jim-ngoo commented on issue #1934:
URL:
https://github.com/apache/iceberg-python/issues/1934#issuecomment-2865539528
> [@jim-ngoo](https://github.com/jim-ngoo) so from Dx perspective we should
just pass in a pydantic schema as e.g. `catalog.create_table('mytable',
schema=MyPydanticModel)`?
potatochipcoconut commented on issue #1934:
URL:
https://github.com/apache/iceberg-python/issues/1934#issuecomment-2851356331
@jim-ngoo so from Dx perspective we should just pass in a pydantic schema as
e.g. `catalog.create_table('mytable', schema=MyPydanticModel)`? That would be
nice
--
jim-ngoo commented on issue #1934:
URL:
https://github.com/apache/iceberg-python/issues/1934#issuecomment-2846711694
> Type mapping is notoriously difficult. Since we already support
bidirectional interchange between pyarrow schema and iceberg schema, i think it
would be easier if we can m
potatochipcoconut commented on issue #1934:
URL:
https://github.com/apache/iceberg-python/issues/1934#issuecomment-2831447185
@choucavalier started playing with your lib and seems like generally what I
was looking for, ran into issues around UUID (opened issues there and duckdb).
Loc
choucavalier commented on issue #1934:
URL:
https://github.com/apache/iceberg-python/issues/1934#issuecomment-2817036701
Pydantic, TypedDict, dataclasses, JSON schema, etc. There are many formats
that could potentially generate iceberg schemas. It's not entirely obvious to
me that pyiceber
kevinjqliu commented on issue #1934:
URL:
https://github.com/apache/iceberg-python/issues/1934#issuecomment-2816805023
Type mapping is notoriously difficult. Since we already support
bidirectional interchange between pyarrow schema and iceberg schema, i think it
would be easier if we can m
potatochipcoconut commented on issue #1934:
URL:
https://github.com/apache/iceberg-python/issues/1934#issuecomment-2816728751
@choucavalier agree it seems like a natural enhancement, possibly should be
available directly through pyiceberg?
--
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choucavalier commented on issue #1934:
URL:
https://github.com/apache/iceberg-python/issues/1934#issuecomment-2816600466
You can look at https://github.com/simw/pydantic-to-pyarrow for inspiration
I think this is the future. being able to manipulate / validate objects
individually, t
potatochipcoconut commented on issue #1934:
URL:
https://github.com/apache/iceberg-python/issues/1934#issuecomment-2816103494
Came up with naive attempt, open to feedback. Not sure how it would handle
e.g. int vs long, float vs double, etc
```
import builtins
import datetime
imp
potatochipcoconut opened a new issue, #1934:
URL: https://github.com/apache/iceberg-python/issues/1934
### Feature Request / Improvement
How difficult or feasible would it be to enable support for native Pydantic
schemas that automatically map to the underlying pyiceberg types etc?
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