feat: support array output in remote_function
#1057
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This is feature request to support use cases like creating custom feature vectors, embeddings etc.
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…tr array outputs
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bigframes/session/__init__.py
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| output_type (type, default None): | ||
| Python type equivalent to the BigQuery return type. This is used | ||
| to coerce the return value of the BigQuery function to BigFrames | ||
| type. For example, if the BigQuery function returns a JSON | ||
| serialized array of integers such as "[1, 2, 3]", then user can | ||
| set `output_type=list[int]` to read it as array of integers [1, 2, 3]. |
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I don't know if this makes sense for existing bq functions. Its more helpful for local python functions where the output type is otherwise ambiguous. Users should call astype or similar methods to explicitly coerce the result.
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The place where it would be useful is reading back a remote function that was created using bigframes. When the user used it after creating, their code didn't have to call astype, so we want to give them a way to have that code continue to work after reading back. The test test_df_apply_axis_1_array_output captures this usecase.
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Remove this param in the latest change, PTAL
| ibis_output_type = ibis_signature.output_type | ||
| if output_type is not None: | ||
| if not isinstance(ibis_signature.output_type, ibis.expr.datatypes.String): | ||
| raise TypeError( |
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@tswast mentioned offline: "I would find that to be pretty annoying as a user. Better to make sure it matches and maybe warn that it's not necessary"
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Removed output_type from read_gbq_function, PTAL
…tput_type in read_gbq_function
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remote_function: screen/5rMtCZVaUYKdqxPSeries.apply: screen/9HkKMuWxMvbbPgfDataFrame.apply: screen/BoXH9A7d4hGpETuFixes internal issue 298876217 🦕