We had an issue with the data feed picking up universe/security changes
too quickly, thereby preventing user code from being able to configure the
security object properly. Specifically, users were having an issue setting
the data normalization mode of options and underlying equity securities. By
the time the user code had set the data mode, the data feed had already
created a subscription and began processing it, so the changes were never
seen in the data feed.
This change moves all security/universe changes into pending lists and at
the end of the time step applies those changes. Security objects are still
added directly to the SecurityManager for instance access, but we delay in
adding the security to the universe and the universe to the UniverseManager.
Once added to the universe manager, an event is fired and the data feed will
process the new subscriptions.
This event was not properly wrapped.
When `IAlgorithm.InsightsGenerated` is set in `IAlphaHandler`, it should be directed to the base algorithm, whereas it was set to a null variable.
Move the logic of importing the module into AlgorithmPythonWrapper where it is wrapped.
Throws an exception if the script does not have a class that inherits from either QCAlgorithm not QCAlgorithmFramework.
Adds a check for OnData being defined in the module. If not, OnData from the base class will not be called (it causes stack overflow otherwise)
The term 'alpha' is used to describe the entire algorithm. Therefore, 'alpha'
produces insights. From this we have things like IAlphaModel, which is the model
defining how insights are produced. We have IAlphaHandler, which defines how the
insights from a single 'alpha' (the algorithm) are managed, analyzed, and stored.
Types closer to the individual prediction level, such as InsightDirection, or
InsightScore relate directly to exactly 1 insight. The distinction between the
two became more clear as we developed the insights API, and from that effort it
was decided to harmonize alpha/insight terminology across the various QC systems.
The error message it was used to bypass the the error logging has been changed from `takes exactly x arguments (y given)` to `takes x positional argument but y were given`.
With this constructor, SetConverter method, that was not respecting Lean pattern, is removed. The initialization of _converter field is done once the type is loaded.
Python algorithms with custom data requires an operation that converts a dictionary key into a attribute. In the current implementation the Slice object was converted into a python dictionary. This was not optimal, since we just need to make this conversion when the value of a key in the Slice is accessed.
This implementation proposes a wrapper for the Slice object, PythonSlice, that would just perform the operation described above when needed.
This method is being added to allow algorithms to complete initialization tasks that cannot be executed during Initialize, such as cancelling existing open orders in live trading.
This method will be called only once, when the warmup task is complete.
Closes#1043
IAlgorithm.FrameworkOnData is used to pulse models with new data each time step
IAlgorithm.FrameworkOnSecuritiesChanged is used to pulse models with security changes
These two functions need to be separate to ensure that if we add an indicator during
the securities changed event that it will get the data from the current time step.
This forces us to call the securities changed event before we invoke the consolidators
for the current time step.
The engine creates schedule events that call OnEndOfDay() and OnEndOdDay(Symbol) for every security. If just one of these method overloads is defined in the python script, the call of the other will throw a exception due different parameter count.
In this case, we will disregard this exception and throw those that may happen in the method implementation body.
- Move BacktestingFutureChainProvider provider to Lean.Engine.DataFeeds along with its options equivalent.
- EmptyFutureChainProvider: provider that returns an empty list of symbols
- CachingFutureChainProvider: implements caching by date
- BacktestingFutureChainProvider: provider that gets chain from local files
- LiveFutureChainProvider: provider that gets chain from external source (empty list of symbols for now)
Summary of members in python wrapper classes where pointing to other methods for reference when they should have a meaningful description to be used in documentation
After we included the method name in the error message, OnMarginCall method was throwing a runtime error when that method was not defined in the script where it sould simply be directed to the method in the base class.
Due to pythonnet limitations, the list of SubmitOrderRequest could not be modified by OnMarginCall event handler. We now get a new list from that method and update the list in the wrapper.
- Moved provider implementations out of brokerages into their own classes
- Removed DefaultOptionChainProvider
- Added BacktestingOptionChainProvider and LiveOptionChainProvider
- Moved SetOptionChainProvider call from Engine to setup handlers
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
When OnMarginCall is not defined at the python script, pythonnet cannot find the method in the base class.
Instead of throwing the exception and exiting, we direct the event to the method in the base class.
Calling Impromptu.ActLike<IAlgorithm> to make the python object acts like a IAlgorithm caused multiple AlgorithmPythonWrapper objects running in parallel to hold the same python object. That call was removed and instead we access the python object directly.
- Removes AlgorithmPythonUtil.py and add its code directly in AlgorithmPythonWrapper.cs
- Clean up: removes all references to IronPython and ImpromptuInterface
Michael Handschuh