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)
Comment From: ramvikrams
At what time tommorow will the autoupdate happen
Comment From: MarcoGorelli
7 am UTC, but this PR can be done at any time
Comment From: ramvikrams
I'll start it at 7 am then, can be done at any time after the autoupdate right
Comment From: MarcoGorelli
it can be done before, the automated job will fail anyway so ideally we'd take your PR instead of the automated one
Comment From: ramvikrams
Oh I'll start with it rightaway then
Comment From: ramvikrams
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
Comment From: MarcoGorelli
yeah looks like it's unused in that function, so you can just remove the npy_datetimestruct dts line
Comment From: ramvikrams
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
Comment From: MarcoGorelli
could you please show me the output of git diff upstream/main?
Comment From: ramvikrams
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
Comment From: MarcoGorelli
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
Comment From: ramvikrams
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
Comment From: ramvikrams
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
Comment From: MarcoGorelli
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
Comment From: ramvikrams
this isn't quite right
diff - __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
Comment From: ramvikrams
How can we create the draft pull request from vscode
Comment From: MarcoGorelli
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
Comment From: ramvikrams
just getting back in 20 mins sir
Comment From: ramvikrams
created a draft pull request sir