cleanup unused imports, constants

pandas/_libs/lib.pyx

@@ -8,7 +8,9 @@ cdef bint PY3 = (sys.version_info[0] >= 3)
 
 from numpy cimport *
 
+# initialize numpy
 np.import_array()
+np.import_ufunc()
 
 from libc.stdlib cimport malloc, free
 
@@ -52,23 +54,15 @@ PyDateTime_IMPORT
 from tslibs.np_datetime cimport get_timedelta64_value, get_datetime64_value
 
 from tslib cimport _check_all_nulls
-import tslib
-from tslib import NaT, Timestamp, Timedelta
-import interval
+from tslib import NaT, Timestamp, Timedelta, array_to_datetime
 from interval import Interval
 
 cdef int64_t NPY_NAT = util.get_nat()
 
 cimport util
 from util cimport is_array, _checknull, _checknan
 
-cdef extern from "math.h":
-    double sqrt(double x)
-    double fabs(double)
-
-# initialize numpy
-import_array()
-import_ufunc()
+from libc.math cimport sqrt, fabs
 
 
 def values_from_object(object o):
@@ -151,7 +145,7 @@ cpdef bint checknull_old(object val):
     elif is_array(val):
         return False
     else:
-        return util._checknull(val)
+        return _checknull(val)
 
 
 cpdef bint isposinf_scalar(object val):
@@ -787,13 +781,13 @@ def scalar_binop(ndarray[object] values, object val, object op):
         object x
 
     result = np.empty(n, dtype=object)
-    if util._checknull(val):
+    if _checknull(val):
         result.fill(val)
         return result
 
     for i in range(n):
         x = values[i]
-        if util._checknull(x):
+        if _checknull(x):
             result[i] = x
         else:
             result[i] = op(x, val)
@@ -820,9 +814,9 @@ def vec_binop(ndarray[object] left, ndarray[object] right, object op):
         try:
             result[i] = op(x, y)
         except TypeError:
-            if util._checknull(x):
+            if _checknull(x):
                 result[i] = x
-            elif util._checknull(y):
+            elif _checknull(y):
                 result[i] = y
             else:
                 raise

pandas/_libs/properties.pyx

@@ -1,3 +1,4 @@
+# -*- coding: utf-8 -*-
 
 from cython cimport Py_ssize_t
 

pandas/_libs/src/datetime.pxd

@@ -5,7 +5,6 @@ from cpython cimport PyUnicode_Check, PyUnicode_AsASCIIString
 
 
 cdef extern from "numpy/ndarrayobject.h":
-
     ctypedef int64_t npy_timedelta
     ctypedef int64_t npy_datetime
 
@@ -16,13 +15,11 @@ cdef extern from "numpy/ndarrayobject.h":
         NPY_SAME_KIND_CASTING
         NPY_UNSAFE_CASTING
 
-
 cdef extern from "numpy_helper.h":
     npy_datetime get_datetime64_value(object o)
     npy_timedelta get_timedelta64_value(object o)
 
 cdef extern from "numpy/npy_common.h":
-
     ctypedef unsigned char npy_bool
 
 cdef extern from "datetime/np_datetime.h":
@@ -53,7 +50,6 @@ cdef extern from "datetime/np_datetime.h":
                                            PANDAS_DATETIMEUNIT fr,
                                            pandas_datetimestruct *result) nogil
     int days_per_month_table[2][12]
-    pandas_datetimestruct _NS_MIN_DTS, _NS_MAX_DTS
 
     int dayofweek(int y, int m, int d) nogil
     int is_leapyear(int64_t year) nogil
@@ -68,8 +64,6 @@ cdef extern from "datetime/np_datetime_strings.h":
                                 npy_bool *out_special)
 
 
-
-
 cdef inline int _string_to_dts(object val, pandas_datetimestruct* dts,
                            int* out_local, int* out_tzoffset) except? -1:
     cdef int result

pandas/_libs/src/inference.pyx

@@ -521,7 +521,7 @@ cpdef object infer_datetimelike_array(object arr):
     # convert *every* string array
     if len(objs):
         try:
-            tslib.array_to_datetime(objs, errors='raise')
+            array_to_datetime(objs, errors='raise')
             return 'datetime'
         except:
             pass

pandas/_libs/src/reduce.pyx

@@ -6,9 +6,8 @@ from distutils.version import LooseVersion
 
 is_numpy_prior_1_6_2 = LooseVersion(np.__version__) < '1.6.2'
 
-cdef _get_result_array(object obj,
-                       Py_ssize_t size,
-                       Py_ssize_t cnt):
+
+cdef _get_result_array(object obj, Py_ssize_t size, Py_ssize_t cnt):
 
     if isinstance(obj, np.ndarray) \
             or isinstance(obj, list) and len(obj) == cnt \