diff --git a/python/triton/language/extern.py b/python/triton/language/extern.py
index 98e42100d..6019726ef 100644
--- a/python/triton/language/extern.py
+++ b/python/triton/language/extern.py
@@ -65,9 +65,9 @@ def elementwise(lib_name: str, lib_path: str, args: list, arg_type_symbol_dict:
     if not all_scalar:
         broadcast_arg = dispatch_args[0]
         # Get the broadcast shape over all the arguments
-        for i in range(len(dispatch_args)):
+        for i, item in enumerate(dispatch_args):
             _, broadcast_arg = semantic.binary_op_type_checking_impl(
-                dispatch_args[i], broadcast_arg, _builder)
+                item, broadcast_arg, _builder)
         # Change the shape of each argument based on the broadcast shape
         for i in range(len(dispatch_args)):
             dispatch_args[i], _ = semantic.binary_op_type_checking_impl(
diff --git a/python/triton/language/semantic.py b/python/triton/language/semantic.py
index af51da74e..67245037b 100644
--- a/python/triton/language/semantic.py
+++ b/python/triton/language/semantic.py
@@ -533,10 +533,10 @@ def broadcast_impl_shape(input: tl.tensor,
         raise ValueError(f"Cannot broadcast, rank mismatch: {src_shape}, {shape}")
     if shape == src_shape:
         return input
-    for i in range(len(src_shape)):
-        if shape[i] != src_shape[i] and src_shape[i] != 1:
+    for i, item in enumerate(src_shape):
+        if shape[i] != item and item != 1:
             raise ValueError(f"Cannot broadcast, the expanded size of the tensor ({shape[i]})"
-                             f" must match the existing size ({src_shape[i]}) at non-singleton dimension"
+                             f" must match the existing size ({item}) at non-singleton dimension"
                              f" {i}: {src_shape}, {shape}")
     ret_ty = tl.block_type(input.type.scalar, shape)
     return tl.tensor(builder.create_broadcast(input.handle, shape), ret_ty)
@@ -576,8 +576,7 @@ def broadcast_impl_value(lhs: tl.tensor,
         assert len(rhs_shape) == len(lhs_shape)
 
         ret_shape = []
-        for i in range(len(lhs_shape)):
-            left = lhs_shape[i]
+        for i, left in enumerate(lhs_shape):
             right = rhs_shape[i]
             if left == 1:
                 ret_shape.append(right)