syun64 commented on code in PR #921:
URL: https://github.com/apache/iceberg-python/pull/921#discussion_r1676966897
##########
tests/integration/test_add_files.py:
##########
@@ -501,14 +501,11 @@ def test_add_files_fails_on_schema_mismatch(spark:
SparkSession, session_catalog
)
expected = """Mismatch in fields:
-┏━━━━┳━━━━━━━━━━━━━━━━━━━━━━━━━━┳━━━━━━━━━━━━━━━━━━━━━━━━━━┓
-┃ ┃ Table field ┃ Dataframe field ┃
-┡━━━━╇━━━━━━━━━━━━━━━━━━━━━━━━━━╇━━━━━━━━━━━━━━━━━━━━━━━━━━┩
-│ ✅ │ 1: foo: optional boolean │ 1: foo: optional boolean │
-| ✅ │ 2: bar: optional string │ 2: bar: optional string │
-│ ❌ │ 3: baz: optional int │ 3: baz: optional string │
-│ ✅ │ 4: qux: optional date │ 4: qux: optional date │
-└────┴──────────────────────────┴──────────────────────────┘
+┏━━━━━━━━━━━━┳━━━━━━━━━━┳━━━━━━━━━━━━━━┳━━━━━━━━━━━━━━━━━┓
Review Comment:
I opted for this approach because I wanted to group the Extra Fields in the
dataframe also into the table. But if we are taking the approach of using the
`name_mapping` to generate the Iceberg Schema with consistent IDs after first
checking that there are no extra fields, I think we can go back to the old way
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