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Cape - a system for explaining outliers in aggregation results through counterbalancing.

Project description


Cape () is a system for explaining outliers (surprisingly low or high) aggregation function results for group-by queries in SQL. The user provides the system with a query and a surprising outcome for this query. Cape uses patterns discovered the describe trends that hold in the data in aggregation to explain such outliers.


Cape requires python 3. Install with pip:

pip install capexplain

Install from github

git clone capexplain
cd capexplain
python3 install


Cape provides a single binary capexplain that support multiple subcommands. The general form is:

capexplain COMMAND [OPTIONS]

Options are specific to each subcommand. Use capexplain help to see a list of supported commands and capexplain help COMMAND get more detailed help for a subcommand.


Cape currently only supports PostgreSQL as a backend database. To use Cape to explain an aggregation outlier, you first have to let cape find patterns for the table over which are you are aggregating. This an offline step that only has to be executed once for each table (unless you want to rerun pattern mining with different parameter settings).

Mining Patterns

Use capexplain mine [OPTIONS] to mine patterns. Cape will store the discovered patterns in the database.

Explaining Outliers

To explain an aggregation outlier use capexplain explain [OPTIONS].


Cape is developed by researchers at Illinois Institute of Technology and Duke University. For more information and publications see the Cape project page

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