{ "info": { "author": "Will Long", "author_email": "long@latech.edu", "bugtrack_url": null, "classifiers": [ "License :: OSI Approved :: MIT License", "Operating System :: OS Independent", "Programming Language :: Python :: 3" ], "description": "# Summary\nPython library to calculate psychrometric states of moist air.\n\n# Installation\nPlace either psySI.py or psyIP.py file in your working directory. If you\nare working with the international system of units (i.e. SI) then use psySI.py.\nIf you are are working with imperial units (i.e. IP) then use psyIP.py.\n\n# Description\npsypy is a python library that calculates psychrometric states of moist air\nusing ASHRAE 2009 Fundamentals formulations. Atmospheric pressure, and two\nindependent properties must be given to calculate all other state properties.\nThe state properties include: dry bulb temperature (DBT), specific enthalpy\n(H), relative humidity (RH), specific volume (V), humidity ratio (W), and wet\nbulb temperature (WBT). Examples can be found in the examples.py file.\n\n\n", "description_content_type": "text/markdown", "docs_url": null, "download_url": "", "downloads": { "last_day": -1, "last_month": -1, "last_week": -1 }, "home_page": "https://github.com/longapalooza/psypy", "keywords": "", "license": "", "maintainer": "", "maintainer_email": "", "name": "psypy", "package_url": "https://pypi.org/project/psypy/", "platform": "", "project_url": "https://pypi.org/project/psypy/", "project_urls": { "Homepage": "https://github.com/longapalooza/psypy" }, "release_url": "https://pypi.org/project/psypy/0.0.2/", "requires_dist": null, "requires_python": "", "summary": "Python library for calculating psychrometric states of moist air.", "version": "0.0.2" }, "last_serial": 5011073, "releases": { "0.0.2": [ { "comment_text": "", "digests": { "md5": "9c7b00b211ce76097406dc1c67a59019", "sha256": "009b1ef163227cc833ff3992886ae8707b3a0ffe44f0423dbcb7ae4dcf2199af" }, "downloads": -1, "filename": "psypy-0.0.2-py3-none-any.whl", "has_sig": false, "md5_digest": "9c7b00b211ce76097406dc1c67a59019", "packagetype": "bdist_wheel", "python_version": "py3", "requires_python": null, "size": 7360, "upload_time": "2019-04-01T00:56:16", "url": "https://files.pythonhosted.org/packages/81/28/6767224b7722fdaac3000a97f1da0bbcada65d0ed5b8c482c3229cd080af/psypy-0.0.2-py3-none-any.whl" }, { "comment_text": "", "digests": { "md5": "7470130bca602a13a397f4192dca3eee", "sha256": "0572f2c1940662e313e835f7c7da902a02af6d6cd62694607f3911e66597c951" }, "downloads": -1, "filename": "psypy-0.0.2.tar.gz", "has_sig": false, "md5_digest": "7470130bca602a13a397f4192dca3eee", "packagetype": "sdist", "python_version": "source", "requires_python": null, "size": 4240, "upload_time": "2019-04-01T00:56:18", "url": "https://files.pythonhosted.org/packages/4d/5f/56f62916f6b847dbeab4a06b4e3ab05cfcb92b87fd5c7896876f104a3770/psypy-0.0.2.tar.gz" } ] }, "urls": [ { "comment_text": "", "digests": { "md5": "9c7b00b211ce76097406dc1c67a59019", "sha256": "009b1ef163227cc833ff3992886ae8707b3a0ffe44f0423dbcb7ae4dcf2199af" }, "downloads": -1, "filename": "psypy-0.0.2-py3-none-any.whl", "has_sig": false, "md5_digest": "9c7b00b211ce76097406dc1c67a59019", "packagetype": "bdist_wheel", "python_version": "py3", "requires_python": null, "size": 7360, "upload_time": "2019-04-01T00:56:16", "url": "https://files.pythonhosted.org/packages/81/28/6767224b7722fdaac3000a97f1da0bbcada65d0ed5b8c482c3229cd080af/psypy-0.0.2-py3-none-any.whl" }, { "comment_text": "", "digests": { "md5": "7470130bca602a13a397f4192dca3eee", "sha256": "0572f2c1940662e313e835f7c7da902a02af6d6cd62694607f3911e66597c951" }, "downloads": -1, "filename": "psypy-0.0.2.tar.gz", "has_sig": false, "md5_digest": "7470130bca602a13a397f4192dca3eee", "packagetype": "sdist", "python_version": "source", "requires_python": null, "size": 4240, "upload_time": "2019-04-01T00:56:18", "url": "https://files.pythonhosted.org/packages/4d/5f/56f62916f6b847dbeab4a06b4e3ab05cfcb92b87fd5c7896876f104a3770/psypy-0.0.2.tar.gz" } ] }