dianfu commented on code in PR #29002:
URL: https://github.com/apache/flink/pull/29002#discussion_r3831359012
##########
flink-python/pyflink/dataframe/tests/test_dataframe.py:
##########
@@ -1080,28 +1304,40 @@ def test_basic_functionality(self):
lambda current: current["age"] + 1,
)
.with_column("age", pf.col("age") + 1)
- .select(
- "id",
- "name",
- "age",
- age_next_year=pf.col("age_next_year"),
- inferred_int=pf.lit(2),
- inferred_string=pf.lit("x"),
- explicit_int=pf.lit(3, pf.DataType.int64()),
- explicit_large_int=pf.lit(1 << 40, pf.DataType.int64()),
- explicit_string=pf.lit("y", pf.DataType.string()),
- null_int=pf.lit(None, pf.DataType.int64()),
- null_string=pf.lit(None, pf.DataType.string()),
- non_nullable_int=pf.lit(
- 3,
- pf.DataType(TableDataTypes.BIGINT().not_null()),
- ),
+ .with_columns(
+ (pf.col("age_next_year") + 1).alias("age_in_two_years"),
+ score_percent=pf.col("score") * 100,
+ )
+ .drop("score", "city", "destination")
+ .rename({"name": "customer_name"})
+ .pipe(
Review Comment:
I think we can call `.select` directly. `pipe` is already welled tested in
test_pipe_forwards_dataframe_arguments_and_return_value.
##########
flink-python/pyflink/dataframe/tests/test_dataframe.py:
##########
@@ -1114,9 +1350,46 @@ def test_basic_functionality(self):
]
)
+ self.assertEqual(
+ result.columns,
+ [
+ "customer_name",
+ "id",
+ "age",
+ "age_next_year",
+ "age_in_two_years",
+ "score_percent",
+ "inferred_int",
+ "inferred_string",
+ "explicit_int",
+ "explicit_large_int",
+ "explicit_string",
+ "null_int",
+ "null_string",
+ "non_nullable_int",
+ ],
+ )
+ self.assertEqual(result.schema.get_field_names(), result.columns)
Review Comment:
It's not that necessary to validate this any more in IT case. It's already
covered in test_schema_exposes_ordered_metadata and
test_columns_returns_defensive_ordered_list
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