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Zip Strict specification for pandas/core/indexes #62533

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f6f1210
add strict arg to interval.py
krishna-datta Oct 1, 2025
7b352dc
expect to fail; removed check
krishna-datta Oct 1, 2025
a57bea0
revert acc chng
krishna-datta Oct 10, 2025
418f19f
some more strict added
krishna-datta Oct 10, 2025
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4 changes: 2 additions & 2 deletions pandas/core/indexes/interval.py
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Original file line number Diff line number Diff line change
Expand Up @@ -1056,8 +1056,8 @@ def _intersection_non_unique(self, other: IntervalIndex) -> IntervalIndex:
first_nan_loc = np.arange(len(self))[self.isna()][0]
mask[first_nan_loc] = True

other_tups = set(zip(other.left, other.right))
for i, tup in enumerate(zip(self.left, self.right)):
other_tups = set(zip(other.left, other.right, strict=True))
for i, tup in enumerate(zip(self.left, self.right, strict=True)):
if tup in other_tups:
mask[i] = True

Expand Down
47 changes: 25 additions & 22 deletions pandas/core/indexes/multi.py
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Original file line number Diff line number Diff line change
Expand Up @@ -720,7 +720,7 @@ def from_frame(
if not isinstance(df, ABCDataFrame):
raise TypeError("Input must be a DataFrame")

column_names, columns = zip(*df.items())
column_names, columns = zip(*df.items(), strict=True)
names = column_names if names is None else names
return cls.from_arrays(columns, sortorder=sortorder, names=names)

Expand Down Expand Up @@ -878,7 +878,10 @@ def levels(self) -> FrozenList:
# Use cache_readonly to ensure that self.get_locs doesn't repeatedly
# create new IndexEngine
# https://github.com/pandas-dev/pandas/issues/31648
result = [x._rename(name=name) for x, name in zip(self._levels, self._names)]
result = [
x._rename(name=name)
for x, name in zip(self._levels, self._names, strict=True)
]
for level in result:
# disallow midx.levels[0].name = "foo"
level._no_setting_name = True
Expand Down Expand Up @@ -912,7 +915,7 @@ def _set_levels(
else:
level_numbers = [self._get_level_number(lev) for lev in level]
new_levels_list = list(self._levels)
for lev_num, lev in zip(level_numbers, levels):
for lev_num, lev in zip(level_numbers, levels, strict=False):
new_levels_list[lev_num] = ensure_index(lev, copy=copy)._view()
new_levels = FrozenList(new_levels_list)

Expand Down Expand Up @@ -1148,13 +1151,13 @@ def _set_codes(
if level is None:
new_codes = FrozenList(
_coerce_indexer_frozen(level_codes, lev, copy=copy).view()
for lev, level_codes in zip(self._levels, codes)
for lev, level_codes in zip(self._levels, codes, strict=False)
)
level_numbers = range(len(new_codes))
else:
level_numbers = [self._get_level_number(lev) for lev in level]
new_codes_list = list(self._codes)
for lev_num, level_codes in zip(level_numbers, codes):
for lev_num, level_codes in zip(level_numbers, codes, strict=False):
lev = self.levels[lev_num]
new_codes_list[lev_num] = _coerce_indexer_frozen(
level_codes, lev, copy=copy
Expand Down Expand Up @@ -1478,7 +1481,7 @@ def _formatter_func(self, tup):
Formats each item in tup according to its level's formatter function.
"""
formatter_funcs = (level._formatter_func for level in self.levels)
return tuple(func(val) for func, val in zip(formatter_funcs, tup))
return tuple(func(val) for func, val in zip(formatter_funcs, tup, strict=False))

def _get_values_for_csv(
self, *, na_rep: str = "nan", **kwargs
Expand All @@ -1487,7 +1490,7 @@ def _get_values_for_csv(
new_codes = []

# go through the levels and format them
for level, level_codes in zip(self.levels, self.codes):
for level, level_codes in zip(self.levels, self.codes, strict=False):
level_strs = level._get_values_for_csv(na_rep=na_rep, **kwargs)
# add nan values, if there are any
mask = level_codes == -1
Expand Down Expand Up @@ -1527,7 +1530,7 @@ def _format_multi(
return []

stringified_levels = []
for lev, level_codes in zip(self.levels, self.codes):
for lev, level_codes in zip(self.levels, self.codes, strict=False):
na = _get_na_rep(lev.dtype)

if len(lev) > 0:
Expand All @@ -1550,7 +1553,7 @@ def _format_multi(
stringified_levels.append(formatted)

result_levels = []
for lev, lev_name in zip(stringified_levels, self.names):
for lev, lev_name in zip(stringified_levels, self.names, strict=False):
level = []

if include_names:
Expand Down Expand Up @@ -1627,7 +1630,7 @@ def _set_names(self, names, *, level=None) -> None:
level = (self._get_level_number(lev) for lev in level)

# set the name
for lev, name in zip(level, names):
for lev, name in zip(level, names, strict=False):
if name is not None:
# GH 20527
# All items in 'names' need to be hashable:
Expand Down Expand Up @@ -2094,7 +2097,7 @@ def _sort_levels_monotonic(self, raise_if_incomparable: bool = False) -> MultiIn
new_levels = []
new_codes = []

for lev, level_codes in zip(self.levels, self.codes):
for lev, level_codes in zip(self.levels, self.codes, strict=False):
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What fails when this is True?

if not lev.is_monotonic_increasing:
try:
# indexer to reorder the levels
Expand Down Expand Up @@ -2173,7 +2176,7 @@ def remove_unused_levels(self) -> MultiIndex:
new_codes = []

changed = False
for lev, level_codes in zip(self.levels, self.codes):
for lev, level_codes in zip(self.levels, self.codes, strict=False):
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What fails when this is True?

