* OnEndOfDayRegressionAlgorithm - Since the EndTime of the hourly benchmark is during the day,
the OnEndOfDay method gets called one less time than usual. Updates statistics
* CustomUniverseWithBenchmarkRegressionAlgorithm.cs - modified algorithm so
that it works with hourly benchmark. Previously only tested for Daily benchmark
* BasicTemplateAlgorithm.py - Modified resolution to be
Resolution.Minute, just like it is in C#
* CustomDataRegressionAlgorithm.py - Remove warmup call from Initialize
* IndicatorSuiteAlgorithm.py - Adds PythonQuandl import to fix import error
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
build.bat (batch.sh in Linux) includes the code inside the file with the desired algorithm (set in config.json by "algorithm-type-name") in the python DLL (QuantConnect.Algorithm.Python.dll) via IronPython.
In the AlgorithmFactory, Loader.TryCreatePythonAlgorithm imports the module with the algorithm name instead of "main".
Closes#289
Gerardo Salazar