ibis-sales-query

Building a Sales Data Query using Ibis Expressions (with complimentary fString Representations)

This repository contains:

1. A requirements file to quickly spin up an environment using venv or Binder
2. A mock dataset generation notebook to randomly generate sales data for use in the following notebooks
3. A notebook that builds a sales data query using fStrings
4. A notebook that builds a sales data query using Ibis expressions.

Using this notebook set (or, at least, notebook 4), we can take a look at how Ibis can make your python-based data workflows a bit simpler.

Ibis performs type and reference checking throughout script execution, whereas fString SQL only performs checks at query execution. By performing type and reference checks in-line, we can easily find bugs and errors with our query, make the code a bit more accessible to Python users, and allows us to use Python objects when programmatically generating queries.

Ibis also directly uses python objects. With fStrings, a user will need to convert those objects to engine-readable strings (e.g. converting a string value to a string within a string, or a list of integers to a comma-delimited list of integers within a string). This process gets very painful as conversions between objects and strings occur, so being able to directly use these objects using Ibis expressions helps a ton.

Try it with Binder: