{"id":18412384,"url":"https://github.com/abinit/abipy","last_synced_at":"2025-10-18T06:07:55.864Z","repository":{"id":9169775,"uuid":"10968614","full_name":"abinit/abipy","owner":"abinit","description":"Open-source library for analyzing the results produced by ABINIT","archived":false,"fork":false,"pushed_at":"2025-05-09T16:27:32.000Z","size":449914,"stargazers_count":120,"open_issues_count":18,"forks_count":103,"subscribers_count":15,"default_branch":"develop","last_synced_at":"2025-05-09T17:32:39.293Z","etag":null,"topics":["abinit","density-functional-theory","materials-informatics","materials-science","physics","python","science","solid-state-physics"],"latest_commit_sha":null,"homepage":"http://abinit.github.io/abipy","language":"Python","has_issues":true,"has_wiki":null,"has_pages":null,"mirror_url":null,"source_name":null,"license":"other","status":null,"scm":"git","pull_requests_enabled":true,"icon_url":"https://github.com/abinit.png","metadata":{"files":{"readme":"README.rst","changelog":"CHANGELOG.rst","contributing":null,"funding":null,"license":"LICENSE","code_of_conduct":null,"threat_model":null,"audit":null,"citation":null,"codeowners":null,"security":null,"support":null,"governance":null,"roadmap":null,"authors":null,"dei":null,"publiccode":null,"codemeta":null,"zenodo":null}},"created_at":"2013-06-26T13:30:30.000Z","updated_at":"2025-05-09T16:27:36.000Z","dependencies_parsed_at":"2024-05-16T00:11:19.339Z","dependency_job_id":"adabd639-132f-4b04-adc9-0bee9a211807","html_url":"https://github.com/abinit/abipy","commit_stats":{"total_commits":3120,"total_committers":48,"mean_commits":65.0,"dds":0.2173076923076923,"last_synced_commit":"f7f0a2b1f27cc1a676e78b5f40b226c6317ff8cb"},"previous_names":[],"tags_count":18,"template":false,"template_full_name":null,"repository_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/abinit%2Fabipy","tags_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/abinit%2Fabipy/tags","releases_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/abinit%2Fabipy/releases","manifests_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/abinit%2Fabipy/manifests","owner_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/owners/abinit","download_url":"https://codeload.github.com/abinit/abipy/tar.gz/refs/heads/develop","host":{"name":"GitHub","url":"https://github.com","kind":"github","repositories_count":254355335,"owners_count":22057354,"icon_url":"https://github.com/github.png","version":null,"created_at":"2022-05-30T11:31:42.601Z","updated_at":"2022-07-04T15:15:14.044Z","host_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub","repositories_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories","repository_names_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repository_names","owners_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/owners"}},"keywords":["abinit","density-functional-theory","materials-informatics","materials-science","physics","python","science","solid-state-physics"],"created_at":"2024-11-06T03:41:28.686Z","updated_at":"2025-10-09T12:11:32.702Z","avatar_url":"https://github.com/abinit.png","language":"Python","funding_links":[],"categories":[],"sub_categories":[],"readme":".. :Repository: https://github.com/abinit/abipy\n.. :Author: Matteo Giantomassi (http://github.com/abinit)\n\n.. list-table::\n    :stub-columns: 1\n    :widths: 10 90\n\n    * - Package\n      - |pypi-version| |download-with-anaconda| |supported-versions|\n    * - Continuous Integration\n      - |travis-status| |coverage-status|\n    * - Documentation\n      - |docs-github| |launch-nbviewer| |launch-binder|\n\nAbout\n=====\n\nAbiPy is a python library to analyze the results produced by Abinit_,\nan open-source program for the ab-initio calculations of the physical properties of materials\nwithin Density Functional Theory and Many-Body perturbation theory.\nIt also provides tools to generate input files and workflows to automate\nab-initio calculations and typical convergence studies.\nAbiPy is interfaced with pymatgen_ and this allows users to\nbenefit from the different tools and python objects available in the pymatgen ecosystem.\n\nThe official documentation is hosted on `github pages \u003chttp://abinit.github.io/abipy\u003e`_.