- Adding `BaseData.AdjustResolution()` that should return a valid
resolution for the given data and security type.
This allows us to set a limitation which is useful to avoid invalid data
requests or unnecessary fill forward situations. The user will be
notified through a console message.
- Adding unit and regression test
- Updating example algorithms custom data resolution
- Some performance improvements. Wont change console color if
`SelectedOptimization` is defined
- Custom data types will know whether or not Lean should use map files
- Updating regression test with sample custom data using map files,
which can run locally
- Adding unit tests for the `SubscriptionDataReaderHistoryProvider`,
checking it mappes equities and options correctly
- Adding _some_ of the missing PyObject.Dispose calls. In the cases
where C# is calling the Python side.
- Note that Python calls to C# code is correctly handling the
disposure of resources.
Implements Quandl support for Python.
It was not possible to derive from Quandl in order to select the column. If the data did not have "close", it would thrown an exception since it would look for this work in a dictionary.
It is now possible to select the column.
See example QuandFuturesDataAlgorithm.py