STYLE autoupdate pre-commit #49406

MarcoGorelli · 2022-10-31T11:21:54Z

Tomorrow, the autoupdate job will run, and there'll be a couple of updates which'll require some manual fixing:

codespell
cython-lint

The task is:

run pre-commit autoupdate
run pre-commit run cython-lint --all-files and pre-commit run codespell --all-files
fixup the errors. e.g. if there's an error saying 'use_time' defined but unused, remove the definition of use_time from that line
stage, commit, push, open pull request, celebrate

Please refer to the contributing guide, and feel free to ask if you run into anything unexpected (e.g. a false positive from the above tools)

The text was updated successfully, but these errors were encountered:

ramvikrams · 2022-10-31T16:20:43Z

At what time tommorow will the autoupdate happen

MarcoGorelli · 2022-10-31T16:30:22Z

7 am UTC, but this PR can be done at any time

ramvikrams · 2022-10-31T16:34:10Z

I'll start it at 7 am then, can be done at any time after the autoupdate right

MarcoGorelli · 2022-10-31T16:39:48Z

it can be done before, the automated job will fail anyway so ideally we'd take your PR instead of the automated one

ramvikrams · 2022-10-31T16:41:28Z

Oh I'll start with it rightaway then

ramvikrams · 2022-10-31T18:33:50Z

While running the cython i found errors like some word defined but unused
for ex:- 'dts' defined but unused

def _from_value_and_reso(cls, int64_t value, NPY_DATETIMEUNIT reso, tzinfo tz):
        cdef:
            npy_datetimestruct dts
            _TSObject obj = _TSObject()

        if value == NPY_NAT:
            return NaT

So should I remove this dts word

MarcoGorelli · 2022-10-31T19:14:08Z

yeah looks like it's unused in that function, so you can just remove the npy_datetimestruct dts line

ramvikrams · 2022-10-31T20:40:08Z

Traceback (most recent call last):
  File "<frozen runpy>", line 198, in _run_module_as_main
  File "<frozen runpy>", line 88, in _run_code
  File "C:\Users\ramvi\.cache\pre-commit\repogmjseui2\py_env-python3.11\Scripts\cython-lint.EXE\__main__.py", line 7, in <module>
  File "C:\Users\ramvi\.cache\pre-commit\repogmjseui2\py_env-python3.11\Lib\site-packages\cython_lint.py", line 448, in main
    ret |= _main(
           ^^^^^^
  File "C:\Users\ramvi\.cache\pre-commit\repogmjseui2\py_env-python3.11\Lib\site-packages\cython_lint.py", line 308, in _main
    tokens = src_to_tokens(code)
           ^^^^^^
  File "C:\Users\ramvi\.cache\pre-commit\repogmjseui2\py_env-python3.11\Lib\site-packages\cython_lint.py", line 308, in _main
    tokens = src_to_tokens(code)
             ^^^^^^^^^^^^^^^^^^^
  File "C:\Users\ramvi\.cache\pre-commit\repogmjseui2\py_env-python3.11\Lib\site-packages\tokenize_rt.py", line 68, in src_to_tokens
    for tok_type, tok_text, (sline, scol), (eline, ecol), line in gen:
  File "C:\Users\ramvi\AppData\Local\Programs\Python\Python311\Lib\tokenize.py", line 516, in _tokenize
    raise IndentationError(
  File "<tokenize>", line 317
    cdef:
IndentationError: unindent does not match any outer indentation level

Getting this error after running this pre-commit run cython-lint --all-files

MarcoGorelli · 2022-10-31T20:42:48Z

could you please show me the output of git diff upstream/main?

ramvikrams · 2022-10-31T20:45:41Z

diff --git a/.pre-commit-config.yaml b/.pre-commit-config.yaml
index 8ff7526b87..1893f57fc0 100644
--- a/.pre-commit-config.yaml
+++ b/.pre-commit-config.yaml
@@ -18,16 +18,16 @@ repos:
         pass_filenames: true
         require_serial: false
 -   repo: https://github.com/python/black
-    rev: 22.8.0
+    rev: 22.10.0
     hooks:
     -   id: black
 -   repo: https://github.com/codespell-project/codespell
-    rev: v2.2.1
+    rev: v2.2.2
     hooks:
     -   id: codespell
         types_or: [python, rst, markdown]
 -   repo: https://github.com/MarcoGorelli/cython-lint
-    rev: v0.1.8
+    rev: v0.2.1
     hooks:
     -   id: cython-lint
 -   repo: https://github.com/pre-commit/pre-commit-hooks
@@ -60,7 +60,7 @@ repos:
         - flake8-bugbear==22.7.1
         - pandas-dev-flaker==0.5.0
 -   repo: https://github.com/pycqa/pylint
-    rev: v2.15.3
+    rev: v2.15.5
     hooks:
     -   id: pylint
 -   repo: https://github.com/PyCQA/isort
@@ -68,7 +68,7 @@ repos:
     hooks:
     -   id: isort
 -   repo: https://github.com/asottile/pyupgrade
-    rev: v2.38.2
+    rev: v3.2.0
     hooks:
     -   id: pyupgrade
         args: [--py38-plus]
@@ -83,7 +83,7 @@ repos:
         types: [text]  # overwrite types: [rst]
         types_or: [python, rst]
 -   repo: https://github.com/sphinx-contrib/sphinx-lint
-    rev: v0.6.1
+    rev: v0.6.7
     hooks:
     - id: sphinx-lint
 -   repo: https://github.com/asottile/yesqa
diff --git a/pandas/_libs/algos.pyx b/pandas/_libs/algos.pyx
:

Here it is

MarcoGorelli · 2022-10-31T20:47:51Z

I can't see what you've modified in pandas/_libs/algos.pyx. if you open a draft pull request that might make it easier to tell what's going on

