Update imports, use nogil version of sqrt (#18557)

Author: jbrockmendel

pandas/_libs/algos.pyx

@@ -27,7 +27,7 @@ from numpy cimport (ndarray,
 cdef double NaN = <double> np.NaN
 cdef double nan = NaN
 
-from libc.math cimport sqrt, fabs
+from libc.math cimport fabs, sqrt
 
 # this is our util.pxd
 from util cimport numeric, get_nat

pandas/_libs/lib.pyx

@@ -1,13 +1,18 @@
 # cython: profile=False
-cimport numpy as np
-cimport cython
-import numpy as np
-import sys
+import operator
 
-cdef bint PY3 = (sys.version_info[0] >= 3)
-
-from numpy cimport *
+cimport cython
+from cython cimport Py_ssize_t
 
+import numpy as np
+cimport numpy as np
+from numpy cimport (ndarray, PyArray_NDIM, PyArray_GETITEM, PyArray_SETITEM,
+                    PyArray_ITER_DATA, PyArray_ITER_NEXT, PyArray_IterNew,
+                    flatiter, NPY_OBJECT,
+                    int64_t,
+                    float32_t, float64_t,
+                    uint8_t, uint64_t,
+                    complex128_t)
 # initialize numpy
 np.import_array()
 np.import_ufunc()
@@ -57,12 +62,12 @@ from tslib import NaT, Timestamp, Timedelta, array_to_datetime
 from interval import Interval
 from missing cimport checknull
 
-cdef int64_t NPY_NAT = util.get_nat()
 
 cimport util
+cdef int64_t NPY_NAT = util.get_nat()
 from util cimport is_array, _checknull
 
-from libc.math cimport sqrt, fabs
+from libc.math cimport fabs, sqrt
 
 
 def values_from_object(object o):
@@ -494,7 +499,6 @@ def maybe_booleans_to_slice(ndarray[uint8_t] mask):
 @cython.wraparound(False)
 @cython.boundscheck(False)
 def scalar_compare(ndarray[object] values, object val, object op):
-    import operator
     cdef:
         Py_ssize_t i, n = len(values)
         ndarray[uint8_t, cast=True] result
@@ -529,7 +533,7 @@ def scalar_compare(ndarray[object] values, object val, object op):
                 result[i] = True
             else:
                 try:
-                    result[i] = cpython.PyObject_RichCompareBool(x, val, flag)
+                    result[i] = PyObject_RichCompareBool(x, val, flag)
                 except (TypeError):
                     result[i] = True
     elif flag == cpython.Py_EQ:
@@ -541,7 +545,7 @@ def scalar_compare(ndarray[object] values, object val, object op):
                 result[i] = False
             else:
                 try:
-                    result[i] = cpython.PyObject_RichCompareBool(x, val, flag)
+                    result[i] = PyObject_RichCompareBool(x, val, flag)
                 except (TypeError):
                     result[i] = False
 
@@ -553,7 +557,7 @@ def scalar_compare(ndarray[object] values, object val, object op):
             elif isnull_val:
                 result[i] = False
             else:
-                result[i] = cpython.PyObject_RichCompareBool(x, val, flag)
+                result[i] = PyObject_RichCompareBool(x, val, flag)
 
     return result.view(bool)
 
@@ -582,7 +586,6 @@ cpdef bint array_equivalent_object(object[:] left, object[:] right):
 @cython.wraparound(False)
 @cython.boundscheck(False)
 def vec_compare(ndarray[object] left, ndarray[object] right, object op):
-    import operator
     cdef:
         Py_ssize_t i, n = len(left)
         ndarray[uint8_t, cast=True] result
@@ -617,7 +620,7 @@ def vec_compare(ndarray[object] left, ndarray[object] right, object op):
             if checknull(x) or checknull(y):
                 result[i] = True
             else:
-                result[i] = cpython.PyObject_RichCompareBool(x, y, flag)
+                result[i] = PyObject_RichCompareBool(x, y, flag)
     else:
         for i in range(n):
             x = left[i]
@@ -626,7 +629,7 @@ def vec_compare(ndarray[object] left, ndarray[object] right, object op):
             if checknull(x) or checknull(y):
                 result[i] = False
             else:
-                result[i] = cpython.PyObject_RichCompareBool(x, y, flag)
+                result[i] = PyObject_RichCompareBool(x, y, flag)
 
     return result.view(bool)
 

pandas/_libs/src/util.pxd

@@ -2,6 +2,7 @@ from numpy cimport ndarray
 cimport numpy as cnp
 cimport cpython
 
