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    "info": {
        "author": "Caleb Bell",
        "author_email": "Caleb.Andrew.Bell@gmail.com",
        "bugtrack_url": null,
        "classifiers": [
            "Development Status :: 3 - Alpha",
            "Intended Audience :: Developers",
            "Intended Audience :: Education",
            "Intended Audience :: Manufacturing",
            "Intended Audience :: Science/Research",
            "License :: OSI Approved :: MIT License",
            "Natural Language :: English",
            "Operating System :: MacOS",
            "Operating System :: Microsoft :: Windows",
            "Operating System :: POSIX",
            "Operating System :: POSIX :: BSD",
            "Operating System :: POSIX :: Linux",
            "Operating System :: Unix",
            "Programming Language :: Python",
            "Programming Language :: Python :: 2",
            "Programming Language :: Python :: 2.7",
            "Programming Language :: Python :: 3",
            "Programming Language :: Python :: 3.3",
            "Programming Language :: Python :: 3.4",
            "Programming Language :: Python :: 3.5",
            "Programming Language :: Python :: 3.6",
            "Programming Language :: Python :: Implementation :: CPython",
            "Topic :: Education",
            "Topic :: Scientific/Engineering :: Atmospheric Science",
            "Topic :: Scientific/Engineering :: Chemistry",
            "Topic :: Scientific/Engineering :: Physics"
        ],
        "description": "======\nthermo\n======\n\n.. image:: http://img.shields.io/pypi/v/thermo.svg?style=flat\n   :target: https://pypi.python.org/pypi/thermo\n   :alt: Version_status\n.. image:: http://img.shields.io/badge/docs-latest-brightgreen.svg?style=flat\n   :target: https://thermo.readthedocs.io/en/latest/\n   :alt: Documentation\n.. image:: http://img.shields.io/travis/CalebBell/thermo/master.svg?style=flat\n   :target: https://travis-ci.org/CalebBell/thermo\n   :alt: Build_status\n.. image:: http://img.shields.io/badge/license-MIT-blue.svg?style=flat\n   :target: https://github.com/CalebBell/thermo/blob/master/LICENSE.txt\n   :alt: license\n.. image:: https://img.shields.io/coveralls/CalebBell/thermo.svg\n   :target: https://coveralls.io/github/CalebBell/thermo\n   :alt: Coverage\n.. image:: https://img.shields.io/pypi/pyversions/thermo.svg\n   :target: https://pypi.python.org/pypi/thermo\n   :alt: Supported_versions\n.. image:: https://badges.gitter.im/CalebBell/thermo.svg\n   :alt: Join the chat at https://gitter.im/CalebBell/thermo\n   :target: https://gitter.im/CalebBell/thermo\n.. image:: http://img.shields.io/appveyor/ci/calebbell/thermo.svg\n   :target: https://ci.appveyor.com/project/calebbell/thermo/branch/master\n   :alt: Build_status\n.. image:: https://zenodo.org/badge/62404647.svg\n   :alt: Zendo\n   :target: https://zenodo.org/badge/latestdoi/62404647\n\n\n.. contents::\n\nWhat is thermo?\n---------------\n\nthermo is open-source software for engineers, scientists, technicians and\nanyone trying to understand the universe in more detail. It facilitates \nthe retrieval of constants of chemicals, the calculation of temperature\nand pressure dependent chemical properties (both thermodynamic and \ntransport), the calculation of the same for chemical mixtures (including\nphase equilibria), and assorted information of a regulatory or legal \nnature about chemicals.\n\nThe thermo library depends on the SciPy library to povide numerical constants,\ninterpolation, integration, differentiation, and numerical solving functionality.\nthermo all operating systems which support Python, is quick to install, and is \nfree of charge. thermo is designed to be easy to use while still providing powerful\nfunctionality. If you need to know something about a chemical, give thermo a try.\n\nInstallation\n------------\n\nGet the latest version of thermo from\nhttps://pypi.python.org/pypi/thermo/\n\nIf you have an installation of Python with pip, simple install it with:\n\n    $ pip install thermo\n\nTo get the git version, run:\n\n    $ git clone git://github.com/CalebBell/thermo.git\n\nDocumentation\n-------------\n\nthermo's documentation is available on the web:\n\n    http://thermo.readthedocs.io/\n\nGetting Started\n---------------\n\nThe library is designed around base SI units only for development\nconvenience. All chemicals default to 298.15 K and 101325 Pa on \ncreation, unless specified. All constant-properties are loaded on\nthe creation of a Chemical instance.\n\n.. code-block:: python\n\n    >>> from thermo.chemical import Chemical\n    >>> tol = Chemical('toluene')\n    >>> tol.Tm, tol.Tb, tol.Tc\n    (179.2, 383.75, 591.75)\n    >>> tol.rho, tol.Cp, tol.k, tol.mu\n    (862.2380125827527, 1706.0746129119084, 0.13034801424538045, 0.0005521951637285534)\n\n\nFor pure species, the phase is easily\nidentified, allowing for properties to be obtained without needing\nto specify the phase. However, the properties are also available in the\nhypothetical gas phase (when under the boiling point) and in the hypothetical\nliquid phase (when above the boiling point) as these properties are needed\nto evaluate mixture properties. Specify the phase of a property to be retrieved \nby appending 'l' or 'g' or 's' to the property.