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Getting Started
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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:

.. code-block:: bash

    quick_pp start <your_file>

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

.. code-block:: bash

    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 <https://github.com/imranfadhil/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 <https://www.researchgate.net/publication/396099755_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.