\nCheck out our `gallery of plotting scripts \u003chttp://abinit.github.io/abipy/gallery/index.html\u003e`_\nand the `gallery of AbiPy workflows \u003chttp://abinit.github.io/abipy/flow_gallery/index.html\u003e`_.\n\nAbiPy can be used in conjunction with matplotlib_, pandas_, scipy_, seaborn_, ipython_ and jupyter_ notebooks\nthus providing a powerful and user-friendly environment for data analysis and visualization.\n\nTo learn more about the integration between jupyter_ and AbiPy, visit `our collection of notebooks\n\u003chttps://abinit.github.io/abipy_book/intro.html\u003e`_\n\nAbiPy is free to use. However, we also welcome your help to improve this library by making your own contributions.\nPlease report any bugs and issues at AbiPy's `Github page \u003chttps://github.com/abinit/abipy\u003e`_.\n\nLinks to talks\n==============\n\nThis section collects links to some of the talks given by the AbiPy developers.\n\n* `The new features of AbiPy v0.9.1. 10th international ABINIT developer workshop, May 31 - June 4, 2021 \u003chttps://gmatteo.github.io/abipy_abidev2021/#/\u003e`_ (New workflows, plotly interface, etc.)\n\n* `Automating ABINIT calculations with AbiPy. Boston MA, 3 March 2019 \u003chttps://gmatteo.github.io/abipy_slides_aps_boston_2019/\u003e`_ (Introduction to AbiPy for newcomers).\n\n* `New features of AbiPy v0.7. Louvain-la-Neuve, Belgium, 20 May 2019 \u003chttps://gmatteo.github.io/abipy_intro_abidev2019/\u003e`_ (How to use the AbiPy command line interface in the terminal)\n\n* `Automatize a DFT code: high-throughput workflows for Abinit\n  \u003chttps://object.cscs.ch/v1/AUTH_b1d80408b3d340db9f03d373bbde5c1e/learn-public/materials/2019_05_aiida_tutorial/day4_abipy_Petretto.pdf\u003e`_\n\n\nGetting AbiPy\n=============\n\nStable version\n--------------\n\nThe version at the Python Package Index (PyPI) is always the latest stable release\nthat can be installed in user mode with::\n\n    pip install abipy --user\n\nNote that you may need to install some optional dependencies manually.\nIn this case, please consult the detailed installation instructions provided by the\n`pymatgen howto \u003chttps://pymatgen.org/installation.html\u003e`_ to install pymatgen\nand then follow the instructions in `our howto \u003chttp://abinit.github.io/abipy/installation\u003e`_.\n\nThe installation process is greatly simplified if you install the required\npython packages through `Anaconda \u003chttps://continuum.io/downloads\u003e`_ (or conda).\nSee `Installing conda`_ to install conda itself.\nWe routinely use conda_ to test new developments with multiple Python versions and multiple virtual environments.\n\nCreate a new conda_ environment based on python 3.12 (let's call it ``abienv``) with::\n\n    conda create --name abienv python=3.12\n\nand activate it with::\n\n    conda activate abienv\n\nYou should see the name of the conda environment in the shell prompt.\n\nFinally, install AbiPy with::\n\n    conda install abipy -c conda-forge --yes\n\nPlease note that, it is also possible to install the abinit executables in the same environment using::\n\n    conda install abinit -c conda-forge --yes\n\nAdditional information on the steps required to install AbiPy with anaconda are available\nin the `anaconda howto \u003chttp://abinit.github.io/abipy/installation#anaconda-howto\u003e`_.\n\n\nDevelopmental version\n---------------------\n\nTo install the developmental version of AbiPy with pip, use::\n\n    pip install git+https://github.com/abinit/abipy.git@develop\n\nClone the `github repository \u003chttps://github.com/abinit/abipy\u003e`_ with::\n\n    git clone https://github.com/abinit/abipy\n\nFor pip, use::\n\n    pip install -r requirements.txt\n    pip install -r requirements-optional.txt\n\nIf you are using conda_ (see `Installing conda`_ to install conda itself), create a new environment (``abienv``) with::\n\n    conda create -n abienv python=3.12\n    source activate abienv\n\nAdd ``conda-forge``, and ``abinit`` to your channels with::\n\n    conda config --add channels conda-forge\n    conda config --add channels abinit\n\nand install the AbiPy dependencies with::\n\n    conda install --file ./requirements.txt\n    conda install --file ./requirements-optional.txt\n\nThe second command is needed for Jupyter only.\nOnce the requirements have been installed (either with pip or conda), execute::\n\n    python setup.py install\n\nor alternately::\n\n    python setup.py develop\n\nto install the package in developmental mode.\nThis is the recommended approach, especially if you are planning to implement new features.\n\nAlso note that the BLAS/Lapack libraries provided by conda have multithreading support activated by default.\nEach process will try to use all of the cores on your machine, which quickly overloads things\nif there are multiple processes running.\n(Also, this is a shared machine, so it is just rude behavior in general).\nTo disable multithreading, add these lines to your ~/.bash_profile::\n\n    export OPENBLAS_NUM_THREADS=1\n    export OMP_NUM_THREADS=1\n\nand then activate these settings with::\n\n    source ~/.bash_profile\n\nThe Github version include test files for complete unit testing.\nTo run the suite of unit tests, make sure you have pytest_ installed and then type::\n\n    pytest\n\nin the AbiPy root directory. A quicker check might be obtained with::\n\n    pytest abipy/core/tests -v\n\nUnit tests require ``scripttest`` that can be installed with::\n\n    pip install scripttest\n\nTwo tests rely on the availability of a\n`pymatgen PMG_MAPI_KEY \u003chttp://pymatgen.org/usage.html#setting-the-pmg-mapi-key-in-the-config-file\u003e` in ~/.pmgrc.yaml.\n\nNote that several unit tests check the integration between AbiPy and Abinit.\nIn order to run the tests, you will need a working set of Abinit executables and  a ``manager.yml`` configuration file.\n\nContributing to AbiPy is relatively easy.\nJust send us a `pull request \u003chttps://help.github.com/articles/using-pull-requests/\u003e`_.\nWhen you send your request, make ``develop`` the destination branch on the repository\nAbiPy uses the `Git Flow \u003chttp://nvie.com/posts/a-successful-git-branching-model/\u003e`_ branching model.\nThe ``develop`` branch contains the latest contributions, and ``master`` is always tagged and points\nto the latest stable release.\n\nInstalling without internet access\n----------------------------------\n\nHere, it is described how to set up a virtual environment with AbiPy on a cluster that cannot reach out to the internet.\nOne first creates a virtual environment with AbiPy on a cluster/computer with access, then ports the required files to the cluster without access, and performs an offline installation.\nWe use Conda for the Python installation and pip for the packages, as the former reduces the odds that incompatibilities arise, while the latter provides convenient syntax for offline package installation.\n\nOne first needs Conda on the cluster with access.\nIf not available by default, follow the instructions for installing Conda at the bottom of this page.\nNext, set up a conda virtual environment with a designated Python version, for example 3.12::\n\n    conda create --name abienv python=3.12\n    conda activate abienv\n\nWe then install AbiPy in this virtual environment, followed by creating requirements.txt, and creating a folder packages/ containing all the wheels (.whl format)::\n\n    pip install abipy\n    pip list --format=freeze \u003e requirements.txt\n    pip download -r requirements.txt -d packages/\n\nNext, the .txt file, the folder, and the miniconda installer must be forwarded to the cluster without internet access.\nYou may have to use a computer that has access to both locations with the scp command.\nIf the offline cluster does not have Conda preinstalled, the Miniconda executable must be ported so that an offline Conda installation can be performed.\nThus, from a computer that can access both locations, execute::\n\n    scp -r connected_cluster:/file/and/folder/location/* .\n    wget https://repo.continuum.io/miniconda/Miniconda3-latest-Linux-x86_64.sh\n    scp -r requirements.txt packages/ Miniconda3-latest-Linux-x86_64.sh disconnected_cluster:/desired/location/\n\nIf conda is not available on the cluster that cannot access the internet, follow the instructions on the bottom of this page to install it.