BLD: Fix IntervalTree build warnings (#30560)

Author: jschendel

pandas/_libs/intervaltree.pxi.in

@@ -6,12 +6,20 @@ WARNING: DO NOT edit .pxi FILE directly, .pxi is generated from .pxi.in
 
 from pandas._libs.algos import is_monotonic
 
-ctypedef fused scalar_t:
-    float64_t
-    float32_t
+ctypedef fused int_scalar_t:
     int64_t
     int32_t
+    float64_t
+    float32_t
+
+ctypedef fused uint_scalar_t:
     uint64_t
+    float64_t
+    float32_t
+
+ctypedef fused scalar_t:
+    int_scalar_t
+    uint_scalar_t
 
 # ----------------------------------------------------------------------
 # IntervalTree
@@ -128,7 +136,12 @@ cdef class IntervalTree(IntervalMixin):
         result = Int64Vector()
         old_len = 0
         for i in range(len(target)):
-            self.root.query(result, target[i])
+            try:
+                self.root.query(result, target[i])
+            except OverflowError:
+                # overflow -> no match, which is already handled below
+                pass
+
             if result.data.n == old_len:
                 result.append(-1)
             elif result.data.n > old_len + 1:
@@ -150,7 +163,12 @@ cdef class IntervalTree(IntervalMixin):
         missing = Int64Vector()
         old_len = 0
         for i in range(len(target)):
-            self.root.query(result, target[i])
+            try:
+                self.root.query(result, target[i])
+            except OverflowError:
+                # overflow -> no match, which is already handled below
+                pass
+
             if result.data.n == old_len:
                 result.append(-1)
                 missing.append(i)
@@ -202,19 +220,26 @@ for dtype in ['float32', 'float64', 'int32', 'int64', 'uint64']:
         ('neither', '<', '<')]:
         cmp_left_converse = '<' if cmp_left == '<=' else '<='
         cmp_right_converse = '<' if cmp_right == '<=' else '<='
+        if dtype.startswith('int'):
+            fused_prefix = 'int_'
+        elif dtype.startswith('uint'):
+            fused_prefix = 'uint_'
+        elif dtype.startswith('float'):
+            fused_prefix = ''
         nodes.append((dtype, dtype.title(),
                       closed, closed.title(),
                       cmp_left,
                       cmp_right,
                       cmp_left_converse,
-                      cmp_right_converse))
+                      cmp_right_converse,
+                      fused_prefix))
 
 }}
 
 NODE_CLASSES = {}
 
 {{for dtype, dtype_title, closed, closed_title, cmp_left, cmp_right,
-      cmp_left_converse, cmp_right_converse in nodes}}
+      cmp_left_converse, cmp_right_converse, fused_prefix in nodes}}
 
 cdef class {{dtype_title}}Closed{{closed_title}}IntervalNode:
     """Non-terminal node for an IntervalTree
@@ -317,7 +342,7 @@ cdef class {{dtype_title}}Closed{{closed_title}}IntervalNode:
     @cython.wraparound(False)
     @cython.boundscheck(False)
     @cython.initializedcheck(False)
-    cpdef query(self, Int64Vector result, scalar_t point):
+    cpdef query(self, Int64Vector result, {{fused_prefix}}scalar_t point):
         """Recursively query this node and its sub-nodes for intervals that
         overlap with the query point.
         """

pandas/tests/indexes/interval/test_interval_tree.py

@@ -63,6 +63,17 @@ def test_get_indexer(self, tree):
         ):
             tree.get_indexer(np.array([3.0]))
 
+    @pytest.mark.parametrize(
+        "dtype, target_value", [("int64", 2 ** 63 + 1), ("uint64", -1)]
+    )
+    def test_get_indexer_overflow(self, dtype, target_value):
+        left, right = np.array([0, 1], dtype=dtype), np.array([1, 2], dtype=dtype)
+        tree = IntervalTree(left, right)
+
+        result = tree.get_indexer(np.array([target_value]))
+        expected = np.array([-1], dtype="intp")
+        tm.assert_numpy_array_equal(result, expected)
+
     def test_get_indexer_non_unique(self, tree):
         indexer, missing = tree.get_indexer_non_unique(np.array([1.0, 2.0, 6.5]))
 
@@ -82,6 +93,21 @@ def test_get_indexer_non_unique(self, tree):
         expected = np.array([2], dtype="intp")
         tm.assert_numpy_array_equal(result, expected)
 
+    @pytest.mark.parametrize(
+        "dtype, target_value", [("int64", 2 ** 63 + 1), ("uint64", -1)]
+    )
+    def test_get_indexer_non_unique_overflow(self, dtype, target_value):
+        left, right = np.array([0, 2], dtype=dtype), np.array([1, 3], dtype=dtype)
+        tree = IntervalTree(left, right)
+        target = np.array([target_value])
+
+        result_indexer, result_missing = tree.get_indexer_non_unique(target)
+        expected_indexer = np.array([-1], dtype="intp")
+        tm.assert_numpy_array_equal(result_indexer, expected_indexer)
+
+        expected_missing = np.array([0], dtype="intp")
+        tm.assert_numpy_array_equal(result_missing, expected_missing)
+
     def test_duplicates(self, dtype):
         left = np.array([0, 0, 0], dtype=dtype)
         tree = IntervalTree(left, left + 1)