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A streamlined Python Parser for 4C input files

Project description

FourCIPP logo

FourCIPP (FourC Input Python Parser) holds a Python Parser to simply interact with 4C YAML input files. This tool provides a streamlined approach to data handling for third party tools.

Overview

Installation

Python Environment

FourCIPP is a Python project supporting Python versions 3.10 - 3.13. To use FourCIPP it is recommended to install it into a virtual Python environment such as Conda/Miniforge or venv.

An exemplary Conda/Miniforge environment can be created and loaded with

# Create the environment (this only has to be done once)
conda create -n fourcipp python=3.13
# Activate the environment
conda activate fourcipp

To now install FourCIPP different ways exist.

Installation from PyPI

FourCIPP is published on PyPI as a universal wheel, meaning you can install it on Windows, Linux and macOS with:

pip install fourcipp

or a specific version with:

pip install fourcipp==0.28.0

Installation from Github (most recent version)

Additionally, the latest main version of FourCIPP can be installed directly from Github via:

pip install git+https://github.com/4C-multiphysics/fourcipp.git@main

Installation from source

If you intend on developing FourCIPP it is crucial to install FourCIPP from source, i.e., cloning the repository from Github. You can then either install it in a non-editable or editable fashion.

  • Install all requirements without fixed versions in a non-editable fashion via:

    # located at the root of the repository
    pip install .
    

    and without fixed versions in an editable fashion via:

    # located at the root of the repository
    pip install -e .
    

    Note: This is the default behavior. This allows to use fourcipp within other projects without version conflicts.

  • Alternatively, you can install all requirements with fixed versions in a non-editable fashion with:

    pip install .[safe]
    

    and with fixed versions in an editable fashion via:

    # located at the root of the repository
    pip install -e .[safe]
    

Once installed, FourCIPP is ready to be used 🎉

Quickstart example

from fourcipp.fourc_input import FourCInput

# Create a new 4C input via
input_4C = FourCInput()

# Or load an existing input file
input_4C = FourCInput.from_4C_yaml(input_file_path)

# Add or overwrite sections
input_4C["PROBLEM TYPE"] = {"PROBLEMTYPE": "Structure"}
input_4C["PROBLEM SIZE"] = {"DIM": 3, "ELEMENTS": 1_000}

# Update section parameter
input_4C["PROBLEM SIZE"]["ELEMENTS"] = 1_000_000

# Add new parameter
input_4C["PROBLEM SIZE"]["NODES"] = 10_000_000

# Remove section
removed_section = input_4C.pop("PROBLEM SIZE")

# Dump to file
input_4C.dump(input_file_path, validate=True)

Configuration

FourCIPP utilizes the 4C_metadata.yaml and schema.json files generated during the 4C build to remain up-to-date with your 4C build. By default, the files for the latest 4C input version can be found in src/fourcipp/config. You can add custom metadata and schema paths to the configuration file src/fourcipp/config/config.yaml by adding a new profile:

profile: your_custom_files
profiles:
  your_custom_files:
    4C_metadata_path: /absolute/path/to/your/4C_metadata.yaml
    json_schema_path: /absolute/path/to/your/4C_schema.json
  default:
    4C_metadata_path: 4C_metadata.yaml
    json_schema_path: 4C_schema.json
    description: 4C metadata from the latest successful nightly 4C build
  4C_docker_main:
    4C_metadata_path: /home/user/4C/build/4C_metadata.yaml
    json_schema_path: /home/user/4C/build/4C_schema.json
    description: 4C metadata in the main 4C docker image

and select it using the profile entry.

Developing FourCIPP

If you plan on actively developing FourCIPP it is advisable to install in editable mode with the additional developer requirements like

pip install -e .[dev]

Note: The developer requirements can also be installed in non-editable installs. Finally, you can install the pre-commit hook with:

pre-commit install

Dependency Management

To ease the dependency update process pip-tools is utilized. To create the necessary requirements.txt file simply execute

pip-compile --all-extras --output-file=requirements.txt requirements.in

To upgrade the dependencies simply execute

pip-compile --all-extras --output-file=requirements.txt --upgrade requirements.in

License

This project is licensed under a MIT license. For further information check LICENSE.

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