ramvikrams · 2022-10-31T20:48:52Z

diff --git a/.pre-commit-config.yaml b/.pre-commit-config.yaml
index 8ff7526b87..1893f57fc0 100644
--- a/.pre-commit-config.yaml
+++ b/.pre-commit-config.yaml
@@ -18,16 +18,16 @@ repos:
         pass_filenames: true
         require_serial: false
 -   repo: https://github.com/python/black
-    rev: 22.8.0
+    rev: 22.10.0
     hooks:
     -   id: black
 -   repo: https://github.com/codespell-project/codespell
-    rev: v2.2.1
+    rev: v2.2.2
     hooks:
     -   id: codespell
         types_or: [python, rst, markdown]
 -   repo: https://github.com/MarcoGorelli/cython-lint
-    rev: v0.1.8
+    rev: v0.2.1
     hooks:
     -   id: cython-lint
 -   repo: https://github.com/pre-commit/pre-commit-hooks
@@ -60,7 +60,7 @@ repos:
         - flake8-bugbear==22.7.1
         - pandas-dev-flaker==0.5.0
 -   repo: https://github.com/pycqa/pylint
-    rev: v2.15.3
+    rev: v2.15.5
     hooks:
     -   id: pylint
 -   repo: https://github.com/PyCQA/isort
@@ -68,7 +68,7 @@ repos:
     hooks:
     -   id: isort
 -   repo: https://github.com/asottile/pyupgrade
-    rev: v2.38.2
+    rev: v3.2.0
     hooks:
     -   id: pyupgrade
         args: [--py38-plus]
@@ -83,7 +83,7 @@ repos:
         types: [text]  # overwrite types: [rst]
         types_or: [python, rst]
 -   repo: https://github.com/sphinx-contrib/sphinx-lint
-    rev: v0.6.1
+    rev: v0.6.7
     hooks:
     - id: sphinx-lint
 -   repo: https://github.com/asottile/yesqa
diff --git a/pandas/_libs/algos.pyx b/pandas/_libs/algos.pyx
index 96c47471aa..587e17e806 100644
--- a/pandas/_libs/algos.pyx
+++ b/pandas/_libs/algos.pyx
@@ -81,26 +81,26 @@ class Infinity:
     """
     Provide a positive Infinity comparison method for ranking.
     """
-    __lt__ = lambda self, other: False
-    __le__ = lambda self, other: isinstance(other, Infinity)
-    __eq__ = lambda self, other: isinstance(other, Infinity)
-    __ne__ = lambda self, other: not isinstance(other, Infinity)
-    __gt__ = lambda self, other: (not isinstance(other, Infinity) and
+    __lt__ = def self, other: False
+    __le__ = def self, other: isinstance(other, Infinity)
+    __eq__ = def self, other: isinstance(other, Infinity)
+    __ne__ = def self, other: not isinstance(other, Infinity)
+    __gt__ = def self, other: (not isinstance(other, Infinity) and
                                   not missing.checknull(other))
-    __ge__ = lambda self, other: not missing.checknull(other)
+    __ge__ = def self, other: not missing.checknull(other)


 class NegInfinity:
     """
     Provide a negative Infinity comparison method for ranking.
     """
-    __lt__ = lambda self, other: (not isinstance(other, NegInfinity) and
+    __lt__ = def self, other: (not isinstance(other, NegInfinity) and
                                   not missing.checknull(other))
-    __le__ = lambda self, other: not missing.checknull(other)
-    __eq__ = lambda self, other: isinstance(other, NegInfinity)
-    __ne__ = lambda self, other: not isinstance(other, NegInfinity)
-    __gt__ = lambda self, other: False
-    __ge__ = lambda self, other: isinstance(other, NegInfinity)
+    __le__ = def self, other: not missing.checknull(other)
+    __eq__ = def self, other: isinstance(other, NegInfinity)
+    __ne__ = def self, other: not isinstance(other, NegInfinity)
+    __gt__ = def self, other: False
+    __ge__ = def self, other: isinstance(other, NegInfinity)


 @cython.wraparound(False)
@@ -321,7 +321,7 @@ def kth_smallest(numeric_t[::1] arr, Py_ssize_t k) -> numeric_t:
 @cython.cdivision(True)
 def nancorr(const float64_t[:, :] mat, bint cov=False, minp=None):
     cdef:
-        Py_ssize_t i, j, xi, yi, N, K
+        Py_ssize_t i, xi, yi, N, K
         bint minpv
         float64_t[:, ::1] result
         ndarray[uint8_t, ndim=2] mask
@@ -377,7 +377,7 @@ def nancorr(const float64_t[:, :] mat, bint cov=False, minp=None):
 @cython.wraparound(False)
 def nancorr_spearman(ndarray[float64_t, ndim=2] mat, Py_ssize_t minp=1) -> ndarray:
     cdef:
-        Py_ssize_t i, j, xi, yi, N, K
+        Py_ssize_t i, xi, yi, N, K
         ndarray[float64_t, ndim=2] result
         ndarray[float64_t, ndim=2] ranked_mat
         ndarray[float64_t, ndim=1] rankedx, rankedy
@@ -746,7 +746,8 @@ def is_monotonic(ndarray[numeric_object_t, ndim=1] arr, bint timelike):
     n = len(arr)

     if n == 1:
-        if arr[0] != arr[0] or (numeric_object_t is int64_t and timelike and arr[0] == NPY_NAT):
+        if arr[0] != arr[0] or (numeric_object_t is int64_t and timelike and 
+                                arr[0] == NPY_NAT):
             # single value is NaN
             return False, False, True
         else:
diff --git a/pandas/_libs/groupby.pyx b/pandas/_libs/groupby.pyx
index f798655e9d..af2877b837 100644
--- a/pandas/_libs/groupby.pyx
+++ b/pandas/_libs/groupby.pyx
@@ -265,7 +265,7 @@ def group_cumprod(
     This method modifies the `out` parameter, rather than returning an object.
     """
     cdef:
-        Py_ssize_t i, j, N, K, size
+        Py_ssize_t i, j, N, K, 
         int64float_t val, na_val
         int64float_t[:, ::1] accum
         intp_t lab
@@ -356,7 +356,7 @@ def group_cumsum(
     This method modifies the `out` parameter, rather than returning an object.
     """
     cdef:
-        Py_ssize_t i, j, N, K, size
+        Py_ssize_t i, j, N, K, 
         int64float_t val, y, t, na_val
         int64float_t[:, ::1] accum, compensation
         uint8_t[:, ::1] accum_mask
@@ -441,7 +441,7 @@ def group_shift_indexer(
     int periods,
 ) -> None:
     cdef:
-        Py_ssize_t N, i, j, ii, lab
+        Py_ssize_t N, i, ii, lab
         int offset = 0, sign
         int64_t idxer, idxer_slot
         int64_t[::1] label_seen = np.zeros(ngroups, dtype=np.int64)
@@ -744,7 +744,7 @@ def group_sum(
                     if uses_mask:
                         isna_entry = mask[i, j]
                     elif (sum_t is float32_t or sum_t is float64_t
-                        or sum_t is complex64_t or sum_t is complex64_t):
+                          or sum_t is complex64_t or sum_t is complex64_t):
                         # avoid warnings because of equality comparison
                         isna_entry = not val == val
                     elif sum_t is int64_t and is_datetimelike and val == NPY_NAT:
@@ -771,7 +771,7 @@ def group_sum(
                         if uses_mask:
                             result_mask[i, j] = True
                         elif (sum_t is float32_t or sum_t is float64_t
-                            or sum_t is complex64_t or sum_t is complex64_t):
+                              or sum_t is complex64_t or sum_t is complex64_t):
                             out[i, j] = NAN
                         elif sum_t is int64_t:
                             out[i, j] = NPY_NAT
@@ -799,7 +799,7 @@ def group_prod(
     """
     cdef:
         Py_ssize_t i, j, N, K, lab, ncounts = len(counts)
-        int64float_t val, count
+        int64float_t val, 
         int64float_t[:, ::1] prodx
         int64_t[:, ::1] nobs
         Py_ssize_t len_values = len(values), len_labels = len(labels)
@@ -872,7 +872,7 @@ def group_var(
         floating[:, ::1] mean
         int64_t[:, ::1] nobs
         Py_ssize_t len_values = len(values), len_labels = len(labels)
-        bint isna_entry, uses_mask = not mask is None
+        bint isna_entry, uses_mask = is not mask is None

     assert min_count == -1, "'min_count' only used in sum and prod"

@@ -969,7 +969,7 @@ def group_mean(
         mean_t[:, ::1] sumx, compensation
         int64_t[:, ::1] nobs
         Py_ssize_t len_values = len(values), len_labels = len(labels)
-        bint isna_entry, uses_mask = not mask is None
+        bint isna_entry, uses_mask = is not mask is None

     assert min_count == -1, "'min_count' only used in sum and prod"

