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* Python research import improvements
- Improve start.py for research env
- Remove unrequired imports
* Centralize algorithm imports
* Add regression test GH action
* Unit test python import clean up
* Join research and main imports
* More python import clean up
* Fix failing skipped regression algorithm
- `SubscriptionSynchronizer` will emit a `TimeSlice.TimePulse` before
performing any universe selection on each time loop. This will advance
`Algorithm.Time` which will allow universe selection data time and
`Algorithm.Time` to be aligned.
- Updating Regression algorithms that were using `algorithm.Time` in the
selection method.
- Coarse selection will start from the algorithms start date (not in the
next day)
- Adding regression algorithm
We didn't experience the expected performance improvements. Locally under
unit test there was aboout an order of magnitude throughput increase, but
when run against the history benchmark, this new approach was 60% slower.
We're reverting this for now to perform further analysis and better
understand the performance profiling of the python history stack.
Martin-Molinero