CLN:F-string in pandas/_libs/tslibs/*.pyx (pandas-dev#29775)

Author: ShaharNaveh

pandas/_libs/tslibs/c_timestamp.pyx

@@ -55,11 +55,11 @@ def maybe_integer_op_deprecated(obj):
     # GH#22535 add/sub of integers and int-arrays is deprecated
     if obj.freq is not None:
         warnings.warn("Addition/subtraction of integers and integer-arrays "
-                      "to {cls} is deprecated, will be removed in a future "
+                      f"to {type(obj).__name__} is deprecated, "
+                      "will be removed in a future "
                       "version.  Instead of adding/subtracting `n`, use "
                       "`n * self.freq`"
-                      .format(cls=type(obj).__name__),
-                      FutureWarning)
+                      , FutureWarning)
 
 
 cdef class _Timestamp(datetime):
@@ -144,11 +144,10 @@ cdef class _Timestamp(datetime):
             # e.g. tzlocal has no `strftime`
             pass
 
-        tz = ", tz='{0}'".format(zone) if zone is not None else ""
-        freq = "" if self.freq is None else ", freq='{0}'".format(self.freqstr)
+        tz = f", tz='{zone}'" if zone is not None else ""
+        freq = "" if self.freq is None else f", freq='{self.freqstr}'"
 
-        return "Timestamp('{stamp}'{tz}{freq})".format(stamp=stamp,
-                                                       tz=tz, freq=freq)
+        return f"Timestamp('{stamp}'{tz}{freq})"
 
     cdef bint _compare_outside_nanorange(_Timestamp self, datetime other,
                                          int op) except -1:
@@ -370,23 +369,22 @@ cdef class _Timestamp(datetime):
 
     @property
     def _repr_base(self) -> str:
-        return '{date} {time}'.format(date=self._date_repr,
-                                      time=self._time_repr)
+        return f"{self._date_repr} {self._time_repr}"
 
     @property
     def _date_repr(self) -> str:
         # Ideal here would be self.strftime("%Y-%m-%d"), but
         # the datetime strftime() methods require year >= 1900
-        return '%d-%.2d-%.2d' % (self.year, self.month, self.day)
+        return f'{self.year}-{self.month:02d}-{self.day:02d}'
 
     @property
     def _time_repr(self) -> str:
-        result = '%.2d:%.2d:%.2d' % (self.hour, self.minute, self.second)
+        result = f'{self.hour:02d}:{self.minute:02d}:{self.second:02d}'
 
         if self.nanosecond != 0:
-            result += '.%.9d' % (self.nanosecond + 1000 * self.microsecond)
+            result += f'.{self.nanosecond + 1000 * self.microsecond:09d}'
         elif self.microsecond != 0:
-            result += '.%.6d' % self.microsecond
+            result += f'.{self.microsecond:06d}'
 
         return result
 

pandas/_libs/tslibs/conversion.pyx

@@ -197,7 +197,7 @@ def datetime_to_datetime64(object[:] values):
                 iresult[i] = pydatetime_to_dt64(val, &dts)
                 check_dts_bounds(&dts)
         else:
-            raise TypeError('Unrecognized value type: %s' % type(val))
+            raise TypeError(f'Unrecognized value type: {type(val)}')
 
     return result, inferred_tz
 
@@ -326,8 +326,8 @@ cdef convert_to_tsobject(object ts, object tz, object unit,
         raise ValueError("Cannot convert Period to Timestamp "
                          "unambiguously. Use to_timestamp")
     else:
-        raise TypeError('Cannot convert input [{}] of type {} to '
-                        'Timestamp'.format(ts, type(ts)))
+        raise TypeError(f'Cannot convert input [{ts}] of type {type(ts)} to '
+                        f'Timestamp')
 
     if tz is not None:
         localize_tso(obj, tz)
@@ -686,7 +686,7 @@ def normalize_date(dt: object) -> datetime:
     elif PyDate_Check(dt):
         return datetime(dt.year, dt.month, dt.day)
     else:
-        raise TypeError('Unrecognized type: %s' % type(dt))
+        raise TypeError(f'Unrecognized type: {type(dt)}')
 
 
 @cython.wraparound(False)

pandas/_libs/tslibs/fields.pyx

@@ -130,7 +130,7 @@ def get_date_name_field(const int64_t[:] dtindex, object field, object locale=No
             out[i] = names[dts.month].capitalize()
 
     else:
-        raise ValueError("Field {field} not supported".format(field=field))
+        raise ValueError(f"Field {field} not supported")
 
     return out
 
@@ -165,8 +165,7 @@ def get_start_end_field(const int64_t[:] dtindex, object field,
 
     if freqstr:
         if freqstr == 'C':
-            raise ValueError("Custom business days is not supported by {field}"
-                             .format(field=field))
+            raise ValueError(f"Custom business days is not supported by {field}")
         is_business = freqstr[0] == 'B'
 
