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Description
Feature request
Currently, we require the user to specify all reduce()
input columns explicitly, for the sake of performance. Let's allow a special case when no columns are specified and all items per row are passed as a single dictionary:
def udf1(base_col, sub_col):
# base_col is a single value, sub_col is a numpy array
...
# Existing behavior:
nf.reduce(udf1, "ra", "lightcurve.time")
def udf2(row):
assert isinstance(row, dict)
assert "ra" in row and "lightcurve.time" in row
# row is a dictionary: base columns are single values,
# nested columns are numpy arrays
...
# New behavior:
nf.reduce(udf2)
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Please check the following:
- I have described the purpose of the suggested change, specifying what I need the enhancement to accomplish, i.e. what problem it solves.
- I have included any relevant links, screenshots, environment information, and data relevant to implementing the requested feature, as well as pseudocode for how I want to access the new functionality.
- If I have ideas for how the new feature could be implemented, I have provided explanations and/or pseudocode and/or task lists for the steps.
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enhancementNew feature or requestNew feature or request