pyquibbler 0.2.2

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Quibbler

Interactive, reproducible and efficient data analytics

What is it?

Quibbler is a toolset for building highly interactive, yet reproducible, transparent and efficient data analysis pipelines. Quibbler allows using standard Python syntax to process data through any series of analysis steps, while automatically maintaining connectivity between downstream results and upstream raw data sources. Quibbler facilitates and embraces human interventions as an inherent part of the analysis pipeline: input parameters, as well as exceptions and overrides, can be specified and adjusted either programmatically, or by interacting with "live" graphics, and all such interventions are automatically recorded in well-documented human-machine readable files. Changes to such parameters propagate downstream, pinpointing which specific data items, or even specific elements thereof, are affected, thereby vastly saving unnecessary recalculations. Quibbler, therefore, facilitates hands-on interactions with data in ways that are not only flexible, fun and interactive, but also traceable, well-documented, and highly efficient.

"Best Quibble" competition

We just launched Quibbler in PyData Tel-Aviv. We are seeking engagement from users and developers and are also eager to learn of the range of applications for Quibbler. To get it fun and going, we are announcing a competition for the best "Quibble" - a short elegant quib-based code that demonstrates fun interactive graphics and/or hints to ideas of applications.

For details (and prizes!) see: Best Quibble Award

Main Features

Here are a few of the things that Quibbler does:

• Easily build powerful GUI-like interaction with data, without a need for callbacks and event listeners.

• Interactive specification of inputs and overrides of parameter values.

• Automatically create human-readable records of user interventions and parameter specifications.

• Independently calculate, cache and validate/invalidate individual slices of heavy-to-calculate arrays.

• Present a dependency graph between raw data and downstream results.

• Provide inherent undo/redo functionalities.

• All-of-the-above using completely standard functions and programming syntax - there is very little to learn to get started!

Documentations

For complete documentations and a getting-started tour, see readthedocs.

Installation

To install run:

pip install pyquibbler

If are using Jupyter lab, you can also add the pyquibbler Jupyter Lab extensions:

pip install pyquibbler_labextension

For developers, see here.

Credit

Quibbler was created by Roy Kishony, initially implemented as a Matlab toolbox.

Quibbler for Python, pyquibbler, was developed at the Kishony lab, Technion - Israel Institute of Technology, by Maor Kern, Maor Kleinberger and Roy Kishony.

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