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* Add performance gh action
- Add new performance github action, running python and csharp benchmark
algorithms
- Adjusting algorithms length so they are not too long or too short
* Checkout master branch benchmark reference
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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
- `PortfolioTargetCollection` avoid calling `Count` on
ConcurrentDictionary directly -> has to take all locks
- `SecurityChanges` change Union for Concat since constructor will call
HashSet
- Make `DynamicSecurityData` hold lazy data objects
- `RegisteredSecurityDataTypesProvider` avoid looping over all
registered types, adding `TryGetType`
- `Security.Update()` will no call group by on data since this data is
already grouped by type. Adding `ContainsFillForwardData` will allows to
be lazy and not re loop through the data unless necessary
- `DefaultAlphaHandler` will use the `static`
`Enumerable.Empty<Insight>` instance when possible
- `SubscriptionSynchronizer` will be lazy to construct the
`universeData` dictionary which is not used in most of the times. Will
use `Count` vs `Any` -> `Count` is known by the dictionary
- For python algorithms `JobQueue` will respect `AlgorithmLocation`, was
using unexisting `"algorithm-path-python"`
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