Commit Graph

3 Commits

Author SHA1 Message Date
Michael Handschuh 39935552a3 Convert ObjectStore ext class to implement IObjectStore for API
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.
2019-12-31 15:55:16 -05:00
Michael Handschuh a2b2f889ea Convert object store to in-memory w/ persistence interval
persistenceIntervalSeconds defines the number of seconds between
each save operation. For the local object store, this dictates
how often the contents of the object store is packaged and written
to disk. The PersistData virtual method is provided for subclasses
to provide a different implementation of how/where to persist the
data. The change to be in-memory aims at keeping the object store
performant with reasonable persistence guarantees.
2019-12-17 22:21:11 -05:00
Stefano Raggi d407307566 Add IObjectStore interface with LocalObjectStore implementation
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.
2019-12-17 22:21:11 -05:00