* Update projects to use .NET 5.0, the successor to .NET Core
* Fix ambiguous errors. Add IBAutomator net5
* Remove FXCM
* Upgrade IBAutomater to v1.0.51
ignored, and an empty message aborts the commit.
* Fix rebase
- Fix ambiguous Index
- Remove StrategyCapacity.cs
- Update System.Threading.Tasks.Extensionsy
* Remove unrequired references
* Fixes
- Travis will use dotnet, not nunit nor mono
- Remove mono from foundation image
- Fix python setup in research
- Fix unit tests
* Don't call ReadKey when input is redirected
* Fix ConsoleLeanOptimizer
* Research fixes
* Update comment
* Add vsdbg to Dockerfile
* Fixes
- Revert dockerfile FROM custom changes
- Adjust and fix regression algorithms
- Option assignment will be deterministic in the order
- 'Rolling Averaged Population' is calculated using doubles, updating
expected values.
- Update readme, removing references to mono
- Add missing Py.Gil lock
* Replace ICSharp with .NET Interactive
* Fixes after rebase
* CSharp research fixes
- Adding new Initialize.csx that pre loads all assemblies
- Adjusting template research file
- Moving steps in dockerfilejupyter
- Fix unit tests and regression tests after rebase
Co-authored-by: Gerardo Salazar <gsalaz9800@gmail.com>
Co-authored-by: Stefano Raggi <stefano.raggi67@gmail.com>
Co-authored-by: Jasper van Merle <jaspervmerle@gmail.com>
* Add a "Hiring" section to readme.md
Added "QuantConnect is Hiring" to the top of the readme
Added links to the open roles on Indeed:
- Developer Advocate
- Quantitative Developer
- Quantitative Development Intern
- 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
This new pythonnet package makes available the latest version from pythonnet master branch and includes modifications to enable charting in Lean for python.
The dockerfile to create images for the cloud is updated to reflect the package update and adds keras and tensorflow
Martin-Molinero