\nNext, one can set up an **offline** virtual environment on the cluster without internet access::\n\n    conda create --name abienv --offline python=3.12\n    conda activate abienv\n\nAt this step, AbiPy might fail to install due to missing/incompatible packages.\nSome of these issues may be solved by repeating the above steps (excluding the environment creation) for packages that are listed as missing/incompatible during the installation procedure, by updating the requirements.txt and packages/ and trying to install again.\nUpon reading::\n\n\tSuccessfully installed abipy-x.y.z\n\nYou can quickly test your installation by running ``python`` followed by ``import abipy``.\n\nInstalling Abinit\n=================\n\nOne of the big advantages of conda over pip is that conda can also install libraries and executables written in Fortran.\nA pre-compiled sequential version of Abinit for Linux and OSx can be installed directly from the\nconda-forge channel with::\n\n    conda install abinit -c conda-forge\n\nOtherwise, follow the usual abinit installation instructions, and make sure abinit can be run with the command::\n\n    abinit --version\n\nConfiguration files for Abipy\n=============================\n\nIn order to run the Abipy tests, you will need a ``manager.yml`` configuration file.\nFor a detailed description of the syntax used in this configuration file\nplease consult the `TaskManager documentation \u003chttp://abinit.github.io/abipy/workflows/taskmanager.html\u003e`_.\n\nAt this stage, for the purpose of checking the installation, you might\ntake the ``shell_nompi_manager.yml`` file from the ``abipy/data/managers`` directory\nof this repository, and copy it with new name ``manager.yml`` to your `$HOME/.abinit/abipy` directory.\nOpen this file and make sure that the ``pre_run`` section contains the shell commands\nneeded to setup the environment before launching Abinit (e.g. Abinit is in $PATH), unless it is available from the environment (e.g. conda).\n\nTo complete the configuration files for Abipy, you might also copy the ``simple_scheduler.yml`` file from the same directory,\nand copy it with name ``scheduler.yml``. Modifications are needed if you are developer.\n\nChecking the installation\n=========================\n\nNow open the python interpreter and import the following three modules\nto check that the python installation is OK::\n\n    import spglib\n    import pymatgen\n    from abipy import abilab\n\nthen quit the interpreter.\n\nFor general information about how to troubleshoot problems that may occur at this level,\nsee the :ref:`troubleshooting` section.\n\n.. _anaconda_howto:\n\nThe Abinit executables are placed inside the anaconda directory associated to the ``abienv`` environment::\n\n    which abinit\n    /Users/gmatteo/anaconda3/envs/abienv/bin/abinit\n\nTo perform a basic validation of the build, execute::\n\n    abinit -b\n\nAbinit should echo miscellaneous information, starting with::\n\n    DATA TYPE INFORMATION:\n    REAL:      Data type name: REAL(DP)\n               Kind value:      8\n               Precision:      15\n\nand ending with::\n\n    ++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++\n    Default optimizations:\n      --- None ---\n\n\n    ++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++\n\nIf successful, one can start to use the AbiPy scripts from the command line to analyze the output results.\nExecute::\n\n    abicheck.py\n\nYou should see (with minor changes)::\n\n    $ abicheck.py\n    AbiPy Manager:\n    [Qadapter 0]\n    ShellAdapter:localhost\n    Hardware:\n       num_nodes: 2, sockets_per_node: 1, cores_per_socket: 2, mem_per_node 4096,\n    Qadapter selected: 0\n\n    Abinitbuild:\n    Abinit Build Information:\n        Abinit version: 8.8.2\n        MPI: True, MPI-IO: True, OpenMP: False\n        Netcdf: True\n\n    Abipy Scheduler:\n    PyFlowScheduler, Pid: 19379\n    Scheduler options: {'weeks': 0, 'days': 0, 'hours': 0, 'minutes': 0, 'seconds': 5}\n\n    Installed packages:\n    Package         Version\n    --------------  ---------\n    system          Darwin\n    python_version  3.6.5\n    numpy           1.14.3\n    scipy           1.1.0\n    netCDF4         1.4.0\n    apscheduler     2.1.0\n    pydispatch      2.0.5\n    yaml            3.12\n    pymatgen        2018.6.11\n\n\n    Abipy requirements are properly configured\n\nIf the script fails with the error message::\n\n    Abinit executable does not support netcdf\n    Abipy requires Abinit version \u003e= 8.0.8 but got 0.0.0\n\nit means that your environment is not property configured or that there's a problem with the binary executable.