Cleanup cimports, implement bits of numpy_helper in util.pxd (pandas-dev#21878)

Author: jbrockmendel

pandas/_libs/groupby.pyx

@@ -1,21 +1,20 @@
 # -*- coding: utf-8 -*-
 # cython: profile=False
 
-cimport numpy as cnp
-import numpy as np
-
 cimport cython
+from cython cimport Py_ssize_t
 
-cnp.import_array()
+from libc.stdlib cimport malloc, free
 
+import numpy as np
 from numpy cimport (ndarray,
                     double_t,
                     int8_t, int16_t, int32_t, int64_t, uint8_t, uint16_t,
                     uint32_t, uint64_t, float32_t, float64_t)
 
-from libc.stdlib cimport malloc, free
 
 from util cimport numeric, get_nat
+
 from algos cimport (swap, TiebreakEnumType, TIEBREAK_AVERAGE, TIEBREAK_MIN,
                     TIEBREAK_MAX, TIEBREAK_FIRST, TIEBREAK_DENSE)
 from algos import take_2d_axis1_float64_float64, groupsort_indexer, tiebreakers
@@ -74,8 +73,8 @@ cdef inline float64_t kth_smallest_c(float64_t* a,
         double_t x, t
 
     l = 0
-    m = n -1
-    while (l<m):
+    m = n - 1
+    while l < m:
         x = a[k]
         i = l
         j = m

pandas/_libs/index.pyx

@@ -9,14 +9,12 @@ from cpython.slice cimport PySlice_Check
 import numpy as np
 cimport numpy as cnp
 from numpy cimport (ndarray, float64_t, int32_t,
-                    int64_t, uint8_t, uint64_t, intp_t)
+                    int64_t, uint8_t, uint64_t, intp_t,
+                    # Note: NPY_DATETIME, NPY_TIMEDELTA are only available
+                    # for cimport in cython>=0.27.3
+                    NPY_DATETIME, NPY_TIMEDELTA)
 cnp.import_array()
 
-cdef extern from "numpy/arrayobject.h":
-    # These can be cimported directly from numpy in cython>=0.27.3
-    cdef enum NPY_TYPES:
-        NPY_DATETIME
-        NPY_TIMEDELTA
 
 cimport util
 

pandas/_libs/interval.pyx

@@ -1,17 +1,22 @@
-cimport numpy as cnp
-import numpy as np
+# -*- coding: utf-8 -*-
+import numbers
+
+from cpython.object cimport (Py_EQ, Py_NE, Py_GT, Py_LT, Py_GE, Py_LE,
+                             PyObject_RichCompare)
 
-cimport util
 cimport cython
-import cython
+from cython cimport Py_ssize_t
+
+import numpy as np
 from numpy cimport ndarray
+
+
+cimport util
+
 from tslibs import Timestamp
 from tslibs.timezones cimport tz_compare
 
-from cpython.object cimport (Py_EQ, Py_NE, Py_GT, Py_LT, Py_GE, Py_LE,
-                             PyObject_RichCompare)
 
-import numbers
 _VALID_CLOSED = frozenset(['left', 'right', 'both', 'neither'])
 
 

pandas/_libs/lib.pyx

@@ -753,4 +753,4 @@ def indices_fast(object index, ndarray[int64_t] labels, list keys,
     return result
 
 
-include "inference.pyx"
+include "src/inference.pyx"

pandas/_libs/src/numpy_helper.h

@@ -30,24 +30,6 @@ PANDAS_INLINE PyObject* get_value_1d(PyArrayObject* ap, Py_ssize_t i) {
     return PyArray_Scalar(item, PyArray_DESCR(ap), (PyObject*)ap);
 }
 
-// returns ASCII or UTF8 (py3) view on python str
-// python object owns memory, should not be freed
-PANDAS_INLINE const char* get_c_string(PyObject* obj) {
-#if PY_VERSION_HEX >= 0x03000000
-    return PyUnicode_AsUTF8(obj);
-#else
-    return PyString_AsString(obj);
-#endif
-}
-
-PANDAS_INLINE PyObject* char_to_string(const char* data) {
-#if PY_VERSION_HEX >= 0x03000000
-    return PyUnicode_FromString(data);
-#else
-    return PyString_FromString(data);
-#endif
-}
-
 
 void set_array_not_contiguous(PyArrayObject* ao) {
     ao->flags &= ~(NPY_C_CONTIGUOUS | NPY_F_CONTIGUOUS);

pandas/_libs/src/util.pxd

@@ -4,6 +4,9 @@ cnp.import_array()
 
 cimport cpython
 from cpython cimport PyTypeObject
+from cpython.string cimport PyString_FromString, PyString_AsString
+
+DEF PY3 = bytes != str
 