@@ -1042,10 +1042,10 @@ def group_ohlc(
     Only aggregates on axis=0
     """
     cdef:
-        Py_ssize_t i, j, N, K, lab
+        Py_ssize_t i, N, K, lab
         int64float_t val
         uint8_t[::1] first_element_set
-        bint isna_entry, uses_mask = not mask is None
+        bint isna_entry, uses_mask = is not mask is None

     assert min_count == -1, "'min_count' only used in sum and prod"

@@ -1240,7 +1240,8 @@ cdef inline bint _treat_as_na(numeric_object_t val, bint is_datetimelike) nogil:
         return False


-cdef numeric_object_t _get_min_or_max(numeric_object_t val, bint compute_max, bint is_datetimelike):
+cdef numeric_object_t _get_min_or_max(numeric_object_t val, bint compute_max, 
+                                      bint is_datetimelike):
     """
     Find either the min or the max supported by numeric_object_t; 'val' is a
     placeholder to effectively make numeric_object_t an argument.
@@ -1366,7 +1367,8 @@ def group_last(
                         #  set a placeholder value in out[i, j].
                         if uses_mask:
                             result_mask[i, j] = True
-                        elif numeric_object_t is float32_t or numeric_object_t is float64_t:
+                        elif numeric_object_t is float32_t or numeric_object_t 
+                            is float64_t:
                             out[i, j] = NAN
                         elif numeric_object_t is int64_t:
                             # Per above, this is a placeholder in
@@ -1486,7 +1488,8 @@ def group_nth(
                             #  it was initialized with np.empty. Also ensures
                             #  we can downcast out if appropriate.
                             out[i, j] = 0
-                        elif numeric_object_t is float32_t or numeric_object_t is float64_t:
+                        elif numeric_object_t is float32_t or numeric_object_t 
+                            is float64_t:
                             out[i, j] = NAN
                         elif numeric_object_t is int64_t:
                             # Per above, this is a placeholder in
diff --git a/pandas/_libs/internals.pyx b/pandas/_libs/internals.pyx
index 1a98633908..747f57e6ba 100644
--- a/pandas/_libs/internals.pyx
+++ b/pandas/_libs/internals.pyx
@@ -133,7 +133,7 @@ cdef class BlockPlacement:
     @property
     def as_array(self) -> np.ndarray:
         cdef:
-            Py_ssize_t start, stop, end, _
+            Py_ssize_t start, stop, _

         if not self._has_array:
             start, stop, step, _ = slice_get_indices_ex(self._as_slice)
@@ -259,7 +259,6 @@ cdef class BlockPlacement:
         """
         cdef:
             slice slc = self._ensure_has_slice()
-            slice new_slice
             ndarray[intp_t, ndim=1] new_placement

         if slc is not None and slc.step == 1:
diff --git a/pandas/_libs/join.pyx b/pandas/_libs/join.pyx
index e574aa10f6..1f2d717cab 100644
--- a/pandas/_libs/join.pyx
+++ b/pandas/_libs/join.pyx
@@ -275,7 +275,7 @@ def left_join_indexer_unique(
     cdef:
         Py_ssize_t i, j, nleft, nright
         ndarray[intp_t] indexer
-        numeric_object_t lval, rval
+        numeric_object_t, rval

     i = 0
     j = 0
@@ -324,7 +324,7 @@ def left_join_indexer(ndarray[numeric_object_t] left, ndarray[numeric_object_t]
     is non-unique (if both were unique we'd use left_join_indexer_unique).
     """
     cdef:
-        Py_ssize_t i, j, k, nright, nleft, count
+        Py_ssize_t i, j, nright, nleft, count
         numeric_object_t lval, rval
         ndarray[intp_t] lindexer, rindexer
         ndarray[numeric_object_t] result
@@ -434,7 +434,7 @@ def inner_join_indexer(ndarray[numeric_object_t] left, ndarray[numeric_object_t]
     Both left and right are monotonic increasing but not necessarily unique.
     """
     cdef:
-        Py_ssize_t i, j, k, nright, nleft, count
+        Py_ssize_t i, j, nright, nleft, count
         numeric_object_t lval, rval
         ndarray[intp_t] lindexer, rindexer
         ndarray[numeric_object_t] result
diff --git a/pandas/_libs/lib.pyx b/pandas/_libs/lib.pyx
index 188b531b2b..914b33c01e 100644
--- a/pandas/_libs/lib.pyx
+++ b/pandas/_libs/lib.pyx
@@ -621,6 +621,7 @@ ctypedef fused ndarr_object:

 # TODO: get rid of this in StringArray and modify
 #  and go through ensure_string_array instead
+
 @cython.wraparound(False)
 @cython.boundscheck(False)
 def convert_nans_to_NA(ndarr_object arr) -> ndarray:
@@ -765,9 +766,9 @@ def generate_bins_dt64(ndarray[int64_t, ndim=1] values, const int64_t[:] binner,
     Int64 (datetime64) version of generic python version in ``groupby.py``.
     """
     cdef:
-        Py_ssize_t lenidx, lenbin, i, j, bc, vc
+        Py_ssize_t lenidx, lenbin, i, j, bc, 
         ndarray[int64_t, ndim=1] bins
-        int64_t l_bin, r_bin, nat_count
+        int64_t, r_bin, nat_count
         bint right_closed = closed == 'right'

     nat_count = 0
@@ -2215,11 +2216,16 @@ def maybe_convert_numeric(
         int status, maybe_int
         Py_ssize_t i, n = values.size
         Seen seen = Seen(coerce_numeric)
-        ndarray[float64_t, ndim=1] floats = cnp.PyArray_EMPTY(1, values.shape, cnp.NPY_FLOAT64, 0)
-        ndarray[complex128_t, ndim=1] complexes = cnp.PyArray_EMPTY(1, values.shape, cnp.NPY_COMPLEX128, 0)
-        ndarray[int64_t, ndim=1] ints = cnp.PyArray_EMPTY(1, values.shape, cnp.NPY_INT64, 0)
-        ndarray[uint64_t, ndim=1] uints = cnp.PyArray_EMPTY(1, values.shape, cnp.NPY_UINT64, 0)
-        ndarray[uint8_t, ndim=1] bools = cnp.PyArray_EMPTY(1, values.shape, cnp.NPY_UINT8, 0)
+        ndarray[float64_t, ndim=1] floats = cnp.PyArray_EMPTY(1, values.shape, 
+                                                              cnp.NPY_FLOAT64, 0)
+        ndarray[complex128_t, ndim=1] complexes = cnp.PyArray_EMPTY(1, values.shape, 
+                                                                    cnp.NPY_COMPLEX128, 0)
+        ndarray[int64_t, ndim=1] ints = cnp.PyArray_EMPTY(1, values.shape,  
+                                                          cnp.NPY_INT64, 0)
+        ndarray[uint64_t, ndim=1] uints = cnp.PyArray_EMPTY(1, values.shape, 
+                                                            cnp.NPY_UINT64, 0)
+        ndarray[uint8_t, ndim=1] bools = cnp.PyArray_EMPTY(1, values.shape,  
+                                                           cnp.NPY_UINT8, 0)
         ndarray[uint8_t, ndim=1] mask = np.zeros(n, dtype="u1")
         float64_t fval
         bint allow_null_in_int = convert_to_masked_nullable
@@ -2298,7 +2304,7 @@ def maybe_convert_numeric(
             seen.float_ = True
         else:
             try:
-                status = floatify(val, &fval, &maybe_int)
+                # status = floatify(val, &fval, &maybe_int)

                 if fval in na_values:
                     seen.saw_null()
@@ -2437,7 +2443,7 @@ def maybe_convert_objects(ndarray[object] objects,
         int64_t[::1] itimedeltas
         Seen seen = Seen()
         object val
-        float64_t fval, fnan = np.nan
+        float64_t, fnan = np.nan

     n = len(objects)

