+import pathlib
 import re
 import sys
 
+import toml
 import yaml
 
 EXCLUDE = {"python", "c-compiler", "cxx-compiler"}
 RENAME = {"pytables": "tables", "pyqt": "pyqt5", "dask-core": "dask"}
 
 
-def conda_package_to_pip(package):
+def conda_package_to_pip(package: str):
     """
     Convert a conda package to its pip equivalent.
 
@@ -36,17 +37,13 @@ def conda_package_to_pip(package):
     package = re.sub("(?<=[^<>])=", "==", package).strip()
 
     for compare in ("<=", ">=", "=="):
-        if compare not in package:
-            continue
+        if compare in package:
+            pkg, version = package.split(compare)
+            if pkg in EXCLUDE:
+                return
 
-        pkg, version = package.split(compare)
-        if pkg in EXCLUDE:
-            return
-
-        if pkg in RENAME:
-            return "".join((RENAME[pkg], compare, version))
-
-        break
+            if pkg in RENAME:
+                return "".join((RENAME[pkg], compare, version))
 
     if package in EXCLUDE:
         return
@@ -57,16 +54,18 @@ def conda_package_to_pip(package):
     return package
 
 
-def main(conda_fname, pip_fname, compare=False):
+def generate_pip_from_conda(
+    conda_path: pathlib.Path, pip_path: pathlib.Path, compare: bool = False
+) -> bool:
     """
     Generate the pip dependencies file from the conda file, or compare that
     they are synchronized (``compare=True``).
 
     Parameters
     ----------
-    conda_fname : str
+    conda_path : pathlib.Path
         Path to the conda file with dependencies (e.g. `environment.yml`).
-    pip_fname : str
+    pip_path : pathlib.Path
         Path to the pip file with dependencies (e.g. `requirements-dev.txt`).
     compare : bool, default False
         Whether to generate the pip file (``False``) or to compare if the
@@ -78,8 +77,8 @@ def main(conda_fname, pip_fname, compare=False):
     bool
         True if the comparison fails, False otherwise
     """
-    with open(conda_fname) as conda_fd:
-        deps = yaml.safe_load(conda_fd)["dependencies"]
+    with conda_path.open() as file:
+        deps = yaml.safe_load(file)["dependencies"]
 
     pip_deps = []
     for dep in deps:
@@ -88,24 +87,30 @@ def main(conda_fname, pip_fname, compare=False):
             if conda_dep:
                 pip_deps.append(conda_dep)
         elif isinstance(dep, dict) and len(dep) == 1 and "pip" in dep:
-            pip_deps += dep["pip"]
+            pip_deps.extend(dep["pip"])
         else:
             raise ValueError(f"Unexpected dependency {dep}")
 
-    fname = os.path.split(conda_fname)[1]
     header = (
-        f"# This file is auto-generated from {fname}, do not modify.\n"
+        f"# This file is auto-generated from {conda_path.name}, do not modify.\n"
         "# See that file for comments about the need/usage of each dependency.\n\n"
     )
     pip_content = header + "\n".join(pip_deps) + "\n"
 
+    # add setuptools to requirements-dev.txt
+    meta = toml.load(pathlib.Path(conda_path.parent, "pyproject.toml"))
+    for requirement in meta["build-system"]["requires"]:
+        if "setuptools" in requirement:
+            pip_content += requirement
+            pip_content += "\n"
+
     if compare:
-        with open(pip_fname) as pip_fd:
-            return pip_content != pip_fd.read()
-    else:
-        with open(pip_fname, "w") as pip_fd:
-            pip_fd.write(pip_content)
-        return False
+        with pip_path.open() as file:
+            return pip_content != file.read()
+
+    with pip_path.open("w") as file:
+        file.write(pip_content)
+    return False
 
 
 if __name__ == "__main__":
@@ -117,25 +122,20 @@ def main(conda_fname, pip_fname, compare=False):
         action="store_true",
         help="compare whether the two files are equivalent",
     )
-    argparser.add_argument(
-        "--azure", action="store_true", help="show the output in azure-pipelines format"
-    )
     args = argparser.parse_args()
 
-    repo_path = os.path.dirname(os.path.abspath(os.path.dirname(__file__)))
-    res = main(
-        os.path.join(repo_path, "environment.yml"),
-        os.path.join(repo_path, "requirements-dev.txt"),
+    conda_fname = "environment.yml"
+    pip_fname = "requirements-dev.txt"
+    repo_path = pathlib.Path(__file__).parent.parent.absolute()
+    res = generate_pip_from_conda(
+        pathlib.Path(repo_path, conda_fname),
+        pathlib.Path(repo_path, pip_fname),
         compare=args.compare,
     )
     if res:
         msg = (
-            f"`requirements-dev.txt` has to be generated with `{sys.argv[0]}` after "
-            "`environment.yml` is modified.\n"
+            f"`{pip_fname}` has to be generated with `{__file__}` after "
+            f"`{conda_fname}` is modified.\n"
         )
-        if args.azure:
-            msg = (
-                f"##vso[task.logissue type=error;sourcepath=requirements-dev.txt]{msg}"
-            )
         sys.stderr.write(msg)
     sys.exit(res)