kylebarron commented on code in PR #825:
URL: https://github.com/apache/datafusion-python/pull/825#discussion_r1731868278
##########
src/dataframe.rs:
##########
@@ -539,3 +579,78 @@ fn print_dataframe(py: Python, df: DataFrame) ->
PyResult<()> {
print.call1((result,))?;
Ok(())
}
+
+fn project_schema(from_schema: Schema, to_schema: Schema) -> Result<Schema,
ArrowError> {
+ let merged_schema = Schema::try_merge(vec![from_schema,
to_schema.clone()])?;
+
+ let project_indices: Vec<usize> = to_schema
+ .fields
+ .iter()
+ .map(|field| field.name())
+ .filter_map(|field_name| merged_schema.index_of(field_name).ok())
+ .collect();
+
+ merged_schema.project(&project_indices)
+}
+
+fn record_batch_into_schema(
Review Comment:
Well there is `cast`. Cast works on struct arrays, so you could make a
simple wrapper around `cast` to work on `RecordBatch` by creating a struct
array from the record batch. [This is what I do in
pyo3-arrow](https://github.com/kylebarron/arro3/blob/c1cdb51527cb769694a4a400a8064a5e5a47290a/pyo3-arrow/src/ffi/to_python/utils.rs#L85-L87).
The main difference is that cast doesn't _also_ project. It's not clear to
me whether the PyCapsule Interface intends to support projection or not. I
don't think anyone has asked.
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