# Since few levels are typically unused, bincount() is more
# efficient than unique() - however it only accepts positive values
# (and drops order):
Expand Down Expand Up @@ -2240,7 +2243,7 @@ def __getitem__(self, key):
key = com.cast_scalar_indexer(key)

retval = []
for lev, level_codes in zip(self.levels, self.codes):
for lev, level_codes in zip(self.levels, self.codes, strict=False):
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What fails when this is True?

if level_codes[key] == -1:
retval.append(np.nan)
else:
Expand Down Expand Up @@ -3078,7 +3081,7 @@ def _partial_tup_index(self, tup: tuple, side: Literal["left", "right"] = "left"

n = len(tup)
start, end = 0, len(self)
zipped = zip(tup, self.levels, self.codes)
zipped = zip(tup, self.levels, self.codes, strict=False)
for k, (lab, lev, level_codes) in enumerate(zipped):
section = level_codes[start:end]

Expand Down Expand Up @@ -3362,7 +3365,7 @@ def maybe_mi_droplevels(indexer, levels):
"Key for location must have same length as number of levels"
)
result = None
for lev, k in zip(level, key):
for lev, k in zip(level, key, strict=False):
loc, new_index = self._get_loc_level(k, level=lev)
if isinstance(loc, slice):
mask = np.zeros(len(self), dtype=bool)
Expand Down Expand Up @@ -3948,7 +3951,7 @@ def _union(self, other, sort) -> MultiIndex:
if isinstance(result, MultiIndex):
return result
return MultiIndex.from_arrays(
zip(*result), sortorder=None, names=result_names
zip(*result, strict=False), sortorder=None, names=result_names
)

else:
Expand Down Expand Up @@ -3995,7 +3998,7 @@ def _maybe_match_names(self, other):
if len(self.names) != len(other.names):
return [None] * len(self.names)
names = []
for a_name, b_name in zip(self.names, other.names):
for a_name, b_name in zip(self.names, other.names, strict=False):
if a_name == b_name:
names.append(a_name)
else:
Expand Down Expand Up @@ -4092,7 +4095,7 @@ def putmask(self, mask, value: MultiIndex) -> MultiIndex:
new_codes = []

for i, (value_level, level, level_codes) in enumerate(
zip(subset.levels, self.levels, self.codes)
zip(subset.levels, self.levels, self.codes, strict=False)
):
new_level = level.union(value_level, sort=False)
value_codes = new_level.get_indexer_for(subset.get_level_values(i))
Expand Down Expand Up @@ -4123,7 +4126,7 @@ def insert(self, loc: int, item) -> MultiIndex:

new_levels = []
new_codes = []
for k, level, level_codes in zip(item, self.levels, self.codes):
for k, level, level_codes in zip(item, self.levels, self.codes, strict=True):
if k not in level:
# have to insert into level
# must insert at end otherwise you have to recompute all the
Expand Down Expand Up @@ -4219,7 +4222,7 @@ def _lexsort_depth(codes: list[np.ndarray], nlevels: int) -> int:


def sparsify_labels(label_list, start: int = 0, sentinel: object = ""):
pivoted = list(zip(*label_list))
pivoted = list(zip(*label_list, strict=True))
k = len(label_list)

result = pivoted[: start + 1]
Expand All @@ -4228,7 +4231,7 @@ def sparsify_labels(label_list, start: int = 0, sentinel: object = ""):
for cur in pivoted[start + 1 :]:
sparse_cur = []

for i, (p, t) in enumerate(zip(prev, cur)):
for i, (p, t) in enumerate(zip(prev, cur, strict=True)):
if i == k - 1:
sparse_cur.append(t)
result.append(sparse_cur) # type: ignore[arg-type]
Expand All @@ -4243,7 +4246,7 @@ def sparsify_labels(label_list, start: int = 0, sentinel: object = ""):

prev = cur

return list(zip(*result))
return list(zip(*result, strict=True))


def _get_na_rep(dtype: DtypeObj) -> str:
Expand Down
2 changes: 0 additions & 2 deletions pyproject.toml
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Original file line number Diff line number Diff line change
Expand Up @@ -452,8 +452,6 @@ exclude = [
"pandas/core/groupby/groupby.py" = ["B905"]
"pandas/core/groupby/grouper.py" = ["B905"]
"pandas/core/groupby/ops.py" = ["B905"]
"pandas/core/indexes/interval.py" = ["B905"]
"pandas/core/indexes/multi.py" = ["B905"]
"pandas/core/methods/to_dict.py" = ["B905"]
"pandas/core/reshape/concat.py" = ["B905"]
"pandas/core/reshape/encoding.py" = ["B905"]
Expand Down
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