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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
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.
This algorithm had a couple of issues:
- it was using a coarse universe with no data files available, so it has been changed to use a custom universe
- it was using algorithm time instead of selection time in the selector function
The regression stats have also been updated to match the new algorithm code.
Martin-Molinero