Client Installation

Python Client

The Kaskada Python client can be installed using pip

pip install kaskada 

This will download and install the latest Kaskada library.

IPython (Jupyter) Extension

IPython is an interactive Python runtime used by Jupyter and other notebooks to evaluate Python code blocks. IPython supports "magic extensions" for customizing how code blocks are interpreted. Kaskada provides a magic extension that simplifies querying Kaskada. To use the extension you must first install the fenlmagic python package, for example using pip:

pip install fenlmagic

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️ Info

Make sure to install this package in the same environment IPython will be running in.

Inside an IPython session (for example a Jupyter notebook) the extension can be loaded using the magic command %load_ext:

%load_ext fenlmagic

This will load the extension into the IPython context. You can verify the install worked by initializing the extension:

%%fenl?

  %fenl [--as-view AS_VIEW] [--data-token DATA_TOKEN] [--debug DEBUG]
            [--output OUTPUT] [--preview-rows PREVIEW_ROWS]
            [--result-behavior RESULT_BEHAVIOR] [--var VAR]

fenl query magic

optional arguments:
  --as-view AS_VIEW     adds the body as a view with the given name to all
                        subsequent fenl queries.
  --data-token DATA_TOKEN
                        A data token to run queries against. Enables
                        repeatable queries.
  --debug DEBUG         Shows debugging information
  --output OUTPUT       Output format for the query results. One of "df"
                        (default), "json", "parquet" or "redis-bulk". "redis-
                        bulk" implies --result-behavior "final-results"
  --preview-rows PREVIEW_ROWS
                        Produces a preview of the data with at least this many
                        rows.
  --result-behavior RESULT_BEHAVIOR
                        Determines which results are returned. Either "all-
                        results" (default), or "final-results" which returns
                        only the final values for each entity.
  --var VAR             Assigns the QueryResponse to a local variable with the given
                        name. The QueryResponse contains result_url, query and dataframe.