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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
- Setting SPY as the default security benchmark
- The security benchmark subscription will be added at `UniverseSelection`
as an internal subscription. Using its own dedicated Security instance
which doesn't live in the algorithms.Securities collection.
- Reducing algorithms exposure to internal subscriptions
- `TimeSliceFactory` will prioritize higher resolution bars, when same
symbol is present twice (for non-internal subscriptionst)
- Adding regression test `CustomUniverseWithBenchmarkRegressionAlgorithm`
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.
- Adds log to display the python version the algorithm is using.
- Fixes python algorithms that were failing because of small subtleties
like leading zeroes.
- Updates pythonnet with a version compiled with python 3.6 flags
- Changes in DockerfileFoundation: we now use miniconda to manage the python
environment.
- Took the opportunity to add NTLK (#1349), Tensorforce (#1369) and
PyTorch/Pyro (#1385).
- Changes readme in Algorithm.Python to show steps to install miniconda
Some python algorithms suffered corrections to run under the new python framework (pythonnet).
Others were deleted because some features will be supported in futures implementations.
Adds a method in AlgorithmPythonUtil to transform C# DateTime into Python datetime