+
 cdef extern from "numpy_helper.h":
     void set_array_not_contiguous(ndarray ao)
 

pandas/core/indexes/datetimes.py

@@ -43,8 +43,7 @@
     DatelikeOps, TimelikeOps, DatetimeIndexOpsMixin)
 from pandas.tseries.offsets import (
     DateOffset, generate_range, Tick, CDay, prefix_mapping)
-from pandas.core.tools.datetimes import (
-    parse_time_string, normalize_date, to_time)
+
 from pandas.core.tools.timedeltas import to_timedelta
 from pandas.util._decorators import (Appender, cache_readonly,
                                      deprecate_kwarg, Substitution)
@@ -55,7 +54,7 @@
 from pandas._libs import (lib, index as libindex, tslib as libts,
                           algos as libalgos, join as libjoin,
                           Timestamp)
-from pandas._libs.tslibs import (timezones, conversion, fields,
+from pandas._libs.tslibs import (timezones, conversion, fields, parsing,
                                  period as libperiod)
 
 # -------- some conversion wrapper functions
@@ -524,14 +523,14 @@ def _generate(cls, start, end, periods, name, offset,
 
         if start is not None:
             if normalize:
-                start = normalize_date(start)
+                start = libts.normalize_date(start)
                 _normalized = True
             else:
                 _normalized = _normalized and start.time() == _midnight
 
         if end is not None:
             if normalize:
-                end = normalize_date(end)
+                end = libts.normalize_date(end)
                 _normalized = True
             else:
                 _normalized = _normalized and end.time() == _midnight
@@ -1529,7 +1528,7 @@ def _maybe_cast_slice_bound(self, label, side, kind):
         if isinstance(label, compat.string_types):
             freq = getattr(self, 'freqstr',
                            getattr(self, 'inferred_freq', None))
-            _, parsed, reso = parse_time_string(label, freq)
+            _, parsed, reso = parsing.parse_time_string(label, freq)
             lower, upper = self._parsed_string_to_bounds(reso, parsed)
             # lower, upper form the half-open interval:
             #   [parsed, parsed + 1 freq)
@@ -1546,7 +1545,7 @@ def _maybe_cast_slice_bound(self, label, side, kind):
     def _get_string_slice(self, key, use_lhs=True, use_rhs=True):
         freq = getattr(self, 'freqstr',
                        getattr(self, 'inferred_freq', None))
-        _, parsed, reso = parse_time_string(key, freq)
+        _, parsed, reso = parsing.parse_time_string(key, freq)
         loc = self._partial_date_slice(reso, parsed, use_lhs=use_lhs,
                                        use_rhs=use_rhs)
         return loc
@@ -1965,8 +1964,8 @@ def indexer_between_time(self, start_time, end_time, include_start=True,
         -------
         values_between_time : TimeSeries
         """
-        start_time = to_time(start_time)
-        end_time = to_time(end_time)
+        start_time = tools.to_time(start_time)
+        end_time = tools.to_time(end_time)
         time_micros = self._get_time_micros()
         start_micros = _time_to_micros(start_time)
         end_micros = _time_to_micros(end_time)

pandas/core/tools/datetimes.py

@@ -629,8 +629,6 @@ def calc_with_mask(carg, mask):
     return None
 
 
-normalize_date = tslib.normalize_date
-
 # Fixed time formats for time parsing
 _time_formats = ["%H:%M", "%H%M", "%I:%M%p", "%I%M%p",
                  "%H:%M:%S", "%H%M%S", "%I:%M:%S%p", "%I%M%S%p"]

pandas/tests/indexes/datetimes/test_tools.py

@@ -16,7 +16,7 @@
 from pandas._libs import tslib
 from pandas._libs.tslibs import parsing
 from pandas.core.tools import datetimes as tools
-from pandas.core.tools.datetimes import normalize_date
+
 from pandas.compat import lmap
 from pandas.compat.numpy import np_array_datetime64_compat
 from pandas.core.dtypes.common import is_datetime64_ns_dtype
@@ -1576,12 +1576,12 @@ def test_coerce_of_invalid_datetimes(self):
 def test_normalize_date():
     value = date(2012, 9, 7)
 
-    result = normalize_date(value)
+    result = tslib.normalize_date(value)
     assert (result == datetime(2012, 9, 7))
 
     value = datetime(2012, 9, 7, 12)
 
-    result = normalize_date(value)
+    result = tslib.normalize_date(value)
     assert (result == datetime(2012, 9, 7))
 
 

pandas/tseries/offsets.py

@@ -8,7 +8,7 @@
 import numpy as np
 
 from pandas.core.dtypes.generic import ABCSeries, ABCDatetimeIndex, ABCPeriod
-from pandas.core.tools.datetimes import to_datetime, normalize_date
+from pandas.core.tools.datetimes import to_datetime
 from pandas.core.common import AbstractMethodError
 
 # import after tools, dateutil check
@@ -103,7 +103,7 @@ def wrapper(self, other):
 
             if self.normalize:
                 # normalize_date returns normal datetime
-                result = normalize_date(result)
+                result = tslib.normalize_date(result)
 
             if tz is not None and result.tzinfo is None:
                 result = tslib._localize_pydatetime(result, tz)