I came to a similar solution to a similar problem. I deal with a lot of CSV files from many different sources and they are often malformed.
HOwever, I just have success/failure. Maybe you should  make SuccessWithWarnings a subclass of success, or getting rid of it altogether making the warnings optional.
I was thinking of making this cleaning/conforming library open source if you're interested.

R.

2015-10-15 5:28 GMT-07:00 Antonio Murgia <antonio.murgia2@studio.unibo.it>:
Hello,
I looked around on the web and I couldn’t find any way to deal in a structured way with malformed/faulty records during computation. All I was able to find was the flatMap/Some/None technique + logging.
I’m facing this problem because I have a processing algorithm that extracts more than one value from each record, but can fail in extracting one of those multiple values, and I want to keep track of them. Logging is not feasible because this “warning” happens so frequently that the logs would become overwhelming and impossibile to read.
Since I have 3 different possible outcomes from my processing I modeled it with this class hierarchy:
That holds result and/or warnings.
Since Result implements Traversable it can be used in a flatMap, discarding all warnings and failure results, in the other hand, if we want to keep track of warnings, we can elaborate them and output them if we need.

Kind Regards
#A.M.



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"Good judgment comes from experience.
Experience comes from bad judgment"
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