\nIn this case, look at the files produced in the temporary directory of the flow.\nThe script reports the name of the directory, something like::\n\n    CRITICAL:pymatgen.io.abinit.tasks:Error while executing /var/folders/89/47k8wfdj11x035svqf8qnl4m0000gn/T/tmp28xi4dy1/job.sh\n\nCheck the `job.sh` script for possible typos, then search for possible error messages in `run.err`.\n\nThe last test consists in executing a small calculation with AbiPy and Abinit.\nInside the terminal, execute::\n\n    abicheck.py --with-flow\n\nto run a GS + NSCF band structure calculation for Si.\nIf the software stack is properly configured, the output should end with::\n\n    Work #0: \u003cBandStructureWork, node_id=313436, workdir=../../../../var/folders/89/47k8wfdj11x035svqf8qnl4m0000gn/T/tmpygixwf9a/w0\u003e, Finalized=True\n      Finalized works are not shown. Use verbose \u003e 0 to force output.\n\n    all_ok reached\n\n    Submitted on: Sat Jul 28 09:14:28 2018\n    Completed on: Sat Jul 28 09:14:38 2018\n    Elapsed time: 0:00:10.030767\n    Flow completed successfully\n\n    Calling flow.finalize()...\n\n    Work #0: \u003cBandStructureWork, node_id=313436, workdir=../../../../var/folders/89/47k8wfdj11x035svqf8qnl4m0000gn/T/tmpygixwf9a/w0\u003e, Finalized=True\n      Finalized works are not shown. Use verbose \u003e 0 to force output.\n\n    all_ok reached\n\n\n    Test flow completed successfully\n\nGreat, if you've reached this part it means that you've installed AbiPy and Abinit on your machine!\nWe can finally start to run the scripts in this repo or use one of the AbiPy script to analyze  the results.\n\n\nUsing AbiPy\n===========\n\nBasic usage\n-----------\n\nThere are a variety of ways to use AbiPy, and most of them are illustrated in the ``abipy/examples`` directory.\nBelow is a brief description of the different directories found there:\n\n  * `examples/plot \u003chttp://abinit.github.io/abipy/gallery/index.html\u003e`_\n\n    Scripts showing how to read data from netcdf files and produce plots with matplotlib_\n\n  * `examples/flows \u003chttp://abinit.github.io/abipy/flow_gallery/index.html\u003e`_.\n\n    Scripts showing how to generate an AbiPy flow, run the calculation and use ipython to analyze the data.\n\nAdditional jupyter notebooks with the Abinit tutorials written with AbiPy are available in the\n`abitutorial repository \u003chttps://nbviewer.jupyter.org/github/abinit/abitutorials/blob/master/abitutorials/index.ipynb\u003e`_.\n\nUsers are strongly encouraged to explore the detailed `API docs \u003chttp://abinit.github.io/abipy/api/index.html\u003e`_.\n\nCommand line tools\n------------------\n\nThe following scripts can be invoked directly from the terminal:\n\n* ``abiopen.py``    Open file inside ipython.\n* ``abistruct.py``  Swiss knife to operate on structures.\n* ``abiview.py``    Visualize results from file.\n* ``abicomp.py``    Compare results extracted from multiple files.\n* ``abicheck.py``   Validate integration between AbiPy and Abinit\n* ``abirun.py``     Execute AbiPy flow from terminal.\n* ``abidoc.py``     Document Abinit input variables and Abipy configuration files.\n* ``abinp.py``      Build input files (simplified interface for the AbiPy factory functions).\n* ``abipsp.py``     Download pseudopotential tables from the PseudoDojo.\n\nUse ``SCRIPT --help`` to get the list of supported commands and\n``SCRIPT COMMAND --help`` to get the documentation for ``COMMAND``.\n\nFor further information, please consult the `scripts docs \u003chttp://abinit.github.io/abipy/scripts/index.html\u003e`_ section.\n\n\nInstalling conda\n================\n\nA brief install guide, in case you have not yet used conda ... For a more extensive description, see our\n`Anaconda Howto \u003chttp://abinit.github.io/abipy/installation#anaconda-howto\u003e`_.\n\nDownload the `miniconda installer \u003chttps://conda.io/miniconda.html\u003e`_.\nSelect the version corresponding to your operating system.