* Solve bug and add unit tests
The bug was raised due to a race condition when writing a file and
deleting it. In order to stop it, a check condition was added at the end
of the PersistData() method to remove files that have just been deleted.
* Nit changes
* Add a different constructor for the test
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- Fully reset the security cache when it's finally removed from the algorithm.
Adding regression algorithm reproducing issue
- Updating regression algorithms which would trade based on data
previously available
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* Refactor `GetFilePath()`
Add also useful methods to use with this one
* Nit changes
* Requested changes
* Requested changes
* Restore SaveString()
* Nit changes
* Address self review
* Test improvements
* Adjust example KerasNeuralNetworkAlgorithm
* Minor tweak for KerasNeuralNetworkAlgorithm.py
Co-authored-by: Martin-Molinero <martin@quantconnect.com>
* Store temp files in subdirectory
* Fix Dispose case for new temp dir
* Adjust tests for new temp dir
* Dispose unit tests
* Unit test for issue 4811
* Refactor for not using temp files
* Fix storage checks for saving data, plus tests
* Use Base64 for storing keys and decoding them; handles odd key strings
* Don't allow "?" in a key
* Address review
* Deleted test cases
* PersistData handle deletion of files
* Refactor GetFilePath to use Persist()
* Make PathForKey protected
- LocalObjectStore.Delete() will also delete file from the local object
store path if present, this will avoid the issue where restarting the
object store will re load the same deleted file. Adding unit test.
Issue https://github.com/QuantConnect/Lean/issues/4811
* DataConsolidator Wrapper for Python Consolidators
* Regression Unit Test
* Refactor Regression test
* Bad test fix
* pre review
* self review
* Add RegisterIndicator for Python Consolidator
* Python base class for consolidators
* Modify regression algo to register indicator
* unit test - attach event
* Test fix
* Fix test python imports
* Add license header file and null check
Co-authored-by: Martin Molinero <martin.molinero1@gmail.com>
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.
Errors raised during persistence aren't able to be handled by user code,
and in fact, are swallowed by the implementation after being logged. By
exposing these errors as events we allow the algorithm to be notified of
such an error and take any step necessary to handle the persistence error.
There's no reason for algorithms to have direct access to this implementation.
Moving this into the engine prevents algoriths from directly accessing LocalObjectStore
and instead can only reference it through the IObjectStore abstraction
JosueNina