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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
- Removed usages of algorithm.Securities.key as a parameter for the
`ManualUniverseSelectionModel()` since those securities, added through
`AddXXXX` calls will be managed by the `UserDefinedUniverse`. This was
causing for Universes to try to add the same subscription requests
- Adding new empty constructor for ManualUniverseSelectionModel,
required for Python
- ManualUniverse will return any existing SDC for the
symbol. This is for maintaining existing behavior and
preventing breaking changes: Specifically motivated by usages of
Algorithm.Securities.Keys as constructor parameter of the
ManualUniverseSelectionModel, since those Symbols added by Addxxx()
calls will already be managed by the UserDefinedUniverse
- Making some format modifications to aling with used Lean formatting
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.
`EqualEeightingPortfolioConstructionModel` (C# and Python) allocates all cash to the stocks who have insights in universe.
- Fixes regression tests to reflect the model logic change
- Fixes imports in python algorithms to use python models when available
Martin-Molinero