Python: FHA LRA workflow checkpoint gap investigation

[TaoChenOSU]

In FHA LRA with MAF workflows, there are a few known gaps that require more in-depth investigation:

1. A workflow that doesn't produce any output until the very end will never be recover from a crash, because a responses checkpoint can only be persisted when the workflow yields output. Upon recovery, the workflow will be restarted from the very beginning, which is not desired.
2. There is always a gap between when the workflow stores its checkpoint and when the responses checkpoint is persisted. Say a superstep that yields two outputs, the first output gets to the client while the second output is still on the wire, the connection drops (client never gets the second output) and the workflow moves the next superstep after storing a checkpoint, and now the process crashes, the checkpoint gets stored but is never persisted with the response stream so upon recovery the workflow resumes from the checkpoint, which will not rerun the previous superstep. The client will lose the second update forever.