Fix DataFrame conversion issue with arrays of objects.

README.md

@@ -340,6 +340,9 @@ Even more queries can be found [here](https://colab.research.google.com/github/R
 
 # Latest updates
 
+## Version 2.1.9
+- Fixed a bug in the inferred conversion to DataFrames of output involving arrays of objects.
+
 ## Version 2.1.8
 - The order of the columns in output DataFrames were occasionally reshuffled. This new version keeps the column order more stable.
 - Further improvements supporting built-in function and improved XML/XQuery 3.1 support.
@@ -455,4 +458,3 @@ Even more queries can be found [here](https://colab.research.google.com/github/R
 - Ability to write back a sequence of items to local disk, HDFS, S3... in various formats (JSON, CSV, Parquet...).
 - Automatically declare external variables bound as DataFrames to improve userfriendliness.
 - Simplified the function names to make them more intuitive (json(), items(), df(), rdd(), etc).
-

pyproject.toml

@@ -4,7 +4,7 @@ build-backend = "setuptools.build_meta"
 
 [project]
 name = "jsoniq"
-version = "2.1.8"
+version = "2.1.9"
 description = "Python edition of RumbleDB, a JSONiq engine"
 requires-python = ">=3.11"
 dependencies = [

src/jsoniq/session.py

@@ -7,7 +7,7 @@
 import pandas as pd
 from importlib.resources import files, as_file
 
-with as_file(files("jsoniq.jars").joinpath("rumbledb-2.1.8.jar")) as jar_path:
+with as_file(files("jsoniq.jars").joinpath("rumbledb-2.1.9.jar")) as jar_path:
     if (os.name == 'nt'):
         jar_path_str = str(jar_path)
     else: