| Name | hsd JSON |
| Version |
0.1
JSON |
| download |
| home_page | https://github.com/dftbplus/hsd-python |
| Summary | Tools for reading, writing and manipulating data stored in the human-friendly structured data (HSD) format |
| upload_time | 2021-11-11 09:41:24 |
| maintainer | |
| docs_url | None |
| author | DFTB+ developers group |
| requires_python | |
| license | BSD |
| keywords |
|
| VCS |
 |
| bugtrack_url |
|
| requirements |
No requirements were recorded.
|
| Travis-CI |
|
| coveralls test coverage |
No coveralls.
|
**********************************************
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+ <https://github.com/dftbplus/dftbplus>`_), 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 <https://hsd-python.readthedocs.io/>`_ can be found on
`Read the Docs <https://hsd-python.readthedocs.io/>`_.
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 <LICENSE>`_.
Raw data
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