HSD — Make your structured data human friendly

Utilities to read and write files in the Human-friendly Structured Data (HSD) format.

The HSD-format is very similar to both JSON and YAML, but tries to minimize the effort for humans to read and write it. It ommits special characters as much as possible (in contrast to JSON) and is not indentation dependent (in contrast to YAML). It was developed originally as the input format for the scientific simulation tool (DFTB+), but is of general purpose. Data stored in HSD can be easily mapped to a subset of JSON or XML and vica versa.

Detailed documentation can be found on Read the Docs.

Installation

The package can be installed via conda-forge:

conda install --channel "conda-forge" hsd-python

Alternatively, the package can be downloaded and installed via pip into the active Python interpreter (preferably using a virtual python environment) by :

pip install hsd

or into the user space issueing :

pip install --user hsd

Quick tutorial

A typical, self-explaining input written in HSD looks like :

driver {
  conjugate_gradients {
    moved_atoms = 1 2 "7:19"
    max_steps = 100
  }
}

hamiltonian {
  dftb {
    scc = yes
    scc_tolerance = 1e-10
    mixer {
      broyden {}
    }
    filling {
      fermi {
        # This is comment which will be ignored
        # Note the attribute (unit) of the field below
        temperature [kelvin] = 100
      }
    }
    k_points_and_weights {
      supercell_folding {
        2   0   0
        0   2   0
        0   0   2
        0.5 0.5 0.5
      }
    }
  }
}

The above input can be parsed into a Python dictionary with:

import hsd
hsdinput = hsd.load("test.hsd")

The dictionary hsdinput will then look as:

{
    "driver": {
        "conjugate_gradients" {
            "moved_atoms": [1, 2, "7:19"],
            "max_steps": 100
        }
    },
    "hamiltonian": {
        "dftb": {
            "scc": True,
            "scc_tolerance": 1e-10,
            "mixer": {
                "broyden": {}
            },
            "filling": {
                "fermi": {
                    "temperature": 100,
                    "temperature.attrib": "kelvin"
                }
            }
            "k_points_and_weights": {
                "supercell_folding": [
                    [2, 0, 0],
                    [0, 2, 0],
                    [0, 0, 2],
                    [0.5, 0.5, 0.5]
                ]
            }
        }
    }
}

Being a simple Python dictionary, it can be easily queried and manipulated in Python :

hsdinput["driver"]["conjugate_gradients"]["max_steps"] = 200

and then stored again in HSD format :

hsd.dump(hsdinput, "test2.hsd")

License

The hsd-python package is licensed under the BSD 2-clause license.