ahmedabu98 commented on issue #34766:
URL: https://github.com/apache/beam/issues/34766#issuecomment-2836048790
Just gave it a short in PyIceberg with the following code:
```python
from pyiceberg.catalog import Catalog
from pyiceberg.catalog.memory import InMemoryCatalog
from pyiceberg.schema import Schema
from pyiceberg.schema import NestedField
from pyiceberg.schema import LongType
from pyiceberg.schema import StructType
from pyiceberg.schema import StringType
TEST_TABLE_SCHEMA = Schema(
NestedField(1, "x", LongType(), required=True),
NestedField(4, "nested", StructType(
NestedField(5, "bar", StringType()),
NestedField(6, "foo", StringType()),
NestedField(7, "baz", StringType()),
)),
NestedField(2, "y", LongType(), doc="comment", required=True),
NestedField(3, "z", LongType(), required=True),
)
catalog: Catalog = InMemoryCatalog("inmemory")
catalog.create_namespace("dataset")
print("xxx schema:", catalog.create_table(
identifier="dataset.table",
schema=TEST_TABLE_SCHEMA,
).schema())
```
Output:
```
xxx schema: table {
1: x: required long
2: nested: optional struct<5: bar: optional string, 6: foo: optional
string, 7: baz: optional string>
3: y: required long (comment)
4: z: required long
}
```
So Python also does a breadth-first approach 🤔
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