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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
- Add Pandas backwards compatibility shim
- Adding `MappingExtensions` which will remove data type from the
`Symbol.ID.Symbol` value to resolve the `MapFile`
- `SecurityIdentifier.TryParse()` will throw when given an invalid
`SecurityType`
This is being done in an effort to prevent symbol collisions within the
custom data (SecurityType.Base) namespace. The custom data type's name,
is used for disambiguation. As written, this change will break several
user algorithms that still rely on using the implicit string -> Symbol
lift. Providing this type information is optional an currently only being
used by AddData<T> methods. Other consumers of SecurityType.Base symbols
arn't at risk for collision, such as the UserDefinedUniverse, ScheduledUniverse
and others that are LEAN controlled. In order to maintain backwards compatibility,
the SymbolCache was updated to do a hard search when the requested ticker was
not found, looking for the prefix ('ticker.').
Fixes#3332
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.
Ricardo Andrés Marino Rojas