Getting Started

There are two primary ways to use quick_pp: from the Command-Line Interface (CLI) or by importing it into your Python code. Additionally, we provide a collection of Jupyter Notebooks to demonstrate various use cases.

Command-Line Interface (CLI)

The CLI is perfect for quick processing tasks directly from your terminal.

To start, simply use the quick_pp command, followed by the desired subcommand and options. For example, to start processing a file, you can run:

quick_pp start <your_file>

For a full list of available commands and their options, you can use the help flag:

quick_pp --help

As a Library

For more complex workflows or to integrate quick_pp into your applications, you can use it as a Python library.

To use quick_pp in a project, import it and call its functions:

import quick_pp

More examples are available in pp_portfolio github repository.

An article demonstrating the use of quick_pp has been published in Petrophysics Journal - Vol. 66, No.5 (October 2025): Pages 807-838 Enhanced Learning Experience for New Petrophysicists Using Open-Source Carbonate Data and Python Programming.

Jupyter Notebooks

We have prepared a series of Jupyter Notebooks that provide in-depth examples and tutorials on how to leverage the full potential of quick_pp. These notebooks cover a range of topics from basic setup to advanced data processing techniques.

You can find the notebooks in the notebooks directory of the project repository. They are an excellent resource for getting started and exploring the library’s features.