1.30.21
1.30.21.2
Improvements
- pandas version 1.0.0 or higher is now required as a dependency.
Bug Fixes
Fixed a segmentation error when calling the
getUnwrittenData
method after the MultithreadedTableWriter failed to insert data.Downloading of BLOB data larger than 64 KB is now supported.
Fixed an issue where out-of-bounds access occurred when subscribing to data from DolphinDB server version 1.30.21/2.00.9 or later on MAC ARM.
Fixed incorrect data type conversion when uploading null values of np.datetime64 type.
Fixed decimal overflow when uploading a vector with the first element being a Decimal("NaN").
Fixed a segmentation error when downloading BLOB sets using the PROTOCOL_DDB protocol.
Fixed an issues where a session variable named “db“ was overwritten when calling the
loadTableBySQL
method.Fixed an issue where the process would be stuck when data was not retrieved after calling the
addTask
method of DBConnectionPool.
1.30.21.1
New Features
Added support for Python 3.10.
Added a new parameter protocol to
Session
andDBConnectionPool
constructors to specify the data transfer protocol.Subscribed data can now be pushed using the connection initiated by the subscriber through Python API.
Added a new parameter args to pass user-defined objects to
DBConnectionPool.addTask
.tableAppender
,tableUpsert
andPartitionedTableAppender
now support uploading IPaddr, UUID, and INT128 values.Added support for downloading data using the Apache Arrow format.
Added support for downloading and uploading DECIMAL values using the DolphinDB-customized data communication protocol.
Error message enhancements
Bug Fixes
Fixed semaphore creation error which is raised after multiple creations of
MultithreadedTableWriter
in macOS.Fixed the "unmarshall failed" error when downloading an empty table containing STRING columns with pickle enabled.
Fixed the issue where the request is aborted when the subscribed data contains array vectors.
Fixed the issue in uWSGI when executing a SQL query with the Python API.
Fixed the issue when uploading np.nan values, the server displays "NaN" instead of converting them to NULL values.