Cubes 0.10 Released

After a while, here is an update to Cubes - Python Lightweight OLAP framework for multidimensional modeling. There are some changes included that were mentioned in the EruoPython talk such as table_rows and cross_table.

I recommend to look at updated examples in the Github repository. The Flask example is now "real" example instead of "sandbox" example and you can see how to generate a simple table for dimension hierarchy browsing.

There is also a more complex example with star-like schema dataset in the cubes-examples github repository. Follow the instructions in README files how to make it running.

There are some backward incompatible changes in this release – until 1.0 the "point" releases will contain this kind of changes, as it is still evolving. You can find more information below.

Quick Summary

• Way how model is constructed has changed. Designated methods are create_model() or load_model()
• Dimension defition can have a "template". For example:

    {
      "name": "contract_date",
      "template": "date"
    }

• added table_rows() and cross_table() to aggregation result for more convenient table creation. The table_rows takes care of providing appropriate dimension key and label for browsed level.
• added simple_model(cube_name, dimension_names, measures)

Incompatibilities: use create_model() instead of Model(**dict), if you were using just load_model(), you are fine.

New Features

• To address issue #8 create_model(dict) was added as replacement for Model(**dict). Model() from now on will expect correctly constructed model objects. create_model() will be able to handle various simplifications and defaults during the construction process.
• added info attribute to all model objects. It can be used to store custom, application or front-end specific information
• preliminary implementation of cross_table() (interface might be changed)
• AggregationResult.table_rows() - new method that iterates through drill-down rows and returns a tuple with key, label, path, and rest of the fields.
• dimension in model description can specify another template dimension – all properties from the template will be inherited in the new dimension. All dimension properties specified in the new dimension completely override the template specification
• added point_cut_for_dimension
• added simple_model(cube_name, dimensions, measures) – creates a single-cube model with flat dimensions from a list of dimension names and measures from a list of measure names. For example:

model = simple_model("contracts", ["year","contractor", "type"], ["amount"])

Slicer Server:

• /cell – return cell details (replaces /details)

Changes

• creation of a model from dictionary through Model(dict) is depreciated, use create_model(dict) instead. All initialization code will be moved there. Depreciation warnings were added. Old functionality retained for the time being. (important)
• Replaced Attribute.full_name() with Attribute.ref()
• Removed Dimension.attribute_reference() as same can be achieved with dim(attr).ref()
• AggregationResult.drilldown renamed to AggregationResults.cells (important)

Planned Changes:

• str(Attribute) will return ref() instead of attribute name as it is more useful

Fixes

• order of dimensions is now preserved in the Model

Links

Sources can be found on github. Read the documentation.

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If you have any questions, comments, requests, do not hesitate to ask.