From ef0bb9109e22190c3bf06e7b11b387122a22391d Mon Sep 17 00:00:00 2001 From: MomIsBestFriend <> Date: Wed, 25 Mar 2020 13:36:12 +0200 Subject: [PATCH] STY: Boolean values for bint variables --- pandas/_libs/lib.pyx | 132 +++++++++++++++++++++---------------------- 1 file changed, 66 insertions(+), 66 deletions(-) diff --git a/pandas/_libs/lib.pyx b/pandas/_libs/lib.pyx index 6aa9a8b2dedfd..6c6f6a8600ba2 100644 --- a/pandas/_libs/lib.pyx +++ b/pandas/_libs/lib.pyx @@ -530,14 +530,14 @@ def maybe_booleans_to_slice(ndarray[uint8_t] mask): cdef: Py_ssize_t i, n = len(mask) Py_ssize_t start = 0, end = 0 - bint started = 0, finished = 0 + bint started = False, finished = False for i in range(n): if mask[i]: if finished: return mask.view(np.bool_) if not started: - started = 1 + started = True start = i else: if finished: @@ -545,7 +545,7 @@ def maybe_booleans_to_slice(ndarray[uint8_t] mask): if started: end = i - finished = 1 + finished = True if not started: return slice(0, 0) @@ -657,13 +657,13 @@ def clean_index_list(obj: list): cdef: Py_ssize_t i, n = len(obj) object val - bint all_arrays = 1 + bint all_arrays = True for i in range(n): val = obj[i] if not (isinstance(val, list) or util.is_array(val) or hasattr(val, '_data')): - all_arrays = 0 + all_arrays = False break if all_arrays: @@ -692,7 +692,7 @@ def clean_index_list(obj: list): @cython.boundscheck(False) @cython.wraparound(False) def generate_bins_dt64(ndarray[int64_t] values, const int64_t[:] binner, - object closed='left', bint hasnans=0): + object closed='left', bint hasnans=False): """ Int64 (datetime64) version of generic python version in ``groupby.py``. """ @@ -1064,29 +1064,29 @@ cdef class Seen: bint timedelta_ # seen_timedelta bint datetimetz_ # seen_datetimetz - def __cinit__(self, bint coerce_numeric=0): + def __cinit__(self, bint coerce_numeric=False): """ Initialize a Seen instance. Parameters ---------- - coerce_numeric : bint, default 0 + coerce_numeric : bool, default False Whether or not to force conversion to a numeric data type if initial methods to convert to numeric fail. """ - self.int_ = 0 - self.nat_ = 0 - self.bool_ = 0 - self.null_ = 0 - self.nan_ = 0 - self.uint_ = 0 - self.sint_ = 0 - self.float_ = 0 - self.object_ = 0 - self.complex_ = 0 - self.datetime_ = 0 - self.timedelta_ = 0 - self.datetimetz_ = 0 + self.int_ = False + self.nat_ = False + self.bool_ = False + self.null_ = False + self.nan_ = False + self.uint_ = False + self.sint_ = False + self.float_ = False + self.object_ = False + self.complex_ = False + self.datetime_ = False + self.timedelta_ = False + self.datetimetz_ = False self.coerce_numeric = coerce_numeric cdef inline bint check_uint64_conflict(self) except -1: @@ -1127,8 +1127,8 @@ cdef class Seen: """ Set flags indicating that a null value was encountered. """ - self.null_ = 1 - self.float_ = 1 + self.null_ = True + self.float_ = True cdef saw_int(self, object val): """ @@ -1147,7 +1147,7 @@ cdef class Seen: val : Python int Value with which to set the flags. """ - self.int_ = 1 + self.int_ = True self.sint_ = self.sint_ or (oINT64_MIN <= val < 0) self.uint_ = self.uint_ or (oINT64_MAX < val <= oUINT64_MAX) @@ -1445,9 +1445,9 @@ def infer_datetimelike_array(arr: object) -> object: """ cdef: Py_ssize_t i, n = len(arr) - bint seen_timedelta = 0, seen_date = 0, seen_datetime = 0 - bint seen_tz_aware = 0, seen_tz_naive = 0 - bint seen_nat = 0 + bint seen_timedelta = False, seen_date = False, seen_datetime = False + bint seen_tz_aware = False, seen_tz_naive = False + bint seen_nat = False list objs = [] object v @@ -1463,27 +1463,27 @@ def infer_datetimelike_array(arr: object) -> object: # nan or None pass elif v is NaT: - seen_nat = 1 + seen_nat = True elif PyDateTime_Check(v): # datetime - seen_datetime = 1 + seen_datetime = True # disambiguate between tz-naive and tz-aware if v.tzinfo is None: - seen_tz_naive = 1 + seen_tz_naive = True else: - seen_tz_aware = 1 + seen_tz_aware = True if seen_tz_naive and seen_tz_aware: return 'mixed' elif util.is_datetime64_object(v): # np.datetime64 - seen_datetime = 1 + seen_datetime = True elif PyDate_Check(v): - seen_date = 1 + seen_date = True elif is_timedelta(v): # timedelta, or timedelta64 - seen_timedelta = 1 + seen_timedelta = True else: return "mixed" @@ -2035,10 +2035,10 @@ def maybe_convert_numeric(ndarray[object] values, set na_values, @cython.boundscheck(False) @cython.wraparound(False) -def maybe_convert_objects(ndarray[object] objects, bint try_float=0, - bint safe=0, bint convert_datetime=0, - bint convert_timedelta=0, - bint convert_to_nullable_integer=0): +def maybe_convert_objects(ndarray[object] objects, bint try_float=False, + bint safe=False, bint convert_datetime=False, + bint convert_timedelta=False, + bint convert_to_nullable_integer=False): """ Type inference function-- convert object array to proper dtype @@ -2102,45 +2102,45 @@ def maybe_convert_objects(ndarray[object] objects, bint try_float=0, val = objects[i] if val is None: - seen.null_ = 1 + seen.null_ = True floats[i] = complexes[i] = fnan mask[i] = True elif val is NaT: - seen.nat_ = 1 + seen.nat_ = True if convert_datetime: idatetimes[i] = NPY_NAT if convert_timedelta: itimedeltas[i] = NPY_NAT if not (convert_datetime or convert_timedelta): - seen.object_ = 1 + seen.object_ = True break elif val is np.nan: - seen.nan_ = 1 + seen.nan_ = True mask[i] = True floats[i] = complexes[i] = val elif util.is_bool_object(val): - seen.bool_ = 1 + seen.bool_ = True bools[i] = val elif util.is_float_object(val): floats[i] = complexes[i] = val - seen.float_ = 1 + seen.float_ = True elif util.is_datetime64_object(val): if convert_datetime: idatetimes[i] = convert_to_tsobject( val, None, None, 0, 0).value - seen.datetime_ = 1 + seen.datetime_ = True else: - seen.object_ = 1 + seen.object_ = True break elif is_timedelta(val): if convert_timedelta: itimedeltas[i] = convert_to_timedelta64(val, 'ns') - seen.timedelta_ = 1 + seen.timedelta_ = True else: - seen.object_ = 1 + seen.object_ = True break elif util.is_integer_object(val): - seen.int_ = 1 + seen.int_ = True floats[i] = val complexes[i] = val if not seen.null_: @@ -2149,7 +2149,7 @@ def maybe_convert_objects(ndarray[object] objects, bint try_float=0, if ((seen.uint_ and seen.sint_) or val > oUINT64_MAX or val < oINT64_MIN): - seen.object_ = 1 + seen.object_ = True break if seen.uint_: @@ -2162,32 +2162,32 @@ def maybe_convert_objects(ndarray[object] objects, bint try_float=0, elif util.is_complex_object(val): complexes[i] = val - seen.complex_ = 1 + seen.complex_ = True elif PyDateTime_Check(val) or util.is_datetime64_object(val): # if we have an tz's attached then return the objects if convert_datetime: if getattr(val, 'tzinfo', None) is not None: - seen.datetimetz_ = 1 + seen.datetimetz_ = True break else: - seen.datetime_ = 1 + seen.datetime_ = True idatetimes[i] = convert_to_tsobject( val, None, None, 0, 0).value else: - seen.object_ = 1 + seen.object_ = True break elif try_float and not isinstance(val, str): # this will convert Decimal objects try: floats[i] = float(val) complexes[i] = complex(val) - seen.float_ = 1 + seen.float_ = True except (ValueError, TypeError): - seen.object_ = 1 + seen.object_ = True break else: - seen.object_ = 1 + seen.object_ = True break # we try to coerce datetime w/tz but must all have the same tz @@ -2195,7 +2195,7 @@ def maybe_convert_objects(ndarray[object] objects, bint try_float=0, if is_datetime_with_singletz_array(objects): from pandas import DatetimeIndex return DatetimeIndex(objects) - seen.object_ = 1 + seen.object_ = True if not seen.object_: if not safe: @@ -2294,7 +2294,7 @@ no_default = object() #: Sentinel indicating the default value. @cython.boundscheck(False) @cython.wraparound(False) -def map_infer_mask(ndarray arr, object f, const uint8_t[:] mask, bint convert=1, +def map_infer_mask(ndarray arr, object f, const uint8_t[:] mask, bint convert=True, object na_value=no_default, object dtype=object): """ Substitute for np.vectorize with pandas-friendly dtype inference. @@ -2343,16 +2343,16 @@ def map_infer_mask(ndarray arr, object f, const uint8_t[:] mask, bint convert=1, if convert: return maybe_convert_objects(result, - try_float=0, - convert_datetime=0, - convert_timedelta=0) + try_float=False, + convert_datetime=False, + convert_timedelta=False) return result @cython.boundscheck(False) @cython.wraparound(False) -def map_infer(ndarray arr, object f, bint convert=1): +def map_infer(ndarray arr, object f, bint convert=True): """ Substitute for np.vectorize with pandas-friendly dtype inference. @@ -2385,9 +2385,9 @@ def map_infer(ndarray arr, object f, bint convert=1): if convert: return maybe_convert_objects(result, - try_float=0, - convert_datetime=0, - convert_timedelta=0) + try_float=False, + convert_datetime=False, + convert_timedelta=False) return result