@@ -2917,7 +2923,7 @@ def to_object_array(rows: object, min_width: int = 0) -> ndarray:

 def tuples_to_object_array(ndarray[object] tuples):
     cdef:
-        Py_ssize_t i, j, n, k, tmp
+        Py_ssize_t i, j, n, k, 
         ndarray[object, ndim=2] result
         tuple tup

@@ -3045,7 +3051,8 @@ cpdef ndarray eq_NA_compat(ndarray[object] arr, object key):
     key is assumed to have `not isna(key)`
     """
     cdef:
-        ndarray[uint8_t, cast=True] result = cnp.PyArray_EMPTY(arr.ndim, arr.shape, cnp.NPY_BOOL, 0)
+        ndarray[uint8_t, cast=True] result = cnp.PyArray_EMPTY(arr.ndim, arr.shape, 
+                                                               cnp.NPY_BOOL, 0)
         Py_ssize_t i
         object item

diff --git a/pandas/_libs/testing.pyx b/pandas/_libs/testing.pyx
index 679cde9932..678ed54fdc 100644
--- a/pandas/_libs/testing.pyx
+++ b/pandas/_libs/testing.pyx
@@ -161,13 +161,15 @@ cpdef assert_almost_equal(a, b,
                 is_unequal = True
                 diff += 1
                 if not first_diff:
-                    first_diff = f"At positional index {i}, first diff: {a[i]} != {b[i]}"
+                    first_diff = f"At positional index {i}, 
+                                  first diff: {a[i]} != {b[i]}"

         if is_unequal:
             from pandas._testing import raise_assert_detail
             msg = (f"{obj} values are different "
                    f"({np.round(diff * 100.0 / na, 5)} %)")
-            raise_assert_detail(obj, msg, lobj, robj, first_diff=first_diff, index_values=index_values)
+            raise_assert_detail(obj, msg, lobj, robj, 
+                                first_diff=first_diff, index_values=index_values)

         return True

diff --git a/pandas/_libs/tslib.pyx b/pandas/_libs/tslib.pyx
index d7c0c91332..699c0255dc 100644
--- a/pandas/_libs/tslib.pyx
+++ b/pandas/_libs/tslib.pyx
@@ -260,7 +260,7 @@ def array_with_unit_to_datetime(
     tz : parsed timezone offset or None
     """
     cdef:
-        Py_ssize_t i, j, n=len(values)
+        Py_ssize_t i, n=len(values)
         int64_t mult
         int prec = 0
         ndarray[float64_t] fvalues
@@ -417,6 +417,7 @@ def array_with_unit_to_datetime(

     return oresult, tz

+
 @cython.wraparound(False)
 @cython.boundscheck(False)
 def first_non_null(values: ndarray) -> int:
@@ -424,7 +425,6 @@ def first_non_null(values: ndarray) -> int:
     cdef:
         Py_ssize_t n = len(values)
         Py_ssize_t i
-        int result
     for i in range(n):
         val = values[i]
         if checknull_with_nat_and_na(val):
@@ -435,6 +435,7 @@ def first_non_null(values: ndarray) -> int:
     else:
         return -1

+
 @cython.wraparound(False)
 @cython.boundscheck(False)
 cpdef array_to_datetime(
@@ -609,7 +610,8 @@ cpdef array_to_datetime(
                                 continue
                             elif is_raise:
                                 raise ValueError(
-                                    f"time data \"{val}\" at position {i} doesn't match format specified"
+                                    f"time data \"{val}\" at position {i} doesn't 
+                                      match format specified"
                                 )
                             return values, tz_out

@@ -625,7 +627,8 @@ cpdef array_to_datetime(
                             if is_coerce:
                                 iresult[i] = NPY_NAT
                                 continue
-                            raise TypeError(f"invalid string coercion to datetime for \"{val}\" at position {i}")
+                            raise TypeError(f"invalid string coercion to datetime for \"{val}\" 
+                                             at position {i}")

                         if tz is not None:
                             seen_datetime_offset = True
diff --git a/pandas/_libs/tslibs/dtypes.pyx b/pandas/_libs/tslibs/dtypes.pyx
index 9478137429..0693a142ec 100644
--- a/pandas/_libs/tslibs/dtypes.pyx
+++ b/pandas/_libs/tslibs/dtypes.pyx
@@ -396,7 +396,8 @@ cdef NPY_DATETIMEUNIT freq_group_code_to_npy_unit(int freq) nogil:


 # TODO: use in _matplotlib.converter?
-cpdef int64_t periods_per_day(NPY_DATETIMEUNIT reso=NPY_DATETIMEUNIT.NPY_FR_ns) except? -1:
+cpdef int64_t periods_per_day(NPY_DATETIMEUNIT reso=NPY_DATETIMEUNIT.NPY_FR_ns) 
+    except? -1:
     """
     How many of the given time units fit into a single day?
     """
diff --git a/pandas/_libs/tslibs/fields.pyx b/pandas/_libs/tslibs/fields.pyx
index 3c7406d231..e8f256d1dc 100644
--- a/pandas/_libs/tslibs/fields.pyx
+++ b/pandas/_libs/tslibs/fields.pyx
@@ -325,7 +325,8 @@ def get_start_end_field(

 @cython.wraparound(False)
 @cython.boundscheck(False)
-def get_date_field(const int64_t[:] dtindex, str field, NPY_DATETIMEUNIT reso=NPY_FR_ns):
+def get_date_field(const int64_t[:] dtindex, str field, NPY_DATETIMEUNIT  
+                   reso=NPY_FR_ns):
     """
     Given a int64-based datetime index, extract the year, month, etc.,
     field and return an array of these values.
diff --git a/pandas/_libs/tslibs/nattype.pyx b/pandas/_libs/tslibs/nattype.pyx
index 79299ec38e..a51f3a4b7b 100644
--- a/pandas/_libs/tslibs/nattype.pyx
+++ b/pandas/_libs/tslibs/nattype.pyx
@@ -204,7 +204,8 @@ cdef class _NaT(datetime):
                     return result

