manual edit

Author: chelsea-lin

bigframes/core/compile/sqlglot/expressions/unary_compiler.py

@@ -304,9 +304,7 @@ def _(op: ops.base_ops.UnaryOp, expr: TypedExpr) -> sge.Expression:
 
 @UNARY_OP_REGISTRATION.register(ops.iso_day_op)
 def _(op: ops.base_ops.UnaryOp, expr: TypedExpr) -> sge.Expression:
-    return sge.Extract(
-        this=sge.Identifier(this="DAYOFWEEK"), expression=expr.expr
-    ) + sge.convert(1)
+    return sge.Extract(this=sge.Identifier(this="DAYOFWEEK"), expression=expr.expr)
 
 
 @UNARY_OP_REGISTRATION.register(ops.iso_week_op)

tests/unit/core/compile/sqlglot/expressions/snapshots/test_unary_compiler/test_iso_day/out.sql

@@ -5,7 +5,7 @@ WITH `bfcte_0` AS (
 ), `bfcte_1` AS (
   SELECT
     *,
-    EXTRACT(DAYOFWEEK FROM `bfcol_0`) + 1 AS `bfcol_1`
+    EXTRACT(DAYOFWEEK FROM `bfcol_0`) AS `bfcol_1`
   FROM `bfcte_0`
 )
 SELECT

tests/unit/core/compile/sqlglot/expressions/test_unary_compiler.py

@@ -93,6 +93,7 @@ def test_capitalize(scalar_types_df: bpd.DataFrame, snapshot):
 def test_ceil(scalar_types_df: bpd.DataFrame, snapshot):
     bf_df = scalar_types_df[["float64_col"]]
     sql = _apply_unary_op(bf_df, ops.ceil_op, "float64_col")
+
     snapshot.assert_match(sql, "out.sql")
 
 
@@ -197,72 +198,84 @@ def test_hash(scalar_types_df: bpd.DataFrame, snapshot):
 def test_hour(scalar_types_df: bpd.DataFrame, snapshot):
     bf_df = scalar_types_df[["timestamp_col"]]
     sql = _apply_unary_op(bf_df, ops.hour_op, "timestamp_col")
+
     snapshot.assert_match(sql, "out.sql")
 
 
 def test_invert(scalar_types_df: bpd.DataFrame, snapshot):
     bf_df = scalar_types_df[["int64_col"]]
     sql = _apply_unary_op(bf_df, ops.invert_op, "int64_col")
+
     snapshot.assert_match(sql, "out.sql")
 
 
 def test_isalnum(scalar_types_df: bpd.DataFrame, snapshot):
     bf_df = scalar_types_df[["string_col"]]
     sql = _apply_unary_op(bf_df, ops.isalnum_op, "string_col")
+
     snapshot.assert_match(sql, "out.sql")
 
 
 def test_isalpha(scalar_types_df: bpd.DataFrame, snapshot):
     bf_df = scalar_types_df[["string_col"]]
     sql = _apply_unary_op(bf_df, ops.isalpha_op, "string_col")
+
     snapshot.assert_match(sql, "out.sql")
 
 
 def test_isdecimal(scalar_types_df: bpd.DataFrame, snapshot):
     bf_df = scalar_types_df[["string_col"]]
     sql = _apply_unary_op(bf_df, ops.isdecimal_op, "string_col")
+
     snapshot.assert_match(sql, "out.sql")
 
 
 def test_isdigit(scalar_types_df: bpd.DataFrame, snapshot):
     bf_df = scalar_types_df[["string_col"]]
     sql = _apply_unary_op(bf_df, ops.isdigit_op, "string_col")
+
     snapshot.assert_match(sql, "out.sql")
 
 
 def test_islower(scalar_types_df: bpd.DataFrame, snapshot):
     bf_df = scalar_types_df[["string_col"]]
     sql = _apply_unary_op(bf_df, ops.islower_op, "string_col")
+
     snapshot.assert_match(sql, "out.sql")
 
 
 def test_isnumeric(scalar_types_df: bpd.DataFrame, snapshot):
     bf_df = scalar_types_df[["string_col"]]
     sql = _apply_unary_op(bf_df, ops.isnumeric_op, "string_col")
+
     snapshot.assert_match(sql, "out.sql")
 
 
 def test_isspace(scalar_types_df: bpd.DataFrame, snapshot):
     bf_df = scalar_types_df[["string_col"]]
     sql = _apply_unary_op(bf_df, ops.isspace_op, "string_col")
+
     snapshot.assert_match(sql, "out.sql")
 
 
 def test_isupper(scalar_types_df: bpd.DataFrame, snapshot):
     bf_df = scalar_types_df[["string_col"]]
     sql = _apply_unary_op(bf_df, ops.isupper_op, "string_col")
+
     snapshot.assert_match(sql, "out.sql")
 
 
 def test_iso_day(scalar_types_df: bpd.DataFrame, snapshot):
     bf_df = scalar_types_df[["timestamp_col"]]
     sql = _apply_unary_op(bf_df, ops.iso_day_op, "timestamp_col")
+
     snapshot.assert_match(sql, "out.sql")
 
 
 def test_iso_week(scalar_types_df: bpd.DataFrame, snapshot):
     bf_df = scalar_types_df[["timestamp_col"]]
     sql = _apply_unary_op(bf_df, ops.iso_week_op, "timestamp_col")
+
     snapshot.assert_match(sql, "out.sql")