\n\nAs an example, if you are a Linux user, download and install `miniconda` on your local machine with::\n\n    wget https://repo.continuum.io/miniconda/Miniconda3-latest-Linux-x86_64.sh\n    bash Miniconda3-latest-Linux-x86_64.sh\n\nwhile for MacOSx use::\n\n    curl -o https://repo.continuum.io/miniconda/Miniconda3-latest-MacOSX-x86_64.sh\n    bash Miniconda3-latest-MacOSX-x86_64.sh\n\nAnswer ``yes`` to the question::\n\n    Do you wish the installer to prepend the Miniconda3 install location\n    to PATH in your /home/gmatteo/.bashrc ? [yes|no]\n    [no] \u003e\u003e\u003e yes\n\nSource your ``.bashrc`` file to activate the changes done by ``miniconda`` to your ``$PATH``::\n\n    source ~/.bashrc\n\n.. _troubleshooting:\n\n\nHow to contribute\n=================\n\nTo contribute to Abipy, the standard procedure is as follows:\n\n1.\tFork the repository by clicking the fork button at the top of the screen.\n\n2.\tClone your repository locally using::\n\n        git clone https://github.com/USERNAME/abipy.git\n\n    where USERNAME is your GitHub username.\n\n3.\tRegister the upstream repository with::\n\n        git remote add trunk https://github.com/abinit/abipy.git\n\n4.  Pull the latest commit from the develop branch of trunk with::\n\n        git pull trunk develop\n\n5. Modify the code and commit your changes to your fork using::\n\n    git commit -a -m \"Message describing the modifications\"\n    git push\n\n6. Use the graphical interface provided by GitHub to open pull requests from your branch to trunk develop.\n\nLicense\n=======\n\nAbiPy is released under the GNU GPL license. For more details see the LICENSE file.\n\n.. _Python: http://www.python.org/\n.. _Abinit: https://www.abinit.org\n.. _abinit-channel: https://anaconda.org/abinit\n.. _pymatgen: http://pymatgen.org\n.. _matplotlib: http://matplotlib.org\n.. _pandas: http://pandas.pydata.org\n.. _scipy: https://www.scipy.org/\n.. _seaborn: https://seaborn.pydata.org/\n.. _ipython: https://ipython.org/index.html\n.. _jupyter: http://jupyter.org/\n.. _netcdf: https://www.unidata.ucar.edu/software/netcdf/docs/faq.html#whatisit\n.. _abiconfig: https://github.com/abinit/abiconfig\n.. _conda: https://conda.io/docs/\n.. _netcdf4-python: http://unidata.github.io/netcdf4-python/\n.. _spack: https://github.com/LLNL/spack\n.. _pytest: https://docs.pytest.org/en/latest/contents.html\n.. _numpy: http://www.numpy.org/\n\n\n.. |pypi-version| image:: https://badge.fury.io/py/abipy.svg\n    :alt: PyPi version\n    :target: https://badge.fury.io/py/abipy\n\n.. |travis-status| image:: https://travis-ci.org/abinit/abipy.svg?branch=develop\n    :alt: Travis status\n    :target: https://travis-ci.org/abinit/abipy\n\n.. |coverage-status| image:: https://coveralls.io/repos/github/abinit/abipy/badge.svg?branch=develop\n    :alt: Coverage status\n    :target: https://coveralls.io/github/abinit/abipy?branch=develop\n\n.. |download-with-anaconda| image:: https://anaconda.org/abinit/abipy/badges/installer/conda.svg\n    :alt: Download with Anaconda\n    :target: https://anaconda.org/conda-forge/abinit\n\n.. |launch-binder| image:: https://mybinder.org/badge.svg\n    :alt: Launch binder\n    :target: https://mybinder.org/v2/gh/abinit/abipy/develop\n\n.. |launch-nbviewer| image:: https://img.shields.io/badge/render-nbviewer-orange.svg\n    :alt: Launch nbviewer\n    :target: https://nbviewer.jupyter.org/github/abinit/abitutorials/blob/master/abitutorials/index.ipynb\n\n.. |supported-versions| image:: https://img.shields.io/pypi/pyversions/abipy.svg?style=flat\n    :alt: Supported versions\n    :target: https://pypi.python.org/pypi/abipy\n\n.. |requires| image:: https://requires.io/github/abinit/abipy/requirements.svg?branch=develop\n     :target: https://requires.io/github/abinit/abipy/requirements/?branch=develop\n     :alt: Requirements Status\n\n.. |docs-github| image:: https://img.shields.io/badge/docs-ff69b4.svg\n     :alt: AbiPy Documentation\n     :target: http://abinit.github.io/abipy\n","project_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fabinit%2Fabipy","html_url":"https://awesome.ecosyste.ms/projects/github.com%2Fabinit%2Fabipy","lists_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fabinit%2Fabipy/lists"}