                 # __rsub__ logic here
-                # TODO(cython3): remove this, move above code out of ``if not is_rsub`` block
+                # TODO(cython3): remove this, move above code out of   
+                # ``if not is_rsub`` block
                 # timedelta64 - NaT we have to treat NaT as timedelta64
                 #  for this to be meaningful, and the result is timedelta64
                 result = np.empty(other.shape, dtype="timedelta64[ns]")
@@ -240,7 +241,8 @@ cdef class _NaT(datetime):
                 result = np.empty(other.shape, dtype="timedelta64[ns]")
                 result.fill("NaT")
                 return result
-        # other cases are same, swap operands is allowed even though we subtract because this is NaT
+        #  other cases are same, swap operands is allowed even though we subtract 
+        # because this is NaT  
         return self.__sub__(other)

     def __pos__(self):
@@ -1201,6 +1203,7 @@ default 'raise'
         NaT
         """,
     )
+
     @property
     def tz(self) -> None:
         return None
diff --git a/pandas/_libs/tslibs/np_datetime.pyx b/pandas/_libs/tslibs/np_datetime.pyx
index 07872050dc..bf5cdd4a0d 100644
--- a/pandas/_libs/tslibs/np_datetime.pyx
+++ b/pandas/_libs/tslibs/np_datetime.pyx
@@ -46,7 +46,7 @@ cdef extern from "src/datetime/np_datetime.h":
     npy_datetimestruct _S_MIN_DTS, _S_MAX_DTS
     npy_datetimestruct _M_MIN_DTS, _M_MAX_DTS

-    PyArray_DatetimeMetaData get_datetime_metadata_from_dtype(cnp.PyArray_Descr *dtype);
+    PyArray_DatetimeMetaData get_datetime_metadata_from_dtype(cnp.PyArray_Descr *dtype)

 cdef extern from "src/datetime/np_datetime_strings.h":
     int parse_iso_8601_datetime(const char *str, int len, int want_exc,
@@ -171,7 +171,8 @@ class OutOfBoundsTimedelta(ValueError):
     pass
 

-cdef get_implementation_bounds(NPY_DATETIMEUNIT reso, npy_datetimestruct *lower, npy_datetimestruct *upper):
+cdef get_implementation_bounds(NPY_DATETIMEUNIT reso, npy_datetimestruct *lower, 
+                               npy_datetimestruct *upper):
     if reso == NPY_FR_ns:
         upper[0] = _NS_MAX_DTS
         lower[0] = _NS_MIN_DTS
@@ -420,7 +421,6 @@ def compare_mismatched_resolutions(ndarray left, ndarray right, op):
         Py_ssize_t i, N = left.size
         npy_datetimestruct ldts, rdts

-
     for i in range(N):
         # Analogous to: lval = lvalues[i]
         lval = (<int64_t*>cnp.PyArray_MultiIter_DATA(mi, 1))[0]
@@ -511,7 +511,8 @@ cdef ndarray astype_round_check(


 @cython.overflowcheck(True)
-cdef int64_t get_conversion_factor(NPY_DATETIMEUNIT from_unit, NPY_DATETIMEUNIT to_unit) except? -1:
+cdef int64_t get_conversion_factor(NPY_DATETIMEUNIT from_unit, NPY_DATETIMEUNIT to_unit)
+    except? -1:
     """
     Find the factor by which we need to multiply to convert from from_unit to to_unit.
     """
diff --git a/pandas/_libs/tslibs/offsets.pyx b/pandas/_libs/tslibs/offsets.pyx
index 37b87f9297..700d8574cf 100644
--- a/pandas/_libs/tslibs/offsets.pyx
+++ b/pandas/_libs/tslibs/offsets.pyx
@@ -2268,7 +2268,8 @@ cdef class QuarterOffset(SingleConstructorOffset):
     def _apply_array(self, dtarr):
         reso = get_unit_from_dtype(dtarr.dtype)
         shifted = shift_quarters(
-            dtarr.view("i8"), self.n, self.startingMonth, self._day_opt, modby=3, reso=reso
+            dtarr.view("i8"), self.n, self.startingMonth, self._day_opt, modby=3, 
+            reso=reso
         )
         return shifted

@@ -2548,7 +2549,8 @@ cdef class SemiMonthOffset(SingleConstructorOffset):
             ndarray i8other = dtarr.view("i8")
             Py_ssize_t i, count = dtarr.size
             int64_t val, res_val
-            ndarray out = cnp.PyArray_EMPTY(i8other.ndim, i8other.shape, cnp.NPY_INT64, 0)
+            ndarray out = cnp.PyArray_EMPTY(i8other.ndim, i8other.shape, cnp.NPY_INT64,
+                                            0)
             npy_datetimestruct dts
             int months, to_day, nadj, n = self.n
             int days_in_month, day, anchor_dom = self.day_of_month
@@ -2756,7 +2758,8 @@ cdef class Week(SingleConstructorOffset):
         cdef:
             Py_ssize_t i, count = i8other.size
             int64_t val, res_val
-            ndarray out = cnp.PyArray_EMPTY(i8other.ndim, i8other.shape, cnp.NPY_INT64, 0)
+            ndarray out = cnp.PyArray_EMPTY(i8other.ndim, i8other.shape, cnp.NPY_INT64,
+                                            0)
             npy_datetimestruct dts
             int wday, days, weeks, n = self.n
             int anchor_weekday = self.weekday
diff --git a/pandas/_libs/tslibs/parsing.pyx b/pandas/_libs/tslibs/parsing.pyx
index 1312124cfb..c65d678c08 100644
--- a/pandas/_libs/tslibs/parsing.pyx
+++ b/pandas/_libs/tslibs/parsing.pyx
@@ -418,7 +418,8 @@ cdef parse_datetime_string_with_reso(
             from pandas import Timestamp
             parsed = Timestamp(date_string)
         else:
-            parsed = datetime(dts.year, dts.month, dts.day, dts.hour, dts.min, dts.sec, dts.us)
+            parsed = datetime(dts.year, dts.month, dts.day, dts.hour, dts.min, dts.sec, 
+                              dts.us)
         reso = {
             NPY_DATETIMEUNIT.NPY_FR_Y: "year",
             NPY_DATETIMEUNIT.NPY_FR_M: "month",
@@ -717,7 +718,7 @@ def try_parse_dates(
             date = datetime.now()
             default = datetime(date.year, date.month, 1)

-        parse_date = lambda x: du_parse(x, dayfirst=dayfirst, default=default)
+        parse_date = def x: du_parse(x, dayfirst=dayfirst, default=default)

         # EAFP here
         try:
@@ -1050,6 +1051,7 @@ def guess_datetime_format(dt_str: str, bint dayfirst=False) -> str | None:
     else:
         return None

+
 cdef str _fill_token(token: str, padding: int):
     cdef str token_filled
     if '.' not in token:
@@ -1064,6 +1066,7 @@ cdef str _fill_token(token: str, padding: int):
         token_filled = f'{seconds}.{nanoseconds}'
     return token_filled

+
 @cython.wraparound(False)
 @cython.boundscheck(False)
 cdef inline object convert_to_unicode(object item, bint keep_trivial_numbers):
diff --git a/pandas/_libs/tslibs/period.pyx b/pandas/_libs/tslibs/period.pyx
index be6f877912..d50fd9ade1 100644
--- a/pandas/_libs/tslibs/period.pyx
+++ b/pandas/_libs/tslibs/period.pyx
@@ -1053,7 +1053,8 @@ def period_asfreq_arr(ndarray[int64_t] arr, int freq1, int freq2, bint end):
     cdef:
         Py_ssize_t n = len(arr)
         Py_ssize_t increment = arr.strides[0] // 8
-        ndarray[int64_t] result = cnp.PyArray_EMPTY(arr.ndim, arr.shape, cnp.NPY_INT64, 0)
+        ndarray[int64_t] result = cnp.PyArray_EMPTY(arr.ndim, arr.shape, cnp.NPY_INT64,  
+                                                    0)