\n\n.. code-block:: python\n\n    >>> tol.rhog, tol.Cpg, tol.kg, tol.mug\n    (4.032009635018902, 1126.5533755283168, 0.010736843919054837, 6.973325939594919e-06)\n\nCreating a chemical object involves identifying the appropriate chemical by name\nthrough a database, and retrieving all constant and temperature and pressure dependent\ncoefficients from Pandas DataFrames - a ~1 ms process. To obtain properties at different\nconditions quickly, the method calculate has been implemented. \n    \n.. code-block:: python\n\n    >>> tol.calculate(T=310, P=101325)\n    >>> tol.rho, tol.Cp, tol.k, tol.mu\n    (851.1582219886011, 1743.280497511088, 0.12705495902514785, 0.00048161578053599225)\n    >>> tol.calculate(310, 2E6)\n    >>> tol.rho, tol.Cp, tol.k, tol.mu\n    (852.7643604407997, 1743.280497511088, 0.12773606382684732, 0.0004894942399156052)\n\nEach property is implemented through an independent object-oriented method, based on \nthe classes TDependentProperty and TPDependentProperty to allow for shared methods of\nplotting, integrating, differentiating, solving, interpolating, sanity checking, and\nerror handling. For example, to solve for the temperature at which the vapor pressure\nof toluene is 2 bar. For each property, as many methods of calculating or estimating\nit are included as possible. All methods can be visualized independently:\n\n.. code-block:: python\n\n    >>> Chemical('toluene').VaporPressure.solve_prop(2E5)\n    409.5909115602903\n    >>> Chemical('toluene').SurfaceTension.plot_T_dependent_property()\n\nMixtures are supported and many mixing rules have been implemented. However, there is\nno error handling. Inputs as mole fractions (`zs`), mass fractions (`ws`), or volume\nfractions (`Vfls` or `Vfgs`) are supported. Some shortcuts are supported to predefined\nmixtures.\n\n.. code-block:: python\n\n    >>> from thermo.chemical import Mixture\n    >>> vodka = Mixture(['water', 'ethanol'], Vfls=[.6, .4], T=300, P=1E5)\n    >>> vodka.Prl,vodka.Prg\n    (35.130757024029364, 0.9490586345579207)\n    >>> air = Mixture('air', T=400, P=1e5)\n    >>> air.Cp\n    1013.7956176577834\n\nRoadmap\n-------\n\nThis library includes a huge database of (70000+) chemicals taken from the PubChem\ndatabase (selected by the availability of CAS numbers, which all data included here \nis indexed by). Regretably, only ~20000 of those have even one chemical property\napart from metadata (molecular weight, etc.). Some niche aspects (ions, ionic \nliquids) have been poorly served by the PubChem, and so extra databases manually\ncurated for these are in development. \n\nThe Chemical and Mixture classes may be subject to considerably change in the\ninterests of performance in the future. Because of this, they have been poorly\ndocumented and tested. However, each individual property method is mature and\nnot expected to change. Documentation and testing are huge strengths, and\nit is intended to keep up the current quality of both.\n\nA number of features have been worked on but are not yet included in this \nlibrary, not ordered by any priority.\n\nPhase equilibria according to activity coefficient methods (NRTL, UNIQUAC, \nWilson, Van Laar, Margules): Functionality has been tentatively created, but\nis not included due to the lack of coefficient databases. Suggestions would\nbe very welcome. UNIFAC has been tested, but is also not included due to the\nlack of automatic group contribution assignment.\n\nRigorous equations of state for excess properties, and phase equilibria:\nTested EOSs are PR, LK, VdW, SRK, BWRS, and a few others. The holdup here\nis the determination of analytical expressions for their partial \nderivatives of mixtures. SymPy is immensely helpful, and has been used to\nsuccessfully obtain specific values of those derivatives at specific points.\nUnfortunately, most listed forms as in Walas (1985) are incorrect. If\nexpressions are not eventually found, this will be implemented with numerical\nderivatives only.\n\nFundamental Equations of State: The IAPWS-95 model, and that of 20 fluids\nin \"Short Fundamental Equations of State for 20 Industrial Fluids\" have\nbeen implemented. However, they are quite slow in Python - taking 2-10 ms\nto solve. This can be reduced to ~1-2 ms if Cython is used, however, this\nmeans that distribution through PyPi because harder. Suggestions about\nthis are welcome. Currently, the phenomenal library CoolProp is used instead;\nwhich has already been packaged for PyPi. Even if custom code is released\nfor these EOS, CoolProp will remain prioritized; developed in C++, it is\nsimply much faster than code can be in pure Python.\n\nElectrolyte models: The Pitzer, Bromley, and LIQUAC models have been in\ndevelopment along with parameter databases for them. The ion database\ncurrently has ~300 species, few of them with much data available.\nPhase equilibria with these models is also in progress.\n\nSafety information, regulatory information, and economic data for chemicals:\nThis functionality has been included, but is not yet very mature. This is \na low priority.\n\nDevelopment follows pep8 and uses pytest for testing. Both Python 2 and 3 are\nsupported.\n\nLatest source code\n------------------\n\nThe latest development version of thermo's sources can be obtained at\n\n    https://github.com/CalebBell/thermo\n\n\nBug reports\n-----------\n\nTo report bugs, please use the thermo's Bug Tracker at:\n\n    https://github.com/CalebBell/thermo/issues\n\n\nLicense information\n-------------------\n\nSee ``LICENSE.txt`` for information on the terms & conditions for usage\nof this software, and a DISCLAIMER OF ALL WARRANTIES.\n\nAlthough not required by the thermo license, if it is convenient for you,\nplease cite thermo if used in your work. Please also consider contributing\nany changes you make back, and benefit the community.\n\n\nCitation\n--------\n\nTo cite thermo in publications use::\n\n    Caleb Bell (2016). thermo: Chemical properties component of Chemical Engineering Design Library (ChEDL)\n    https://github.com/CalebBell/thermo.",
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