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        "author": "Guillermo Avenda\u00f1o Franco",
        "author_email": "gufranco@mail.wvu.edu",
        "bugtrack_url": null,
        "classifiers": [
            "Development Status :: 4 - Beta",
            "Intended Audience :: Science/Research",
            "License :: OSI Approved :: MIT License",
            "Natural Language :: English",
            "Operating System :: POSIX",
            "Programming Language :: Python",
            "Programming Language :: Python :: 3",
            "Programming Language :: Python :: 3.6",
            "Programming Language :: Python :: 3.7",
            "Topic :: Scientific/Engineering :: Chemistry",
            "Topic :: Scientific/Engineering :: Physics"
        ],
        "description": "[![Build Status](https://travis-ci.org/MaterialsDiscovery/PyChemia.svg?branch=master)](https://travis-ci.org/MaterialsDiscovery/PyChemia)\n[![PyPI version](https://badge.fury.io/py/pychemia.svg)](https://badge.fury.io/py/pychemia)\n[![Coverage Status](https://coveralls.io/repos/github/MaterialsDiscovery/PyChemia/badge.svg?branch=master)](https://coveralls.io/github/MaterialsDiscovery/PyChemia?branch=master)\n[![Documentation Status](https://readthedocs.org/projects/pychemia/badge/?version=latest)](http://pychemia.readthedocs.io/en/latest/?badge=latest)\n[![HitCount](http://hits.dwyl.io/MaterialsDiscovery/PyChemia.svg)](http://hits.dwyl.io/MaterialsDiscovery/PyChemia)\n\nPyChemia, Python Framework for Materials Discovery and Design\n=============================================================\n\n![PyChemia](https://raw.githubusercontent.com/MaterialsDiscovery/PyChemia/master/docs/_static/PyChemia_Small.png)\n\nPyChemia is an open-source Python Library for materials structural\nsearch. The purpose of the initiative is to create a method agnostic\nframework for materials discovery and design using a variety of methods\nfrom Minima Hoping to Soft-computing based methods. PyChemia is also a\nlibrary for data-mining, using several methods to discover interesting\ncandidates among the materials already processed.\n\nThe core of the library is the Structure python class, it is able to\ndescribe periodic and non-periodic structures. As the focus of this\nlibrary is structural search the class defines extensive capabilities to\nmodify atomic structures.\n\nThe library includes capability to read and write in several ab-initio\ncodes. At the level of DFT, PyChemia support VASP, ABINIT and Octopus.\nAt Tight-binding level development is in process to support DFTB+ and\nFireball. This allows the library to compute electronic-structure\nproperties using state-of-the-art ab-initio software packages and\nextract properties from those calculations.\n\nInstallation\n============\n\nYou can install pychemia in several ways. We are showing 3 ways of\ninstalling PyChemia inside a Virtual environment. A virtual environment\nis a good way of isolating software packages from the pacakges installed\nwith the Operating System. The decision on which method to use\ndepends if you want to use the most recent code or the package uploaded\nfrom time to time to PyPi. The last method is particularly suited for\ndevelopers who want to change the code and get those changes operative without\nan explicit instalation.\n\n\nInstalling with pip from pypi.org on a virtual environment \n----------------------------------------------------------\n\nThis method installs PyChemia from the packages uploaded\nto PyPi every month. It will provides a version of \nPyChemia that is stable.\n\nFirst, create and activate the virtual environment.\nWe are using the name `pychemia_ve`, but that is arbitrary.\n\n```bash\nvirtualenv pychemia_ve\nsource pychemia_ve/bin/activate\n```\n\nWhen the virtual environment is activated, your prompt \nchanges to `(pychemia_ve)...$`. Now, install pychemia \nwith pip\n\n```bash\npython3 -m pip install pychemia\n```\n\nInstalling with pip from a cloned repo on a virtual environment\n---------------------------------------------------------------\n\nThis method installs PyChemia from the Github repo.\nThe method will install PyChemia from the most recent sources.\n\nFirst, create and activate the virtual environment.\nWe are using the name `pychemia_ve`, but that is arbitrary.\n\n```bash\nvirtualenv pychemia_ve\nsource pychemia_ve/bin/activate\n```\n\nSecond, clone the repository from GitHub\n\n```bash\ngit clone https://github.com/MaterialsDiscovery/PyChemia.git\n```\n\nFinally, install from the repo folder\n\n```bash\npython3 -m pip install PyChemia\n```\n\nUsing PyChemia from repo folder on a virtual environment\n--------------------------------------------------------\n\nThis method is mostly used for development. \nIn this way PyChemia is not actually installed and changes to the code\nwill take inmediate effect.\n\nFirst, create and activate the virtual environment.\nWe are using the name `pychemia_ve`, but that is arbitrary.\n \n```bash\nvirtualenv pychemia_ve\nsource pychemia_ve/bin/activate\n```\n\nClone the repository\n\n```bash\ngit clone https://github.com/MaterialsDiscovery/PyChemia.git\n```\n\nGo to repo folder, install Cython with pip and \nexecute `setup.py` to build the Cython modules.  \n\n```bash\ncd PyChemia\npython3 -m pip install Cython\npython3 setup.py build_ext --inplace\npython3 setup.py build\n```\n\nFinally, install the packages required for PyChemia to work\n\n```bash\npython3 -m pip install -r requirements.txt\n```\n\nSet the variable $PYTHONPATH to point to PyChemia folder, in the case of bash it will be:\n\n```bash\nexport PYTHONPATH=`path`\n```\n\nOn C shell (csh or tcsh)\n\n```csh\nsetenv PYTHONPATH `path`\n```\n\nPyChemia requirements\n=====================\n\nPyChemia relies on a number of other python packages to \noperate. Some of them are mandatory and they must be installed.\nOther packages are optional and their absence will only constrain\ncertain capabilities. \n\nMandatory\n---------\n\n1.  Python >= 3.6\n    The library is tested on Travis for Python 3.6 up to 3.9\n    Support for Python 2.7 has been removed\n\n    https://travis-ci.org/MaterialsDiscovery/PyChemia\n\n2.  [Numpy](http://www.numpy.org/ \"Numpy\") >= 1.19\n    Fundamental library for numerical intensive computation in Python.\n    Numpy arrays are essential for efficient array manipulation. \n\n3.  [SciPy](http://scipy.org/ \"SciPy\") >= 1.5\n    Used mostly for Linear Algebra, FFT and spatial routines.\n\n4.  [Spglib](http://spglib.sourceforge.net/) >= 1.9\n    Used to determine symmetry groups for periodic structures\n\n5.  [Matplotlib](http://matplotlib.org/  \"Matplotlib\") >= 3.3\n    Used to plot band structures, densities of states and other 2D plots\n\n6.  [PyMongo](http://api.mongodb.org/python/current/) >= 3.11\n    Used for structural search PyChemia relies strongly in MongoDB and its python driver. \n    For the MongoDB server, any version beyond 3.11 should be fine. \n    We have tested pychemia on MongoDB 4.0\n\n7.  [psutil](https://github.com/giampaolo/psutil) >= 5.8\n    Cross-platform lib for process and system monitoring in Python\n\n\nOptional\n--------\n\n1.  [nose](https://nose.readthedocs.io/en/latest/) >= 1.3.7 A python\n    library for testing, simply go to the source directory and execute\n\n    nosetests -v\n\n2.  [pytest](https://docs.pytest.org/en/latest/) \n    Another utility for testing. \n\n3.  [Pandas](http://pandas.pydata.org/ \"Pandas\")\n    Library for Data Analysis used by the datamining modules\n\n4.  [PyMC](http://pymc-devs.github.io/pymc/index.html)\n    PyMC is a python module that implements Bayesian statistical models \n    and fitting algorithms\n    Important for the datamining capabilities of PyChemia\n\n5.  [Mayavi](http://docs.enthought.com/mayavi/mayavi/ \"Mayavi\") >= 4.1\n    Some basic visualization tools are incorporated using this library\n\n6.  [ScientificPython](http://dirac.cnrs-orleans.fr/plone/software/scientificpython/overview/ \"Scientific Python\") >2.6\n    This library is used for reading and writing NetCDF files\n\n7.  [pymatgen](http://www.pymatgen.org \"pymatgen\") >= 2.9\n    pymatgen is an excellent library for materials analysis\n\n8.  [ASE](https://wiki.fysik.dtu.dk/ase/ \"Atomic Simulation Environment\")\n    Atomic Simulation Environment is another good library for ab-initio calculations.\n    Quite impressive for the number of ab-initio packages supported\n\n9.  [qmpy](http://oqmd.org/static/docs/index.html \"qmpy\")\n    The Python library behind the [Open Quantum Materials Database](http://oqmd.org).\n    The OQMD is a database of DFT calculated structures.\n    For the time being the database contains more than 300000 structures, with more than\n    90% of them with the electronic ground-state computed.\n\n10. [coverage](https://bitbucket.org/ned/coveragepy) >= 4.0.1\n    Provides code coverage analysis\n\n11. [python-coveralls](https://github.com/z4r/python-coveralls)\n    To submit coverage information to coveralls.io\n\n    https://coveralls.io/github/MaterialsDiscovery/PyChemia\n\nDocumentation\n=============\n\nInstructions for installation, using and programming scripts with PyChemia\ncan be found on two repositories for documentation:\n\n* Read The Docs:\n   \n   http://pychemia.readthedocs.io/en/latest\n      \n* Python Hosted:\n    \n   http://pythonhosted.org/pychemia\n\nDocumentation is hosted on [Read the Docs](https://readthedocs.org/projects/pychemia/) also available with Short URLs [readthedocs](http://pychemia.readthedocs.io) and [rtfd](http://pychemia.rtfd.io)\n\nDocumentation is also hosted on [Python Hosted](http://pythonhosted.org/pychemia/index.html)\n\nSources\n=======\n\nThe main repository is on [GitHub](https://github.com/MaterialsDiscovery/PyChemia)\n\nSources and wheel binaries are also distrubuted on [PyPI](https://pypi.python.org/pypi/pychemia) or [PyPI](https://pypi.org/project/pychemia/)\n\nStructure of the Library\n========================\n\n![PyChemia](https://raw.githubusercontent.com/MaterialsDiscovery/PyChemia/master/docs/_static/PyChemia_code.png)\n\n![PyChemia](https://raw.githubusercontent.com/MaterialsDiscovery/PyChemia/master/docs/_static/PyChemia_workflow.png)\n\nContributors\n============\n\n1.  Prof. Aldo H. Romero [West Virginia University] (Project Director)\n\n2.  Guillermo Avenda\u00f1o-Franco [West Virginia University]\n    (Basic Infrastructure)\n\n3.  Adam Payne [West Virginia University] (Bug fixes (Populations,\n    Relaxators, and KPoints) )\n\n4.  Irais Valencia Jaime [West Virginia University] (Simulation\n    and testing)\n\n5.  Sobhit Singh [West Virginia University] (Data-mining)\n\n6.  Francisco Mu\u00f1oz [Universidad de Chile] (PyPROCAR)\n\n7.  Wilfredo Ibarra Hernandez [West Virginia University] (Interface\n    with MAISE)\n\n\n",
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