     _period_asfreq(
         <int64_t*>cnp.PyArray_DATA(arr),
@@ -1362,7 +1363,6 @@ def get_period_field_arr(str field, const int64_t[:] arr, int freq):
     cdef:
         Py_ssize_t i, sz
         int64_t[::1] out
-        accessor f

     func = _get_accessor_func(field)
     if func is NULL:
@@ -1439,7 +1439,7 @@ def extract_ordinals(ndarray values, freq) -> np.ndarray:
         Py_ssize_t i, n = values.size
         int64_t ordinal
         ndarray ordinals = cnp.PyArray_EMPTY(values.ndim, values.shape, cnp.NPY_INT64, 0)
-        cnp.broadcast mi = cnp.PyArray_MultiIterNew2(ordinals, values)
+        cnp.broadcast mi = cnp.PyArray_MultiIterNew2(ordinals, values) 
         object p

     if values.descr.type_num != cnp.NPY_OBJECT:
@@ -2478,7 +2478,8 @@ class Period(_Period):
         the start or the end of the period, but rather the entire period itself.
     freq : str, default None
         One of pandas period strings or corresponding objects. Accepted
-        strings are listed in the :ref:`offset alias section <timeseries.offset_aliases>` in the user docs.
+        strings are listed in the :ref:`offset alias section 
+        <timeseries.offset_aliases>` in the user docs. 
     ordinal : int, default None
         The period offset from the proleptic Gregorian epoch.
     year : int, default None
@@ -2511,7 +2512,6 @@ class Period(_Period):
         # ('T', 5) but may be passed in as a string like '5T'

         # ordinal is the period offset from the gregorian proleptic epoch
-        cdef _Period self

         if freq is not None:
             freq = cls._maybe_convert_freq(freq)
diff --git a/pandas/_libs/tslibs/strptime.pyx b/pandas/_libs/tslibs/strptime.pyx
index 6287c2fbc5..f540ad19c4 100644
--- a/pandas/_libs/tslibs/strptime.pyx
+++ b/pandas/_libs/tslibs/strptime.pyx
@@ -75,7 +75,6 @@ def array_strptime(ndarray[object] values, str fmt, bint exact=True, errors='rai
         int iso_week, iso_year
         int64_t us, ns
         object val, group_key, ampm, found, timezone
-        dict found_key
         bint is_raise = errors=='raise'
         bint is_ignore = errors=='ignore'
         bint is_coerce = errors=='coerce'
diff --git a/pandas/_libs/tslibs/timedeltas.pyx b/pandas/_libs/tslibs/timedeltas.pyx
index f3de67b705..62b30855a9 100644
--- a/pandas/_libs/tslibs/timedeltas.pyx
+++ b/pandas/_libs/tslibs/timedeltas.pyx
@@ -176,7 +176,8 @@ def ints_to_pytimedelta(ndarray m8values, box=False):
         #  `it` iterates C-order as well, so the iteration matches
         #  See discussion at
         #  github.com/pandas-dev/pandas/pull/46886#discussion_r860261305
-        ndarray result = cnp.PyArray_EMPTY(m8values.ndim, m8values.shape, cnp.NPY_OBJECT, 0)
+        ndarray result = cnp.PyArray_EMPTY(m8values.ndim, m8values.shape, 
+                                           cnp.NPY_OBJECT, 0)
         object[::1] res_flat = result.ravel()     # should NOT be a copy

         ndarray arr = m8values.view("i8")
@@ -468,7 +469,8 @@ cdef inline int64_t _item_to_timedelta64_fastpath(object item) except? -1:
         return parse_timedelta_string(item)


-cdef inline int64_t _item_to_timedelta64(object item, str parsed_unit, str errors) except? -1:
+cdef inline int64_t _item_to_timedelta64(object item, str parsed_unit, str errors) 
+    except? -1:
     """
     See array_to_timedelta64.
     """
@@ -967,7 +969,6 @@ cdef _timedelta_from_value_and_reso(int64_t value, NPY_DATETIMEUNIT reso):
             "Only resolutions 's', 'ms', 'us', 'ns' are supported."
         )

-
     td_base.value = value
     td_base._is_populated = 0
     td_base._creso = reso
@@ -1570,7 +1571,7 @@ class Timedelta(_Timedelta):
                            "milliseconds", "microseconds", "nanoseconds"}

     def __new__(cls, object value=_no_input, unit=None, **kwargs):
-        cdef _Timedelta td_base
+        cdef _Timedelta 

         if value is _no_input:
             if not len(kwargs):
@@ -1625,7 +1626,8 @@ class Timedelta(_Timedelta):
             if len(kwargs):
                 # GH#48898
                 raise ValueError(
-                    "Cannot pass both a Timedelta input and timedelta keyword arguments, got "
+                    "Cannot pass both a Timedelta input and timedelta keyword 
+                     arguments, got "
                     f"{list(kwargs.keys())}"
                 )
             return value
@@ -1712,7 +1714,7 @@ class Timedelta(_Timedelta):
     @cython.cdivision(True)
     def _round(self, freq, mode):
         cdef:
-            int64_t result, unit, remainder
+            int64_t result, unit,
             ndarray[int64_t] arr

         from pandas._libs.tslibs.offsets import to_offset
@@ -1802,7 +1804,7 @@ class Timedelta(_Timedelta):

     def __truediv__(self, other):
         cdef:
-            int64_t new_value
+            int64_t 

         if _should_cast_to_timedelta(other):
             # We interpret NaT as timedelta64("NaT")
diff --git a/pandas/_libs/tslibs/timestamps.pyx b/pandas/_libs/tslibs/timestamps.pyx
index 3c3bb8496a..95fc683ed4 100644
--- a/pandas/_libs/tslibs/timestamps.pyx
+++ b/pandas/_libs/tslibs/timestamps.pyx
@@ -267,7 +267,6 @@ cdef class _Timestamp(ABCTimestamp):
     @classmethod
     def _from_value_and_reso(cls, int64_t value, NPY_DATETIMEUNIT reso, tzinfo tz):
         cdef:
-            npy_datetimestruct dts
             _TSObject obj = _TSObject()

         if value == NPY_NAT:
@@ -294,8 +293,8 @@ cdef class _Timestamp(ABCTimestamp):
         # This is herely mainly so we can incrementally implement non-nano
         #  (e.g. only tznaive at first)
         cdef:
-            npy_datetimestruct dts
-            int64_t value
+            npy_datetimestruct 
+            int64_t value 
             NPY_DATETIMEUNIT reso

         reso = get_datetime64_unit(dt64)
@@ -317,7 +316,6 @@ cdef class _Timestamp(ABCTimestamp):
     def __richcmp__(_Timestamp self, object other, int op):
         cdef:
             _Timestamp ots
-            int ndim

         if isinstance(other, _Timestamp):
             ots = other
@@ -1532,7 +1530,7 @@ class Timestamp(_Timestamp):
                 if (is_integer_object(tz)
                     and is_integer_object(ts_input)
                     and is_integer_object(freq)
-                ):
+                     ):
                     # GH#31929 e.g. Timestamp(2019, 3, 4, 5, 6, tzinfo=foo)
                     # TODO(GH#45307): this will still be fragile to
                     #  mixed-and-matched positional/keyword arguments
@@ -1675,7 +1673,8 @@ class Timestamp(_Timestamp):
             if not is_offset_object(freq):
                 freq = to_offset(freq)

