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https://issues.apache.org/jira/browse/SPARK-6218?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=14590791#comment-14590791
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Shivaram Venkataraman commented on SPARK-6218:
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[~nchammas] I just updated the target version to 1.5.0 for this. FWIW I don't
have a strong opinion about which argument parsing library we use as long we
can maintain compatibility with Python 2.6
> Upgrade spark-ec2 from optparse to argparse
> -------------------------------------------
>
> Key: SPARK-6218
> URL: https://issues.apache.org/jira/browse/SPARK-6218
> Project: Spark
> Issue Type: Improvement
> Components: EC2
> Reporter: Nicholas Chammas
> Priority: Minor
>
> spark-ec2 [currently uses
> optparse|https://github.com/apache/spark/blob/55b1b32dc8b9b25deea8e5864b53fe802bb92741/ec2/spark_ec2.py#L43].
> In Python 2.7, optparse was [deprecated in favor of
> argparse|https://docs.python.org/2/library/optparse.html]. This is the main
> motivation for moving away from optparse.
> Additionally, upgrading to argparse provides some [additional benefits noted
> in the
> docs|https://argparse.googlecode.com/svn/trunk/doc/argparse-vs-optparse.html].
> The one we are mostly likely to benefit from is the better input validation.
> Specifically, being able to cleanly tie each input parameter to a validation
> method will cut down the input validation code currently spread out across
> the script.
> argparse is not include with Python 2.6, which is currently the minimum
> version of Python we support in Spark, but it can easily be downloaded by
> spark-ec2 with the work that has already been done in SPARK-6191.
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