parsnip-cif

.. _images:

.. image:: https://raw.githubusercontent.com/glotzerlab/parsnip/refs/heads/main/doc/source/_static/parsnip_header_dark.svg :width: 600

.. _header:

|ReadTheDocs| |PyPI| |conda-forge|

.. |ReadTheDocs| image:: https://readthedocs.org/projects/parsnip-cif/badge/?version=latest :target: http://parsnip-cif.readthedocs.io/en/latest/?badge=latest .. |PyPI| image:: https://img.shields.io/pypi/v/parsnip-cif.svg :target: https://pypi.org/project/parsnip-cif/ .. |conda-forge| image:: https://img.shields.io/conda/vn/conda-forge/parsnip-cif.svg :target: https://anaconda.org/conda-forge/parsnip-cif

.. _introduction:

parsnip is a minimal Python library for parsing CIF <https://www.iucr.org/resources/cif>_ files. While its primary focus is on simplicity and portability, performance-oriented design choices are made where possible.

.. _parse:

Importing parsnip allows users to read CIF 1.1 <https://www.iucr.org/resources/cif/spec/version1.1>_ files, as well as many features from the CIF 2.0 <https://www.iucr.org/resources/cif/cif2>_ and mmCIF <https://pdb101.rcsb.org/learn/guide-to-understanding-pdb-data/beginner’s-guide-to-pdb-structures-and-the-pdbx-mmcif-format>_ formats. Creating a CifFile_ object provides easy access to name-value pairs, as well as loop\_-delimited loops. Data entries can be extracted as python primitives or numpy arrays for further use.

.. _CifFile: https://parsnip-cif.readthedocs.io/en/latest/package-parse.html#parsnip.parsnip.CifFile .. _pairs: https://parsnip-cif.readthedocs.io/en/latest/package-parse.html#parsnip.parsnip.CifFile.pairs .. _loops: https://parsnip-cif.readthedocs.io/en/latest/package-parse.html#parsnip.parsnip.CifFile.loops

.. _installing:

Setup

parsnip may be installed with pip or from conda-forge.

Installation via pip ^^^^^^^^^^^^^^^^^^^^

.. code:: bash

python -m pip install parsnip-cif

Installation via conda-forge ^^^^^^^^^^^^^^^^^^^^^^^^^^^^

.. code:: bash

conda install -c conda-forge parsnip-cif

Installation from source ^^^^^^^^^^^^^^^^^^^^^^^^

First, clone the repository:

.. code:: bash

git clone https://github.com/glotzerlab/parsnip.git
cd parsnip

Then, choose one of the following. While parsnip is only dependent on Numpy, additional dependencies are required to run the tests and build the docs.

.. code:: bash

pip install .            # Install with no additional dependencies
pip install .[sympy]     # Install with sympy for symbolic unit cell math
pip install .[tests]     # Install with dependencies required to run tests (including sympy)
pip install .[tests,doc] # Install with dependencies required to run tests and make docs

Dependencies ^^^^^^^^^^^^

.. code:: text

numpy>=1.19 more-itertools

.. _contributing: