Since extension methods don't play well with pythonnet, this change converts
the extensions class into a decorator class. Additionally, this ObjectStore
type is the type that gets exposed via QCAlgorithm so users can access these
methods directly without requiring the use of extension methods.
This approach has many good properties. For one, it doesn't force implementors
of IObjectStore to use a base class. Second, it maintains healthy separation of
API level concerns (such as convenient methods) from the abstraction level conerns
of IObjectStore. Setting it up in this way ensures ANY implementation of IObjectStore
will still get access to these additional methods. Another thing to note is this
prevents using a base class on QCAlgorithm's public interface. Instead, we have a
specific type that is dedicated to fulfilling API level requirements, which also
provides us flexibility in the event the API needs to be updated. If it were a subclass,
you run the risk of breaking the implementors of the subclass.
This commit is squashed from iterative development:
- More consistent method naming
- Storage root path updated to be absolute and include algorithm name
- Storage root path created only if object store is actually used
- Implemented XML save/load
- Added missing unit tests
- Replaced Log.Trace with Log.Error calls
- Added the object store name logging in Engine.Main
- Read storage root from config
- Create algorithm storage root folder in Initialize
- Remove empty folder in Dispose
- Added null checks in all methods
- Added missing XML parameter docs
- make Initialize and Dispose virtual
- make AlgorithmStorageRoot protected
The IObjectStore abstraction provides algorithms with a persistent
storage mechanism. While the algorithm is running, data is maintained
in memory as a dictionary of raw bytes (string -> byte[]). This ensures
we avoid any reference type shenanigans. Periodically, the data in the
object store is persisted and additionally, when the algorithm shuts
down, the object store's data will again be persisted. This ensures that
when the algorithm starts up again, it will have access to any state
that has been saved into the object store.
A great use case for IObjectStore is saving a compute heavy model.
For example, computing the weights of a deep neural network is very
CPU intensive, but after the weights are computed, evaluation is fairly
quick. An initial backtest can be used to solved for the network's weights
and then subsequent backtests or even in live mode, the weights will be
available to the algorithm provided they were saved into the object store.
Also, some libraries require a file path to load model data. The object
store provides a `GetFilePath(key)` method which will copy the data for
the provided key to the disk and return that path so the library can load
the model data.
- Replacing `BaseData.AdjustResolution` for `DefaultResolution` and
`SupportedResolutions`
- Making `Resolution` nullable for `Algorithm.AddData` methods
- The `ISubscriptionDataConfigService` will set the default resolution
if none was provided and assert it is supported
- Fix bug with `PythonData` `IsSparseData` and `RequiresMapping`
resolution
- Adding `IRealTimeHandler.OnSecurityChanged()` will be used to update
the `OnEndOfDay` security related scheduled events
- Adding `BaseRealTimeHandler.cs` to reduce code duplication in the
`Backtesting` and `LiveTrading` `RealTimeHandlers`
- Adding CSharp and Python regression tests
- Deprecating `OnEndOfDay()` callback because of two reasons, mainly
because Python does not support two methods with the same name, but also
because different assets have different market close times.
- `ScheduledEvents` set at the same time will now be deterministic
- Removing `using QCAlgorithmFramework = QuantConnect.Algorithm.QCAlgorithm`
- Removing `QCAlgorithmFrameworkBridge`
- Removing `IsFrameworkAlgorithm`
- Making `EmitInsightBasedOnFill` private. Adding new
`IOrderEventProvider` exposing an `event` to which `QCAlgorithm` will
subscribe.
- `AccountType.Cash` algorithms will be allowed to manually trade and
emight insights manually or with alpha model.
- Classic Algorithms will emight insights based on order fills.
- To be able to update generated insights closed time, we will not
clone emitted insights.
- `InsightAnalysisContext` will update `AnalysisEndTimeUtc` when the
Insight period is closed and the period is `EndOfTimeTimeSpan`
- Adding new regression algorithm asserting on the new emitted insights
- Adding unit tests
- `LiveTradingResultHandler` will store `AlphaRunTimeStatistics`
- Making `DefaultAlphaHandler.ProcessAsynchronousEvents` virtual to
facilitate cloud changes
- Adding new `SetAccountCurrency()` for backtesting. Has to be called
before adding any `Security` or calling `SetCash()`, else will throw.
- Adding new Non account currency unit tests for `CashBuyingPower`,
`SecurityPortfolioModel`, `SecurityMarginModel`,
`SecurityPortfolioManager`, `Future/OptionMarginBuyingPowerModels`
- Adding new C# regression test using `SetAccountCurrency()`, one for
`CashBuyingPowerModel` and one for `SecurityMarginModel`
- Adding new Py and C# basic regression algorithms using
`SetAccountCurrency()`
- `Options` and `Futures` will use not use `AccountCurrency` as quote
Cash.
- `SecurityBenchmark` value will be in account currency
- Moving `UniverseSelection.EnsureCurrencyDataFeeds` call into the
`IResultHandler` implementation through usage of the new `SetupHandlerHelper`
class, that will also set an initial conversion rate if none present.
- Adding regression test, that reproduces original issue
- Adding new `IAlgorithm.AccountCurrency { get; }` that will point to the
`Portfolio.CashBook.AccountCurrency`. Setter will be added in a
following PR.
- Base `Brokerage` class will now have a `AccountCurrency { get }`
pointing to the `IAccountCurrencyProvider`. Will be used by the different
brokerages implementations.
- Adding new ISecurityService and its implementation SecurityService.
Expose by SecurityManager.
This class will expose a method for creating new securities. The
SecurityManager is exposing this new interface, calling _securityService
internally, so Future/OptionUniverseSelectionModel.cs can use it
- Replacing all usages of SecurityManager.CreateSecurity for new
ISecurityService
- Modifying `Cash.cs` and `CashBook.cs` `EnsureCurrencyDataFeeds()` to
return newly added `SubscriptionDataConfig` instead of `Security`. This
will avoid using `Security.Subscriptions` at call site.
- Moving old SecurityManager.CreateSecurity into new
SecurityServiceTests.cs
IAlgorithm exposed a means of setting the CurrentSlice but not a
means for consumers to get the value. This was because until now
all consumers were within the QCAlgorithm scope and had access to
the member variable. This change makes the CurrentSlice available
to LEAN engine code, where it's first use will be in PaperBrokerage
to detect and apply dividend distributions.
This type is just used as a container for generatd insights. Renaming in
preparation for a new InsightCollection to mirror the PortfolioTargetCollection
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.
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.
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.
- 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)
- Moved provider implementations out of brokerages into their own classes
- Removed DefaultOptionChainProvider
- Added BacktestingOptionChainProvider and LiveOptionChainProvider
- Moved SetOptionChainProvider call from Engine to setup handlers