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Releases: RumbleDB/python-jsoniq

jsoniq 2.0.2 "Lemon Ironwood" beta

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@ghislainfourny ghislainfourny released this 12 Sep 08:44
f10408c
  • Add MongoDB connection (mongodb-collection()). Requires including .withMongo() when creating the RumbleSession.

jsoniq 2.0.1 "Lemon Ironwood" beta

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@ghislainfourny ghislainfourny released this 10 Sep 14:26
70736d4
  • Works with Spark 4.0.1.
  • Add postgreSQL connection (postgresql-table()).

jsoniq 2.0.0 "Lemon Ironwood" beta

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@ghislainfourny ghislainfourny released this 29 Aug 11:27
aeb6223

Official release aligned on the brand new RumbleDB 2.0 release.

  • Improved display of pandas dataframes output with -pdf in Jupyter notebooks.
  • if error info is activated in the configuration, then they are now printed in the notebook.
  • JSON nulls are now by default conflated with absent upon validating for dataframe output, this can be deactivated in the configuration.
  • The materialization error upon df/pdf output is now fixed.

jsoniq 2.0.0 alpha 1

jsoniq 2.0.0 alpha 1 Pre-release
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@ghislainfourny ghislainfourny released this 27 Aug 14:02
d94b4b7
  • When returning a single-column DataFrame with atomic values, the name is now __value and not value to avoid collisions with user-defined columns.
  • Improved schema inferrence: DataFrames can be returned in a wider range of cases.
  • Improved error display in notebooks when errors happen upon collecting the results and not already upon calling jsoniq().

jsoniq 0.2.0 alpha 9

jsoniq 0.2.0 alpha 9 Pre-release
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@ghislainfourny ghislainfourny released this 21 Aug 12:18
955145c
  • Stability improvements.

jsoniq 0.2.0 alpha 8

jsoniq 0.2.0 alpha 8 Pre-release
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@ghislainfourny ghislainfourny released this 21 Aug 12:04
c61f5dc
  • Variables can now be bound to JSON values, pandas DataFrames or pyspark DataFrames with extra parameters to the rumble.jsoniq() call. It is no longer necessary to explicitly call bind(). This is similar to how DataFrames can be attached to views with extra parameters to spark.sql().
  • rumble.lastResult is now correctly assigned also when partial data is returned (only with the partial data).
  • Fixed issue with empty array constructors.

jsoniq 0.2.0 alpha 7

jsoniq 0.2.0 alpha 7 Pre-release
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@ghislainfourny ghislainfourny released this 20 Aug 12:37
05d0ee6
  • rumble.lastResult now returns a pyspark/pandas DataFrame or rdd or tuple and no longer the sequence object.
  • Enhance schema detection. When the detected static type of the overall query is DataFrame-compatible, it is now automatically possible to obtain the output as a DataFrame without explicitly giving a schema.
  • It is now possible to access a table previously registered as a view via a table() function call. This is an alternative to binding variables.
  • Enhancements in the JSONiq Update Facility support to update delta files and Hive metastore tables.

jsoniq 0.2.0 alpha 6

jsoniq 0.2.0 alpha 6 Pre-release
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@ghislainfourny ghislainfourny released this 13 Aug 14:04
8cfc3a7
  • Fix a bug with the config() call of the builder.
  • add withDelta() to configure Delta Lake tables and files, for use with the JSONiq Update Facility.

jsoniq 0.2.0 alpha 5

jsoniq 0.2.0 alpha 5 Pre-release
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@ghislainfourny ghislainfourny released this 08 Aug 08:42
0b137cf
  • If the initialization of the Spark session fails, we now check if SPARK_HOME is set and if it may be invalid or pointing to a different Spark version than 4.0, and output a more informative error message.

jsoniq 0.2.0 alpha 4

jsoniq 0.2.0 alpha 4 Pre-release
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@ghislainfourny ghislainfourny released this 06 Aug 14:47
2fea77c
  • Added parameters to the jsoniq magic to select the desired output to print: -j, -df, -pdf
  • Added informative error message with a hint on how to fix when trying to get a DataFrame and there is no schema.
  • Added parameter -t to the jsoniq magic to measure the response time
  • The RumbleSession object now saves the latest result (sequence of items) in a field called lastResult. This is particularly useful in notebooks for post-processing a result in Python after obtained it through the jsoniq magic.
  • Improved static type detection upon binding a pandas or pyspark DataFrame as an input variable to a JSONiq queries.
  • Now also accepts pandas version 2.2.