pyobjcryst 2026.1.0

Citation

If you use diffpy.srfit in a scientific publication, we would like you to cite this package as

P. Juhás, C. L. Farrow, X. Yang, K. R. Knox and S. J. L. Billinge, Complex modeling: a strategy and software program for combining multiple information sources to solve ill posed structure and nanostructure inverse problems, Acta Crystallogr. A 71, 562-568 (2015).

and

V. Favre-Nicolin and R. Cerný, FOX, ‘free objects for crystallography’: a modular approach to ab initio structure determination from powder diffraction, J. Appl. Cryst. 35, 734-743 (2002)

The second paper describes the c++ crystallographic objects in ObjCryst++ that are wrapped by pyobjcryst

Installation

The latest release of pyobjcryst runs in python versions 3.12, 3.13 and 3.14. You may specify an earlier release if you need it to run in an earlier version of Python.

The preferred method is to use Miniconda Python and install from the “conda-forge” channel of Conda packages.

To permanently add “conda-forge” to the conda channels (recommended), run the following in a terminal.

conda config --add channels conda-forge

We want to install our packages in a suitable conda environment. The following creates and activates a new environment named pyobjcryst-env

conda create -n pyobjcryst-env pyobjcryst
conda activate pyobjcryst-env

To confirm that the installation was successful, type

python -c "import pyobjcryst; print(pyobjcryst.__version__)"

The output should print the latest version displayed on the badges above.

pyobjcryst is also included in the diffpy.cmi collection of packages for structure analysis and so can be installed by

conda install -c conda-forge diffpy.cmi

and following the instructions in the diffpy.cmi documentation to install packs containing pyobjcryst and its libraries.

Getting Started

You may consult our online documentation for tutorials and API references.

Alternative methods of installation

These approaches are not recommended but reproduced here for advanced users. You can use pip to download and install the latest release from Python Package Index.

Pyobjcryst can be installed from pip. We recommend installing the dependencies that can be found in requirements/conda.txt from conda-forge, e.g.,

conda create -n pyobjcryst-env python=3.14
conda activate pyobjcryst-env
conda install -c conda-forge numpy libobjcryst libboost-devel libboost-python packaging ipywidgets matplotlib-base ipympl py3dmol
pip install pyobjcryst

If you prefer to install from sources, after installing the dependencies, obtain the source archive from GitHub. Once installed, cd into your pyobjcryst directory and run the following

pip install .

An alternative way of installing pyobjcryst is to use the SCons tool, which can speed up the process by compiling C++ files in several parallel jobs (-j4):

conda install scons
conda install --file requirements/conda.txt
scons -j4 dev

See scons -h for description of build targets and options.

Alternatively, on Ubuntu Linux the required software can be installed using

sudo apt-get install \
     python-setuptools python-numpy scons \
     build-essential python-dev libboost-all-dev

If this doesn’t work, please see the requirements/conda.txt file for the latest list of requirements.

The libobjcryst library can also be installed as per the instructions at https://github.com/diffpy/libobjcryst. Make sure other required software are also in place and then run from the pyobjcryst directory

pip install .

You may need to use sudo with system Python so the process is allowed to copy files to system directories, unless you are installing into a conda environment. If administrator (root) access is not available, see the usage information from python setup.py install –help for options to install to a user-writable location.

Testing your installation

The installation integrity can be verified by executing the included tests with

First install test dependencies then type pytest:

conda install --file requirements/tests.txt
pytest

Support and Contribute

If you see a bug or want to request a feature, please report it as an issue and/or submit a fix as a PR.

Feel free to fork the project and contribute. To install pyobjcryst in a development mode, with its sources being directly used by Python rather than copied to a package directory, use the following in the root directory

pip install -e .

To ensure code quality and to prevent accidental commits into the default branch, please set up the use of our pre-commit hooks.

1. Install pre-commit in your working environment by running conda install pre-commit.

2. Initialize pre-commit (one time only) pre-commit install.

Thereafter your code will be linted by black and isort and checked against flake8 before you can commit. If it fails by black or isort, just rerun and it should pass (black and isort will modify the files so should pass after they are modified). If the flake8 test fails please see the error messages and fix them manually before trying to commit again.

When developing it is preferable to compile the C++ files with SCons using the build=debug option, which compiles the extension module with debug information and C-assertions checks

scons -j4 build=debug dev

Improvements and fixes are always appreciated.

Before contributing, please read our Code of Conduct.

Contact

For more information on pyobjcryst please visit the project web-page or email Simon Billinge at sbillinge@ucsb.edu.

You can also contact Vincent Favre-Nicolin (favre@esrf.fr) if you are using pyobjcryst outside diffpy, e.g. to display structures in a notebook, refine powder patterns or solve structures using the global optimisation algorithms, etc..

Acknowledgements

This package bundles the following IUCr data files for bona fide research use:

• cpd-1a.prn: Powder diffraction dataset from the IUCr CPD Round Robin on Quantitative Phase Analysis.

  Source: https://www.iucr.org/__data/iucr/powder/QARR/col/cpd-1a.prn

  Round Robin on Quantitative Phase Analysis: Madsen, I. (1997) ‘Round Robin on Quantitative Phase Analysis’, Powder Diffraction, 12(1), pp. 1–2. Available at: https://doi.org/10.1017/S0885715600020212.

pyobjcryst is built and maintained with scikit-package.