         # YearBegin(), BYearBegin() use month = starting month of year.
@@ -373,7 +372,7 @@ def get_start_end_field(const int64_t[:] dtindex, object field,
                     out[i] = 1
 
     else:
-        raise ValueError("Field {field} not supported".format(field=field))
+        raise ValueError(f"Field {field} not supported")
 
     return out.view(bool)
 
@@ -537,7 +536,7 @@ def get_date_field(const int64_t[:] dtindex, object field):
     elif field == 'is_leap_year':
         return isleapyear_arr(get_date_field(dtindex, 'Y'))
 
-    raise ValueError("Field {field} not supported".format(field=field))
+    raise ValueError(f"Field {field} not supported")
 
 
 @cython.wraparound(False)
@@ -653,7 +652,7 @@ def get_timedelta_field(const int64_t[:] tdindex, object field):
                 out[i] = tds.nanoseconds
         return out
 
-    raise ValueError("Field %s not supported" % field)
+    raise ValueError(f"Field {field} not supported")
 
 
 cpdef isleapyear_arr(ndarray years):

pandas/_libs/tslibs/frequencies.pyx

@@ -197,7 +197,7 @@ cpdef _base_and_stride(str freqstr):
     groups = opattern.match(freqstr)
 
     if not groups:
-        raise ValueError("Could not evaluate {freq}".format(freq=freqstr))
+        raise ValueError(f"Could not evaluate {freqstr}")
 
     stride = groups.group(1)
 

pandas/_libs/tslibs/nattype.pyx

@@ -115,8 +115,8 @@ cdef class _NaT(datetime):
             if is_datetime64_object(other):
                 return _nat_scalar_rules[op]
             else:
-                raise TypeError('Cannot compare type %r with type %r' %
-                                (type(self).__name__, type(other).__name__))
+                raise TypeError(f'Cannot compare type {type(self).__name__} '
+                                f'with type {type(other).__name__}')
 
         # Note: instead of passing "other, self, _reverse_ops[op]", we observe
         # that `_nat_scalar_rules` is invariant under `_reverse_ops`,
@@ -150,8 +150,7 @@ cdef class _NaT(datetime):
                 result = np.empty(other.shape, dtype="datetime64[ns]")
                 result.fill("NaT")
                 return result
-            raise TypeError("Cannot add NaT to ndarray with dtype {dtype}"
-                            .format(dtype=other.dtype))
+            raise TypeError(f"Cannot add NaT to ndarray with dtype {other.dtype}")
 
         return NotImplemented
 
@@ -203,9 +202,8 @@ cdef class _NaT(datetime):
                 result.fill("NaT")
                 return result
 
-            raise TypeError(
-                "Cannot subtract NaT from ndarray with dtype {dtype}"
-                .format(dtype=other.dtype))
+            raise TypeError(f"Cannot subtract NaT from ndarray with "
+                            f"dtype {other.dtype}")
 
         return NotImplemented
 

pandas/_libs/tslibs/np_datetime.pyx

@@ -112,11 +112,9 @@ cdef inline check_dts_bounds(npy_datetimestruct *dts):
         error = True
 
     if error:
-        fmt = '%d-%.2d-%.2d %.2d:%.2d:%.2d' % (dts.year, dts.month,
-                                               dts.day, dts.hour,
-                                               dts.min, dts.sec)
-        raise OutOfBoundsDatetime(
-            'Out of bounds nanosecond timestamp: {fmt}'.format(fmt=fmt))
+        fmt = (f'{dts.year}-{dts.month:02d}-{dts.day:02d} '
+               f'{dts.hour:02d}:{dts.min:02d}:{dts.sec:02d}')
+        raise OutOfBoundsDatetime(f'Out of bounds nanosecond timestamp: {fmt}')
 
 
 # ----------------------------------------------------------------------

pandas/_libs/tslibs/offsets.pyx

@@ -66,16 +66,16 @@ need_suffix = ['QS', 'BQ', 'BQS', 'YS', 'AS', 'BY', 'BA', 'BYS', 'BAS']
 
 for __prefix in need_suffix:
     for _m in MONTHS:
-        key = '%s-%s' % (__prefix, _m)
+        key = f'{__prefix}-{_m}'
         _offset_to_period_map[key] = _offset_to_period_map[__prefix]
 
 for __prefix in ['A', 'Q']:
     for _m in MONTHS:
-        _alias = '%s-%s' % (__prefix, _m)
+        _alias = f'{__prefix}-{_m}'
         _offset_to_period_map[_alias] = _alias
 
 for _d in DAYS:
-    _offset_to_period_map['W-%s' % _d] = 'W-%s' % _d
+    _offset_to_period_map[f'W-{_d}'] = f'W-{_d}'
 
