sklam · May 26, 2022 · Feb 11, 2022 · Feb 11, 2022 · Feb 15, 2022 · Feb 15, 2022
diff --git a/numba/core/typing/builtins.py b/numba/core/typing/builtins.py
@@ -881,7 +881,7 @@ class MinMaxBase(AbstractTemplate):
 
     def _unify_minmax(self, tys):
         for ty in tys:
-            if not isinstance(ty, types.Number):
+            if not isinstance(ty, (types.Number, types.NPDatetime, types.NPTimedelta)):
                 return
         return self.context.unify_types(*tys)
 
@@ -1103,8 +1103,8 @@ class MinValInfer(AbstractTemplate):
     def generic(self, args, kws):
         assert not kws
         assert len(args) == 1
-        assert isinstance(args[0], (types.DType, types.NumberClass))
-        return signature(args[0].dtype, *args)
+        if isinstance(args[0], (types.DType, types.NumberClass)):
+            return signature(args[0].dtype, *args)
 
 
 #------------------------------------------------------------------------------

diff --git a/numba/core/typing/npdatetime.py b/numba/core/typing/npdatetime.py
@@ -266,3 +266,20 @@ class DatetimeCmpGt(DatetimeCmpOp):
 @infer_global(operator.ge)
 class DatetimeCmpGE(DatetimeCmpOp):
     key = operator.ge
+
+
+@infer_global(npdatetime_helpers.datetime_minimum)
+@infer_global(npdatetime_helpers.datetime_maximum)
+class DatetimeMinMax(AbstractTemplate):
+    def generic(self, args, kws):
+        assert not kws
+        assert len(args) == 2
+        error_msg = "DatetimeMinMax requires both arguments to be NPDatetime type or both arguments to be NPTimedelta types"
+        assert isinstance(args[0], (types.NPDatetime, types.NPTimedelta)), error_msg
+        if isinstance(args[0], types.NPDatetime):
+            if not isinstance(args[1], types.NPDatetime):
+                raise TypeError(error_msg)
+        else:
+            if not isinstance(args[1], types.NPTimedelta):
+                raise TypeError(error_msg)
+        return signature(args[0], *args)
diff --git a/numba/cpython/builtins.py b/numba/cpython/builtins.py
@@ -481,13 +481,14 @@ def get_type_min_value(typ):
 @lower_builtin(get_type_min_value, types.DType)
 def lower_get_type_min_value(context, builder, sig, args):
     typ = sig.args[0].dtype
-    bw = typ.bitwidth
 
     if isinstance(typ, types.Integer):
+        bw = typ.bitwidth
         lty = ir.IntType(bw)
         val = typ.minval
         res = ir.Constant(lty, val)
     elif isinstance(typ, types.Float):
+        bw = typ.bitwidth
         if bw == 32:
             lty = ir.FloatType()
         elif bw == 64:
@@ -496,19 +497,25 @@ def lower_get_type_min_value(context, builder, sig, args):
             raise NotImplementedError("llvmlite only supports 32 and 64 bit floats")
         npty = getattr(np, 'float{}'.format(bw))
         res = ir.Constant(lty, -np.inf)
+    elif isinstance(typ, (types.NPDatetime, types.NPTimedelta)):
+        bw = 64
+        lty = ir.IntType(bw)
+        val = types.int64.minval + 1 # minval is NaT, so minval + 1 is the smallest value
+        res = ir.Constant(lty, val)
     return impl_ret_untracked(context, builder, lty, res)
 
 @lower_builtin(get_type_max_value, types.NumberClass)
 @lower_builtin(get_type_max_value, types.DType)
 def lower_get_type_max_value(context, builder, sig, args):
     typ = sig.args[0].dtype
-    bw = typ.bitwidth
 
     if isinstance(typ, types.Integer):
+        bw = typ.bitwidth
         lty = ir.IntType(bw)
         val = typ.maxval
         res = ir.Constant(lty, val)
     elif isinstance(typ, types.Float):
+        bw = typ.bitwidth
         if bw == 32:
             lty = ir.FloatType()
         elif bw == 64:
@@ -517,6 +524,11 @@ def lower_get_type_max_value(context, builder, sig, args):
             raise NotImplementedError("llvmlite only supports 32 and 64 bit floats")
         npty = getattr(np, 'float{}'.format(bw))
         res = ir.Constant(lty, np.inf)
+    elif isinstance(typ, (types.NPDatetime, types.NPTimedelta)):
+        bw = 64
+        lty = ir.IntType(bw)
+        val = types.int64.maxval
+        res = ir.Constant(lty, val)
     return impl_ret_untracked(context, builder, lty, res)
 