-        return create_timestamp_from_ts(ts.value, ts.dts, ts.tzinfo, freq, ts.fold, ts.creso)
+        return create_timestamp_from_ts(ts.value, ts.dts, ts.tzinfo, freq, ts.fold,
+                                        ts.creso)

     def _round(self, freq, mode, ambiguous='raise', nonexistent='raise'):
         cdef:
diff --git a/pandas/_libs/tslibs/tzconversion.pyx b/pandas/_libs/tslibs/tzconversion.pyx
index e2812178a2..030113df86 100644
--- a/pandas/_libs/tslibs/tzconversion.pyx
+++ b/pandas/_libs/tslibs/tzconversion.pyx
@@ -224,14 +224,13 @@ timedelta-like}
     """
     cdef:
         ndarray[uint8_t, cast=True] ambiguous_array
-        Py_ssize_t i, idx, pos, n = vals.shape[0]
-        Py_ssize_t delta_idx_offset, delta_idx, pos_left, pos_right
+        Py_ssize_t i, n = vals.shape[0]
+        Py_ssize_t delta_idx_offset, delta_idx,  
         int64_t v, left, right, val, new_local, remaining_mins
         int64_t first_delta, delta
         int64_t shift_delta = 0
         ndarray[int64_t] result_a, result_b, dst_hours
-        int64_t[::1] result
-        npy_datetimestruct dts
+        int64_t[::1] result 
         bint infer_dst = False, is_dst = False, fill = False
         bint shift_forward = False, shift_backward = False
         bint fill_nonexist = False
diff --git a/pandas/_libs/tslibs/vectorized.pyx b/pandas/_libs/tslibs/vectorized.pyx
index 6a6b156af3..0a16cf38ee 100644
--- a/pandas/_libs/tslibs/vectorized.pyx
+++ b/pandas/_libs/tslibs/vectorized.pyx
@@ -155,7 +155,7 @@ def ints_to_pydatetime(
     elif box == "timestamp":
         use_ts = True
     elif box == "time":
-        use_time = True
+        # use_time = True
     elif box == "datetime":
         use_pydt = True
     else:
diff --git a/pandas/_libs/window/aggregations.pyx b/pandas/_libs/window/aggregations.pyx
index 68c05f2bb2..8e08d63477 100644
--- a/pandas/_libs/window/aggregations.pyx
+++ b/pandas/_libs/window/aggregations.pyx
@@ -172,7 +172,8 @@ def roll_sum(const float64_t[:] values, ndarray[int64_t] start,
                     add_sum(values[j], &nobs, &sum_x, &compensation_add,
                             &num_consecutive_same_value, &prev_value)

-            output[i] = calc_sum(minp, nobs, sum_x, num_consecutive_same_value, prev_value)
+            output[i] = calc_sum(minp, nobs, sum_x, num_consecutive_same_value, 
+                                 prev_value)

             if not is_monotonic_increasing_bounds:
                 nobs = 0
@@ -296,7 +297,8 @@ def roll_mean(const float64_t[:] values, ndarray[int64_t] start,
                     add_mean(val, &nobs, &sum_x, &neg_ct, &compensation_add,
                              &num_consecutive_same_value, &prev_value)

-            output[i] = calc_mean(minp, nobs, neg_ct, sum_x, num_consecutive_same_value, prev_value)
+            output[i] = calc_mean(minp, nobs, neg_ct, sum_x, num_consecutive_same_value, 
+                                  prev_value)

             if not is_monotonic_increasing_bounds:
                 nobs = 0
@@ -310,7 +312,8 @@ def roll_mean(const float64_t[:] values, ndarray[int64_t] start,


 cdef inline float64_t calc_var(int64_t minp, int ddof, float64_t nobs,
-                               float64_t ssqdm_x, int64_t num_consecutive_same_value) nogil:
+                               float64_t ssqdm_x, int64_t num_consecutive_same_value) 
+                               nogil:
     cdef:
         float64_t result

@@ -330,7 +333,8 @@ cdef inline float64_t calc_var(int64_t minp, int ddof, float64_t nobs,

 cdef inline void add_var(float64_t val, float64_t *nobs, float64_t *mean_x,
                          float64_t *ssqdm_x, float64_t *compensation,
-                         int64_t *num_consecutive_same_value, float64_t *prev_value) nogil:
+                         int64_t *num_consecutive_same_value, float64_t *prev_value) 
+                         nogil:
     """ add a value from the var calc """
     cdef:
         float64_t delta, prev_mean, y, t
@@ -566,7 +570,7 @@ def roll_skew(ndarray[float64_t] values, ndarray[int64_t] start,
               ndarray[int64_t] end, int64_t minp) -> np.ndarray:
     cdef:
         Py_ssize_t i, j
-        float64_t val, prev, min_val, mean_val, sum_val = 0
+        float64_t val, min_val, mean_val, sum_val = 0
         float64_t compensation_xxx_add, compensation_xxx_remove
         float64_t compensation_xx_add, compensation_xx_remove
         float64_t compensation_x_add, compensation_x_remove
@@ -574,7 +578,7 @@ def roll_skew(ndarray[float64_t] values, ndarray[int64_t] start,
         float64_t prev_value
         int64_t nobs = 0, N = len(start), V = len(values), nobs_mean = 0
         int64_t s, e, num_consecutive_same_value
-        ndarray[float64_t] output, mean_array, values_copy
+        ndarray[float64_t] output, values_copy
         bint is_monotonic_increasing_bounds

     minp = max(minp, 3)
@@ -779,7 +783,7 @@ def roll_kurt(ndarray[float64_t] values, ndarray[int64_t] start,
               ndarray[int64_t] end, int64_t minp) -> np.ndarray:
     cdef:
         Py_ssize_t i, j
-        float64_t val, prev, mean_val, min_val, sum_val = 0
+        float64_t val, mean_val, min_val, sum_val = 0
         float64_t compensation_xxxx_add, compensation_xxxx_remove
         float64_t compensation_xxx_remove, compensation_xxx_add
         float64_t compensation_xx_remove, compensation_xx_add
@@ -853,7 +857,8 @@ def roll_kurt(ndarray[float64_t] values, ndarray[int64_t] start,
                              &compensation_xxx_add, &compensation_xxxx_add,
                              &num_consecutive_same_value, &prev_value)

-            output[i] = calc_kurt(minp, nobs, x, xx, xxx, xxxx, num_consecutive_same_value)
+            output[i] = calc_kurt(minp, nobs, x, xx, xxx, xxxx, 
+                                  num_consecutive_same_value)

             if not is_monotonic_increasing_bounds:
                 nobs = 0
@@ -876,7 +881,7 @@ def roll_median_c(const float64_t[:] values, ndarray[int64_t] start,
         bint err = False, is_monotonic_increasing_bounds
         int midpoint, ret = 0
         int64_t nobs = 0, N = len(start), s, e, win
-        float64_t val, res, prev
+        float64_t val, res,
         skiplist_t *sl
         ndarray[float64_t] output