 
 # ---------------------------------------------------------------------
@@ -432,9 +432,9 @@ class _BaseOffset:
 
         n_str = ""
         if self.n != 1:
-            n_str = "%s * " % self.n
+            n_str = f"{self.n} * "
 
-        out = '<%s' % n_str + className + plural + self._repr_attrs() + '>'
+        out = f'<{n_str}{className}{plural}{self._repr_attrs()}>'
         return out
 
     def _get_offset_day(self, datetime other):
@@ -460,16 +460,13 @@ class _BaseOffset:
         ValueError if n != int(n)
         """
         if util.is_timedelta64_object(n):
-            raise TypeError('`n` argument must be an integer, '
-                            'got {ntype}'.format(ntype=type(n)))
+            raise TypeError(f'`n` argument must be an integer, got {type(n)}')
         try:
             nint = int(n)
         except (ValueError, TypeError):
-            raise TypeError('`n` argument must be an integer, '
-                            'got {ntype}'.format(ntype=type(n)))
+            raise TypeError(f'`n` argument must be an integer, got {type(n)}')
         if n != nint:
-            raise ValueError('`n` argument must be an integer, '
-                             'got {n}'.format(n=n))
+            raise ValueError(f'`n` argument must be an integer, got {n}')
         return nint
 
     def __setstate__(self, state):

pandas/_libs/tslibs/parsing.pyx

@@ -153,7 +153,7 @@ cdef inline object _parse_delimited_date(object date_string, bint dayfirst):
             return datetime_new(year, month, day, 0, 0, 0, 0, None), reso
         return datetime(year, month, day, 0, 0, 0, 0, None), reso
 
-    raise DateParseError("Invalid date specified ({}/{})".format(month, day))
+    raise DateParseError(f"Invalid date specified ({month}/{day})")
 
 
 cdef inline bint does_string_look_like_time(object parse_string):
@@ -311,7 +311,7 @@ cdef parse_datetime_string_with_reso(date_string, freq=None, dayfirst=False,
         # TODO: allow raise of errors within instead
         raise DateParseError(err)
     if parsed is None:
-        raise DateParseError("Could not parse {dstr}".format(dstr=date_string))
+        raise DateParseError(f"Could not parse {date_string}")
     return parsed, parsed, reso
 
 
@@ -420,18 +420,18 @@ cdef inline object _parse_dateabbr_string(object date_string, object default,
                     raise ValueError
 
             if not (1 <= quarter <= 4):
-                msg = ('Incorrect quarterly string is given, quarter must be '
-                       'between 1 and 4: {dstr}')
-                raise DateParseError(msg.format(dstr=date_string))
+                raise DateParseError(f'Incorrect quarterly string is given, '
+                                     f'quarter must be '
+                                     f'between 1 and 4: {date_string}')
 
             if freq is not None:
                 # hack attack, #1228
                 try:
                     mnum = MONTH_NUMBERS[_get_rule_month(freq)] + 1
                 except (KeyError, ValueError):
-                    msg = ('Unable to retrieve month information from given '
-                           'freq: {freq}'.format(freq=freq))
-                    raise DateParseError(msg)
+                    raise DateParseError(f'Unable to retrieve month '
+                                         f'information from given '
+                                         f'freq: {freq}')
 
                 month = (mnum + (quarter - 1) * 3) % 12 + 1
                 if month > mnum:
@@ -464,7 +464,7 @@ cdef inline object _parse_dateabbr_string(object date_string, object default,
         except ValueError:
             pass
 
-    raise ValueError('Unable to parse {0}'.format(date_string))
+    raise ValueError(f'Unable to parse {date_string}')
 
 
 cdef dateutil_parse(object timestr, object default, ignoretz=False,
@@ -484,8 +484,7 @@ cdef dateutil_parse(object timestr, object default, ignoretz=False,
         res, _ = res
 
     if res is None:
-        msg = "Unknown datetime string format, unable to parse: {timestr}"
-        raise ValueError(msg.format(timestr=timestr))
+        raise ValueError(f"Unknown datetime string format, unable to parse: {timestr}")
 
     for attr in ["year", "month", "day", "hour",
                  "minute", "second", "microsecond"]:
@@ -495,8 +494,7 @@ cdef dateutil_parse(object timestr, object default, ignoretz=False,
             reso = attr
 
     if reso is None:
-        msg = "Unable to parse datetime string: {timestr}"
-        raise ValueError(msg.format(timestr=timestr))
+        raise ValueError(f"Unable to parse datetime string: {timestr}")
 
     if reso == 'microsecond':
         if repl['microsecond'] == 0:
@@ -710,7 +708,7 @@ class _timelex:
         elif getattr(instream, 'read', None) is None:
             raise TypeError(
                 'Parser must be a string or character stream, not '
-                '{itype}'.format(itype=instream.__class__.__name__))
+                f'{type(instream).__name__}')
         else:
             self.stream = instream.read()