0.4.1 (June 17, 2020)

Added

• New tutorial exploring the main basic features of Atoti.

• atoti.rank() returns a measure ranking the members of a given hierarchy based on the value of another measure.

• atoti.array.prefix_sum() performs the prefix sum of array measures.

• Hierarchies can have the same name if they are in different dimensions. To avoid conflicts, a hierarchy can be accessed via a tuple containing the dimension and the hierarchy: cube.hierarchies["Product", "Size"].

Changed

• Bumped the minimal required version of JupyterLab to 2.1.

• Upgraded Atoti UI to 4.3.8.

• Better messages for Java known errors (issue #43).

• The Auth0 support in Atoti+ has been replaced by the more general OpenID Connect authentication protocol. The structure of the configuration can be seen in atoti.config.create_oidc_authentication().

Fixed

• atoti.filter()’s measure parameter accepts any value that can be converted to a measure (issue #22).

• atoti.filter() and atoti.where() support inequalities on dates as conditions.

• Issue when loading data into a scenario with truncate=True (issue #53).

• Issue with atoti.agg.quantile() combined with atoti.scope.origin().

• Issue when aggregating .VALUE measures using any of the atoti.agg.*() functions (issue #52).

• Type issue that sometimes happened when chaining operators such as atoti.array.quantile() and atoti.date_shift().

• Blinking cell updates not appearing in pivot tables with real time queries.