Separate out strptime.pyx from tslib (pandas-dev#17342)

Author: jbrockmendel

pandas/_libs/__init__.py

@@ -1,3 +1,4 @@
+# -*- coding: utf-8 -*-
 # flake8: noqa
 
 from .tslib import iNaT, NaT, Timestamp, Timedelta, OutOfBoundsDatetime

pandas/_libs/src/datetime.pxd

@@ -94,6 +94,7 @@ 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
@@ -161,3 +162,17 @@ cdef inline int64_t _date_to_datetime64(object val,
     dts.hour = dts.min = dts.sec = dts.us = 0
     dts.ps = dts.as = 0
     return pandas_datetimestruct_to_datetime(PANDAS_FR_ns, dts)
+
+
+cdef inline bint check_dts_bounds(pandas_datetimestruct *dts):
+    """Returns True if an error needs to be raised"""
+    cdef:
+        bint error = False
+
+    if (dts.year <= 1677 and
+            cmp_pandas_datetimestruct(dts, &_NS_MIN_DTS) == -1):
+        error = True
+    elif (dts.year >= 2262 and
+          cmp_pandas_datetimestruct(dts, &_NS_MAX_DTS) == 1):
+        error = True
+    return error

pandas/_libs/src/datetime/np_datetime.c

@@ -40,6 +40,12 @@ This file is derived from NumPy 1.7. See NUMPY_LICENSE.txt
 #define PyInt_AsUnsignedLongLongMask PyLong_AsUnsignedLongLongMask
 #endif
 
+const pandas_datetimestruct _NS_MIN_DTS = {
+    1677, 9, 21, 0, 12, 43, 145225, 0, 0};
+const pandas_datetimestruct _NS_MAX_DTS = {
+    2262, 4, 11, 23, 47, 16, 854775, 807000, 0};
+
+
 const int days_per_month_table[2][12] = {
     {31, 28, 31, 30, 31, 30, 31, 31, 30, 31, 30, 31},
     {31, 29, 31, 30, 31, 30, 31, 31, 30, 31, 30, 31}};

pandas/_libs/src/datetime/np_datetime.h

@@ -54,6 +54,9 @@ typedef struct {
     int num;
 } pandas_datetime_metadata;
 
+extern const pandas_datetimestruct _NS_MIN_DTS;
+extern const pandas_datetimestruct _NS_MAX_DTS;
+
 // stuff pandas needs
 // ----------------------------------------------------------------------------