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This way, there's a single argument to PipelineManager, which accepts a dict of pipestat config options, which can be passed with **kwargs. This seems cleaner than specifying separate arguments, one for each pipestat config option. Also, it will ensure the options stay in sync -- right now they're out of sync (pypiper wants pipestat_sample_name, which it will pass to record_identifier). So, it will eliminate maintaining a bunch of pypiper argument names for consistency.
The text was updated successfully, but these errors were encountered:
Another issue is that I can't figure out how to map the config options to configure pipestat the way I want it. I don't know what pipestat_project_name maps to, and I don't see how to set the pipeline_type through pypiper.
I wanted to pass multi_pipeilnes=True to pipestat, when I'm constructing my pypiper.PipelineManager, but this is not documented. The way to do it is to say multi=True to pypiper, which takes this and changes it to multi_pipelines=True passed to pipestat. I had to find this in the code itself to figure it out.
This would be easier and not require additional documentation if instead we used pipestat_config and passed through kwargs.
Right now, the docs suggest configuring pipestat via pypiper like this:
meanwhile, pipestat is configured like this:
I would like these to be uniform. So, I want to do:
And use this for either, like:
or:
This way, there's a single argument to PipelineManager, which accepts a dict of pipestat config options, which can be passed with
**kwargs
. This seems cleaner than specifying separate arguments, one for each pipestat config option. Also, it will ensure the options stay in sync -- right now they're out of sync (pypiper wantspipestat_sample_name
, which it will pass torecord_identifier
). So, it will eliminate maintaining a bunch of pypiper argument names for consistency.The text was updated successfully, but these errors were encountered: