I noticed that the python dataflow runner appends some "uniqueness" (the timestamp) [1] to the staging directory when staging artifacts for a dataflow job. This is very suboptimal because it makes caching artifacts between job runs useless.
The jvm runner doesn't do this, is there a good reason the python one does? Or is this just an oversight that hasn't been fixed yet? [1] https://github.com/apache/beam/blob/master/sdks/python/apache_beam/runners/dataflow/internal/apiclient.py#L467
