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These decorators just provide information that mist uses to know what type of context function takes.
So, you want to call the function directly from python, you need to create and pass sparkContext into it.
Unfortunately, there aren't any built-in feature to share anything except context. Technically, it is possible to cache data on the worker process, but you need to do it on your own.
A context can be shared between several function invocation - there is sharedworker-mode option for it (details: 1, 2) Actually, it means that Mist tries to reuse worker processes to not to start a new one per every function invocation.
I'm getting error while trying to get the Spark Context.
Am I missing something? why the wrapper is not passing the argument ?
Thanks,
Bala
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