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Posted to issues@spark.apache.org by "Josh Rosen (JIRA)" <ji...@apache.org> on 2015/04/20 19:45:59 UTC

[jira] [Updated] (SPARK-6661) Python type errors should print type, not object

     [ https://issues.apache.org/jira/browse/SPARK-6661?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel ]

Josh Rosen updated SPARK-6661:
------------------------------
    Assignee: Elisey Zanko

> Python type errors should print type, not object
> ------------------------------------------------
>
>                 Key: SPARK-6661
>                 URL: https://issues.apache.org/jira/browse/SPARK-6661
>             Project: Spark
>          Issue Type: Bug
>          Components: MLlib, PySpark
>    Affects Versions: 1.3.0
>            Reporter: Joseph K. Bradley
>            Assignee: Elisey Zanko
>            Priority: Minor
>             Fix For: 1.4.0
>
>
> In MLlib PySpark, we sometimes test the type of an object and print an error if the object is of the wrong type.  E.g.:
> [https://github.com/apache/spark/blob/f084c5de14eb10a6aba82a39e03e7877926ebb9e/python/pyspark/mllib/regression.py#L173]
> These checks should print the type, not the actual object.  E.g., if the object cannot be converted to a string, then the check linked above will give a warning like this:
> {code}
> TypeError: not all arguments converted during string formatting
> {code}
> ...which is weird for the user.
> There may be other places in the codebase where this is an issue, so we need to check through and verify.



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