@@ -1149,7 +1154,7 @@ def roll_quantile(const float64_t[:] values, ndarray[int64_t] start,
         Py_ssize_t i, j, s, e, N = len(start), idx
         int ret = 0
         int64_t nobs = 0, win
-        float64_t val, prev, midpoint, idx_with_fraction
+        float64_t val, idx_with_fraction
         float64_t vlow, vhigh
         skiplist_t *skiplist
         InterpolationType interpolation_type
@@ -1275,7 +1280,7 @@ def roll_rank(const float64_t[:] values, ndarray[int64_t] start,
     derived from roll_quantile
     """
     cdef:
-        Py_ssize_t i, j, s, e, N = len(start), idx
+        Py_ssize_t i, j, s, e, N = len(start),
         float64_t rank_min = 0, rank = 0
         int64_t nobs = 0, win
         float64_t val
diff --git a/pandas/errors/__init__.py b/pandas/errors/__init__.py
index 3e4f116953..89ac1c1025 100644
--- a/pandas/errors/__init__.py
+++ b/pandas/errors/__init__.py
@@ -283,7 +283,7 @@ class SettingWithCopyError(ValueError):
     The ``mode.chained_assignment`` needs to be set to set to 'raise.' This can
     happen unintentionally when chained indexing.

-    For more information on eveluation order,
+    For more information on evaluation order,
     see :ref:`the user guide<indexing.evaluation_order>`.

     For more information on view vs. copy,
@@ -306,7 +306,7 @@ class SettingWithCopyWarning(Warning):
     'Warn' is the default option. This can happen unintentionally when
     chained indexing.

-    For more information on eveluation order,
+    For more information on evaluation order,
     see :ref:`the user guide<indexing.evaluation_order>`.

     For more information on view vs. copy,
diff --git a/pandas/io/sas/byteswap.pyx b/pandas/io/sas/byteswap.pyx
index 4620403910..a83419b15b 100644
--- a/pandas/io/sas/byteswap.pyx
+++ b/pandas/io/sas/byteswap.pyx
@@ -1,5 +1,6 @@
 """
-The following are faster versions of struct.unpack that avoid the overhead of Python function calls.
+The following are faster versions of struct.unpack that avoid the overhead of Python  
+function calls.

 In the SAS7BDAT parser, they may be called up to (n_rows * n_cols) times.
 """
diff --git a/pandas/io/sas/sas.pyx b/pandas/io/sas/sas.pyx
index 9406900b69..3e8471907f 100644
--- a/pandas/io/sas/sas.pyx
+++ b/pandas/io/sas/sas.pyx
@@ -253,8 +253,10 @@ cdef:


 def _init_subheader_signatures():
-    subheaders_32bit = [(sig, idx) for sig, idx in const.subheader_signature_to_index.items() if len(sig) == 4]
-    subheaders_64bit  = [(sig, idx) for sig, idx in const.subheader_signature_to_index.items() if len(sig) == 8]
+    subheaders_32bit = [(sig, idx) for sig, idx 
+                                in const.subheader_signature_to_index.items() if len(sig) == 4]
+    subheaders_64bit  = [(sig, idx) for sig, idx 
+                                in const.subheader_signature_to_index.items() if len(sig) == 8]
     assert len(subheaders_32bit) == 13
     assert len(subheaders_64bit) == 17
     assert len(const.subheader_signature_to_index) == 13 + 17
@@ -366,7 +368,6 @@ cdef class Parser:
     def read(self, int nrows):
         cdef:
             bint done
-            int i

         for _ in range(nrows):
             done = self.readline()
@@ -490,7 +491,8 @@ cdef class Parser:
             rpos = self.decompress(source, decompressed_source)
             if rpos != self.row_length:
                 raise ValueError(
-                    f"Expected decompressed line of length {self.row_length} bytes but decompressed {rpos} bytes"
+                    f"Expected decompressed line of length {self.row_length} bytes but 
+                      decompressed {rpos} bytes"
                 )
             source = decompressed_source

(END)

Sorry here is the full output

ramvikrams · 2022-10-31T20:51:04Z

I can't see what you've modified in pandas/_libs/algos.pyx. if you open a draft pull request that might make it easier to tell what's going on

Should I open it or the full output is fine

MarcoGorelli · 2022-10-31T20:52:48Z

this isn't quite right

-    __lt__ = lambda self, other: (not isinstance(other, NegInfinity) and
+    __lt__ = def self, other: (not isinstance(other, NegInfinity) and
                                   not missing.checknull(other))

you'll want something like

def __lt__(self, other):
    return (not isinstance(other, NegInfinity) and
                                   not missing.checknull(other))

But yes, if you open a PR then it'll be easier to comment on specific lines

ramvikrams · 2022-10-31T20:55:45Z

this isn't quite right

-    __lt__ = lambda self, other: (not isinstance(other, NegInfinity) and
+    __lt__ = def self, other: (not isinstance(other, NegInfinity) and
                                   not missing.checknull(other))

you'll want something like

def __lt__(self, other):
    return (not isinstance(other, NegInfinity) and
                                   not missing.checknull(other))

But yes, if you open a PR then it'll be easier to comment on specific lines

Ok I'll do that

ramvikrams · 2022-10-31T21:06:47Z

How can we create the draft pull request from vscode

MarcoGorelli · 2022-10-31T21:09:50Z

I don't know about vscode, but see here for draft PRs https://github.blog/2019-02-14-introducing-draft-pull-requests/

it doesn't even have to be a draft PR, you can just put "WIP" in the title and I'll take a look whilst we fix up the error

ramvikrams · 2022-10-31T21:12:52Z

just getting back in 20 mins sir

ramvikrams · 2022-10-31T21:51:35Z

created a draft pull request sir

MarcoGorelli added Code Style Code style, linting, code_checks good first issue labels Oct 31, 2022

MarcoGorelli mentioned this issue Nov 4, 2022

UPGRADE: Autoupdate pre-commit config #49428

Merged

MarcoGorelli closed this as completed in #49428 Nov 4, 2022

Uh oh!

STYLE autoupdate pre-commit #49406

STYLE autoupdate pre-commit #49406

Comments

MarcoGorelli commented Oct 31, 2022

ramvikrams commented Oct 31, 2022

Uh oh!

MarcoGorelli commented Oct 31, 2022

Uh oh!

ramvikrams commented Oct 31, 2022

Uh oh!

MarcoGorelli commented Oct 31, 2022

Uh oh!

ramvikrams commented Oct 31, 2022

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ramvikrams commented Oct 31, 2022

Uh oh!

MarcoGorelli commented Oct 31, 2022

Uh oh!

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MarcoGorelli commented Oct 31, 2022

Uh oh!

ramvikrams commented Oct 31, 2022

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MarcoGorelli commented Oct 31, 2022

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ramvikrams commented Oct 31, 2022

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ramvikrams commented Oct 31, 2022

Uh oh!

MarcoGorelli commented Oct 31, 2022

Uh oh!

ramvikrams commented Oct 31, 2022

Uh oh!

ramvikrams commented Oct 31, 2022

Uh oh!

MarcoGorelli commented Oct 31, 2022

Uh oh!

ramvikrams commented Oct 31, 2022

Uh oh!

ramvikrams commented Oct 31, 2022

Uh oh!

ramvikrams commented Oct 31, 2022 •

edited

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