 cdef extern from "Python.h":
     # Note: importing extern-style allows us to declare these as nogil
@@ -14,6 +17,8 @@ cdef extern from "Python.h":
     bint PyFloat_Check(object obj) nogil
     bint PyComplex_Check(object obj) nogil
     bint PyObject_TypeCheck(object obj, PyTypeObject* type) nogil
+    char* PyUnicode_AsUTF8(object unicode)
+    object PyUnicode_FromString(const char* u) nogil
 
 
 cdef extern from "numpy/arrayobject.h":
@@ -69,8 +74,6 @@ cdef extern from "numpy_helper.h":
     int assign_value_1d(ndarray, Py_ssize_t, object) except -1
     cnp.int64_t get_nat()
     object get_value_1d(ndarray, Py_ssize_t)
-    char *get_c_string(object) except NULL
-    object char_to_string(char*)
 
 ctypedef fused numeric:
     cnp.int8_t
@@ -101,6 +104,26 @@ cdef extern from "headers/stdint.h":
     enum: INT64_MIN
 
 
+cdef inline const char* get_c_string(object obj) except NULL:
+    """
+    returns ASCII or UTF8 (py3) view on python str
+    python object owns memory, should not be freed
+    """
+    # TODO: this docstring is copied verbatim from version that was
+    # directly in numpy_helper.C; is it still accurate?
+    IF PY3:
+        return PyUnicode_AsUTF8(obj)
+    ELSE:
+        return PyString_AsString(obj)
+
+
+cdef inline object char_to_string(const char* data):
+    IF PY3:
+        return PyUnicode_FromString(data)
+    ELSE:
+        return PyString_FromString(data)
+
+
 cdef inline object get_value_at(ndarray arr, object loc):
     cdef:
         Py_ssize_t i, sz

pandas/_libs/tslib.pyx

@@ -1,24 +1,29 @@
 # -*- coding: utf-8 -*-
 # cython: profile=False
+cimport cython
+from cython cimport Py_ssize_t
+
+from cpython cimport PyFloat_Check, PyUnicode_Check
+
+from cpython.datetime cimport (PyDateTime_Check, PyDate_Check,
+                               PyDateTime_CheckExact,
+                               PyDateTime_IMPORT,
+                               timedelta, datetime, date, time)
+# import datetime C API
+PyDateTime_IMPORT
+
 
 cimport numpy as cnp
 from numpy cimport int64_t, ndarray, float64_t
 import numpy as np
 cnp.import_array()
 
+import pytz
 
-from cpython cimport PyFloat_Check, PyUnicode_Check
 
 from util cimport (is_integer_object, is_float_object, is_string_object,
                    is_datetime64_object)
 
-from cpython.datetime cimport (PyDateTime_Check, PyDate_Check,
-                               PyDateTime_CheckExact,
-                               PyDateTime_IMPORT,
-                               timedelta, datetime, date, time)
-# import datetime C API
-PyDateTime_IMPORT
-
 
 from tslibs.np_datetime cimport (check_dts_bounds,
                                  pandas_datetimestruct,
@@ -30,13 +35,6 @@ from tslibs.np_datetime import OutOfBoundsDatetime
 
 from tslibs.parsing import parse_datetime_string
 
-cimport cython
-from cython cimport Py_ssize_t
-
-
-import pytz
-
-
 from tslibs.timedeltas cimport cast_from_unit
 from tslibs.timezones cimport (is_utc, is_tzlocal, is_fixed_offset,
                                treat_tz_as_pytz, get_dst_info)
@@ -54,7 +52,8 @@ from tslibs.timestamps cimport (create_timestamp_from_ts,
                                 _NS_UPPER_BOUND, _NS_LOWER_BOUND)
 from tslibs.timestamps import Timestamp
 
-cdef bint PY2 = str == bytes
+
+DEF PY2 = str == bytes
 
 
 cdef inline object create_datetime_from_ts(
@@ -556,8 +555,9 @@ cpdef array_to_datetime(ndarray[object] values, errors='raise',
                 if len(val) == 0 or val in nat_strings:
                     iresult[i] = NPY_NAT
                     continue
-                if PyUnicode_Check(val) and PY2:
-                    val = val.encode('utf-8')
+                if PY2:
+                    if PyUnicode_Check(val):
+                        val = val.encode('utf-8')
 
                 try:
                     _string_to_dts(val, &dts, &out_local, &out_tzoffset)

pandas/_libs/tslibs/offsets.pyx

@@ -334,8 +334,6 @@ class _BaseOffset(object):
             # other is not a DateOffset object
             return False
 
-        return self._params == other._params
-
     def __ne__(self, other):
         return not self == other
 

pandas/_libs/tslibs/parsing.pyx

@@ -10,7 +10,7 @@ cimport cython
 from cython cimport Py_ssize_t
 
 
-from datetime import datetime
+from cpython.datetime cimport datetime
 import time
 
 import numpy as np
@@ -37,7 +37,7 @@ from dateutil.parser import DEFAULTPARSER
 from dateutil.parser import parse as du_parse
 
 from ccalendar import MONTH_NUMBERS
-from nattype import nat_strings
+from nattype import nat_strings, NaT
 
 # ----------------------------------------------------------------------
 # Constants
@@ -54,9 +54,6 @@ cdef object _TIMEPAT = re.compile(r'^([01]?[0-9]|2[0-3]):([0-5][0-9])')
 
 cdef set _not_datelike_strings = {'a', 'A', 'm', 'M', 'p', 'P', 't', 'T'}
 
-NAT_SENTINEL = object()
-# This allows us to reference NaT without having to import it
-
 # ----------------------------------------------------------------------
 
 
@@ -136,9 +133,6 @@ def parse_time_string(arg, freq=None, dayfirst=None, yearfirst=None):
     res = parse_datetime_string_with_reso(arg, freq=freq,
                                           dayfirst=dayfirst,
                                           yearfirst=yearfirst)
-    if res[0] is NAT_SENTINEL:
-        from pandas._libs.tslib import NaT
-        res = (NaT,) + res[1:]
     return res
 
 
@@ -206,7 +200,7 @@ cdef inline object _parse_dateabbr_string(object date_string, object default,
     # should be NaT???
 
     if date_string in nat_strings:
-        return NAT_SENTINEL, NAT_SENTINEL, ''
+        return NaT, NaT, ''
 
     date_string = date_string.upper()
     date_len = len(date_string)
@@ -407,7 +401,7 @@ def try_parse_dates(ndarray[object] values, parser=None,
 
         # EAFP here
         try:
-            for i from 0 <= i < n:
+            for i in range(n):
                 if values[i] == '':
                     result[i] = np.nan
                 else:
@@ -419,7 +413,7 @@ def try_parse_dates(ndarray[object] values, parser=None,
         parse_date = parser
 
         try:
-            for i from 0 <= i < n:
+            for i in range(n):
                 if values[i] == '':
                     result[i] = np.nan
                 else:
@@ -459,7 +453,7 @@ def try_parse_date_and_time(ndarray[object] dates, ndarray[object] times,
     else:
         parse_time = time_parser
 
-    for i from 0 <= i < n:
+    for i in range(n):
         d = parse_date(str(dates[i]))
         t = parse_time(str(times[i]))
         result[i] = datetime(d.year, d.month, d.day,
@@ -479,7 +473,7 @@ def try_parse_year_month_day(ndarray[object] years, ndarray[object] months,
         raise ValueError('Length of years/months/days must all be equal')
     result = np.empty(n, dtype='O')
 
-    for i from 0 <= i < n:
+    for i in range(n):
         result[i] = datetime(int(years[i]), int(months[i]), int(days[i]))
 
     return result
@@ -505,7 +499,7 @@ def try_parse_datetime_components(ndarray[object] years,
         raise ValueError('Length of all datetime components must be equal')
     result = np.empty(n, dtype='O')
 
-    for i from 0 <= i < n:
+    for i in range(n):
         float_secs = float(seconds[i])
         secs = int(float_secs)
 

pandas/_libs/tslibs/period.pyx

@@ -46,14 +46,14 @@ from conversion cimport tz_convert_utc_to_tzlocal
 from frequencies cimport (get_freq_code, get_base_alias,
                           get_to_timestamp_base, get_freq_str,
                           get_rule_month)
-from parsing import parse_time_string, NAT_SENTINEL
+from parsing import parse_time_string
 from resolution import Resolution
 from nattype import nat_strings, NaT, iNaT
 from nattype cimport _nat_scalar_rules, NPY_NAT, is_null_datetimelike
 from offsets cimport to_offset
 from offsets import _Tick
 
-cdef bint PY2 = str == bytes
+DEF PY2 = str == bytes
 
 
 cdef extern from "period_helper.h":
@@ -729,7 +729,7 @@ cdef object _period_strftime(int64_t value, int freq, object fmt):
 
             result = result.replace(str_extra_fmts[i], repl)
 
-    if PY2:
+    IF PY2:
         result = result.decode('utf-8', 'ignore')
 
     return result
@@ -1820,7 +1820,7 @@ class Period(_Period):
                 value = str(value)
             value = value.upper()
             dt, _, reso = parse_time_string(value, freq)
-            if dt is NAT_SENTINEL:
+            if dt is NaT:
                 ordinal = iNaT
 
             if freq is None: