Allow DFS to take in strings or datetime values into cutoff_time argument#2147
Allow DFS to take in strings or datetime values into cutoff_time argument#2147
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@@ Coverage Diff @@
## main #2147 +/- ##
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Coverage 99.21% 99.22%
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Files 143 143
Lines 16917 16937 +20
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+ Hits 16785 16805 +20
Misses 132 132
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featuretools/synthesis/dfs.py
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| entityset = EntitySet("dfs", dataframes, relationships) | ||
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| if isinstance(cutoff_time, str): | ||
| cutoff_time = dateutil.parser.parse(cutoff_time) |
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What if this raises a ParserError or OverflowError?
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Thanks. I added handling for parseutil's ParserError and a plain OverflowError (looks like parseutil doesn't have a OverflowError defined, as far as I can tell). In the event of a ParserError is it best to just raise a ValueError?
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Not sure. @thehomebrewnerd any clue on what we usually do here?
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We have tended to use pandas.to_datetime a lot for these types of conversions. Is there a reason to move away from that here and use dateutil.parser.parse instead?
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We also probably need to think about situations where we have a numeric time index instead of a datetime time index. Do we also want to handle the conversion for those cases? "100" -> 100?
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I used dateutil.parser.parse only because it was in the issue description; I can change it to pandas.to_datetime right now. Should I just re-raise if throws an exception?
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@sbadithe My suggestion would be to catch the pandas exception and raise an error with a more meaningful message alerting the user that they have supplied an invalid cutoff time value.
sbadithe
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Merge branch 'dfs-cutoff_time-should-take-datetime-string' of https://github.com/alteryx/featuretools into dfs-cutoff_time-should-take-datetime-string
gsheni
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gsheni
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4 participants
Fixes #2014
Makes it possible for users to pass in strings, or datetime values into dfs's
cutoff_timeargument