feat(sqlalchemy): implement clip

ibis/backends/base/sql/alchemy/registry.py

@@ -502,6 +502,22 @@ def _nth_value(t, expr):
     return sa.func.nth_value(t.translate(op.arg), t.translate(op.nth) + 1)
 
 
+def _clip(*, min_func, max_func):
+    def translate(t, expr):
+        op = expr.op()
+        arg = t.translate(op.arg)
+
+        if (upper := op.upper) is not None:
+            arg = min_func(t.translate(upper), arg)
+
+        if (lower := op.lower) is not None:
+            arg = max_func(t.translate(lower), arg)
+
+        return arg
+
+    return translate
+
+
 sqlalchemy_operation_registry: Dict[Any, Any] = {
     ops.Alias: _alias,
     ops.And: fixed_arity(operator.and_, 2),
@@ -616,6 +632,7 @@ def _nth_value(t, expr):
     ops.IdenticalTo: fixed_arity(
         sa.sql.expression.ColumnElement.is_not_distinct_from, 2
     ),
+    ops.Clip: _clip(min_func=sa.func.least, max_func=sa.func.greatest),
 }
 
 

ibis/backends/sqlite/registry.py

@@ -20,7 +20,7 @@
     varargs,
     variance_reduction,
 )
-from ibis.backends.base.sql.alchemy.registry import _gen_string_find
+from ibis.backends.base.sql.alchemy.registry import _clip, _gen_string_find
 
 operation_registry = sqlalchemy_operation_registry.copy()
 operation_registry.update(sqlalchemy_window_functions_registry)
@@ -358,5 +358,6 @@ def _time_from_hms(t, expr):
         ops.BitXor: reduction(sa.func._ibis_sqlite_bit_xor),
         ops.Degrees: unary(sa.func._ibis_sqlite_degrees),
         ops.Radians: unary(sa.func._ibis_sqlite_radians),
+        ops.Clip: _clip(min_func=sa.func.min, max_func=sa.func.max),
     }
 )

ibis/backends/tests/test_numeric.py

@@ -562,16 +562,7 @@ def test_random(con):
         ),
     ],
 )
-@pytest.mark.notimpl(
-    [
-        "duckdb",
-        "datafusion",
-        "impala",
-        "mysql",
-        "postgres",
-        "sqlite",
-    ]
-)
+@pytest.mark.notimpl(["datafusion", "impala"])
 def test_clip(alltypes, df, ibis_func, pandas_func):
     result = ibis_func(alltypes.int_col).execute()
     expected = pandas_func(df.int_col).astype(result.dtype)