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"].

Bumped the minimal required version of JupyterLab to 2.1.
Upgraded ActiveUI 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The Auth0 support in Atoti+ has been replaced by the more general OpenID Connect authentication protocol.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().

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.

0.4.2 (July 15, 2020)

0.4.0 (May 25, 2020)