 # -----------------------------------------------------------------------------

diff --git a/numba/np/npdatetime.py b/numba/np/npdatetime.py
@@ -847,3 +847,9 @@ def impl(x):
                 return np.int64(-2)
             return np.int64(x)
     return impl
+
+
+lower_builtin(npdatetime_helpers.datetime_minimum, types.NPDatetime, types.NPDatetime)(datetime_minimum_impl)
+lower_builtin(npdatetime_helpers.datetime_minimum, types.NPTimedelta, types.NPTimedelta)(datetime_minimum_impl)
+lower_builtin(npdatetime_helpers.datetime_maximum, types.NPDatetime, types.NPDatetime)(datetime_maximum_impl)
+lower_builtin(npdatetime_helpers.datetime_maximum, types.NPTimedelta, types.NPTimedelta)(datetime_maximum_impl)
diff --git a/numba/np/npdatetime_helpers.py b/numba/np/npdatetime_helpers.py
@@ -202,3 +202,11 @@ def get_best_unit(unit_a, unit_b):
     if b > a:
         return unit_b
     return unit_a
+
+
+def datetime_minimum(a, b):
+    pass
+
+
+def datetime_maximum(a, b):
+    pass
@@ -24,13 +24,16 @@
 from contextlib import contextmanager
 import operator
 
+from llvmlite import ir as lir
+from numba.core.imputils import impl_ret_untracked
 import numba.core.ir
 from numba.core import types, typing, utils, errors, ir, analysis, postproc, rewrites, typeinfer, config, ir_utils
 from numba import prange, pndindex
-from numba.np.numpy_support import as_dtype
+from numba.np.npdatetime_helpers import datetime_minimum, datetime_maximum
+from numba.np.numpy_support import as_dtype, numpy_version
 from numba.core.typing.templates import infer_global, AbstractTemplate
 from numba.stencils.stencilparfor import StencilPass
-from numba.core.extending import register_jitable
+from numba.core.extending import register_jitable, lower_builtin
 
 from numba.core.ir_utils import (
     mk_unique_var,
@@ -121,20 +124,31 @@ class internal_prange(object):
     def __new__(cls, *args):
         return range(*args)
 
+
 def min_parallel_impl(return_type, arg):
     # XXX: use prange for 1D arrays since pndindex returns a 1-tuple instead of
     # integer. This causes type and fusion issues.
     if arg.ndim == 0:
         def min_1(in_arr):
             return in_arr[()]
     elif arg.ndim == 1:
-        def min_1(in_arr):
-            numba.parfors.parfor.init_prange()
-            min_checker(len(in_arr))
-            val = numba.cpython.builtins.get_type_max_value(in_arr.dtype)
-            for i in numba.parfors.parfor.internal_prange(len(in_arr)):
-                val = min(val, in_arr[i])
-            return val
+        if isinstance(arg.dtype, (types.NPDatetime, types.NPTimedelta)):
+            # NaT is always returned if it is in the array
+            def min_1(in_arr):
+                numba.parfors.parfor.init_prange()
+                min_checker(len(in_arr))
+                val = numba.cpython.builtins.get_type_max_value(in_arr.dtype)
+                for i in numba.parfors.parfor.internal_prange(len(in_arr)):
+                    val = datetime_minimum(val, in_arr[i])
+                return val
+        else:
+            def min_1(in_arr):
+                numba.parfors.parfor.init_prange()
+                min_checker(len(in_arr))
+                val = numba.cpython.builtins.get_type_max_value(in_arr.dtype)
+                for i in numba.parfors.parfor.internal_prange(len(in_arr)):
+                    val = min(val, in_arr[i])
+                return val
     else:
         def min_1(in_arr):
             numba.parfors.parfor.init_prange()
@@ -150,13 +164,23 @@ def max_parallel_impl(return_type, arg):
         def max_1(in_arr):
             return in_arr[()]
     elif arg.ndim == 1:
-        def max_1(in_arr):
-            numba.parfors.parfor.init_prange()
-            max_checker(len(in_arr))
-            val = numba.cpython.builtins.get_type_min_value(in_arr.dtype)
-            for i in numba.parfors.parfor.internal_prange(len(in_arr)):
-                val = max(val, in_arr[i])
-            return val
+        if isinstance(arg.dtype, (types.NPDatetime, types.NPTimedelta)):
+            # NaT is always returned if it is in the array
+            def max_1(in_arr):
+                numba.parfors.parfor.init_prange()
+                max_checker(len(in_arr))
+                val = numba.cpython.builtins.get_type_min_value(in_arr.dtype)
+                for i in numba.parfors.parfor.internal_prange(len(in_arr)):
+                    val = datetime_maximum(val, in_arr[i])
+                return val
+        else:
+            def max_1(in_arr):
+                numba.parfors.parfor.init_prange()
+                max_checker(len(in_arr))
+                val = numba.cpython.builtins.get_type_min_value(in_arr.dtype)
+                for i in numba.parfors.parfor.internal_prange(len(in_arr)):
+                    val = max(val, in_arr[i])
+                return val
     else:
         def max_1(in_arr):
             numba.parfors.parfor.init_prange()
@@ -3608,7 +3632,12 @@ def supported_reduction(x, func_ir):
         return True
     if x.op == 'call':
         callname = guard(find_callname, func_ir, x)
-        if callname == ('max', 'builtins') or callname == ('min', 'builtins'):
+        if callname in [
+            ('max', 'builtins'),
+            ('min', 'builtins'),
+            ('datetime_minimum', 'numba.np.npdatetime_helpers'),
+            ('datetime_maximum', 'numba.np.npdatetime_helpers'),
+        ]:
             return True
     return False