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https://issues.apache.org/jira/browse/SEDONA-59?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=17404294#comment-17404294
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Jia Yu commented on SEDONA-59:
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This is an awesome solution. Can you create this PR at your earliest
convenience? We are planing to roll out 1.1.0 in the next one or two weeks.
> Remove explicit pyspark dependency
> ----------------------------------
>
> Key: SEDONA-59
> URL: https://issues.apache.org/jira/browse/SEDONA-59
> Project: Apache Sedona
> Issue Type: Improvement
> Reporter: Sebastian Eckweiler
> Priority: Normal
>
> The currently published sedona python package has an explicit dependency on
> pyspark.
> When used on spark platforms such as Databricks spark comes pre-installed,
> but not integrated with pip. A `pip install sedona` will thus install another
> pyspark copy - which in the best case is just superfluous. In the worst case
> it might cause trouble in combination with the pre-installed spark.
> Workarounds, such as installing sedona without dependencies can work for a
> while.
> But this is fragile: as soon as dependency validation as performed e.g. by
> setuptools entrypoints comes around it will break.
>
> I guess there are two options:
> * Removing the pyspark dependency completely, considering it to "obvious"
> * Add pyspark as an optional `extras_require` to an extra called "spark".
> This would allow a pip install as below, which would get sedona and the
> corresponding pyspark distribution:
> {code:java}
> pip install sedona[spark]{code}
>
> I'd be willing to create a corresponding pull-request if one of the options
> would be accepted.
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