pyecosim


Namepyecosim JSON
Version 0.0.0 PyPI version JSON
download
home_page
SummaryPython-based Eco-friendly Simulation and Lifecycle Assessment Model
upload_time2023-08-06 19:12:31
maintainer
docs_urlNone
authorHedi ROMDHANA
requires_python>=3.4
licenseGPLv3
keywords lca simulation sustainability
VCS
bugtrack_url
requirements No requirements were recorded.
Travis-CI No Travis.
coveralls test coverage No coveralls.
            # PyEcoSim
`PyEcoSim` performs a comprehensive Life Cycle Assessment (LCA) calculation. By default, it includes pre-installed data, such as life cycle inventories and two environmental impact calculation methods. It offers flexibility to add other calculation methods and inventories, enabling complete customization of the LCA to suit specific needs for simulating or optimizing processes with environmental criteria. 

            

Raw data

            {
    "_id": null,
    "home_page": "",
    "name": "pyecosim",
    "maintainer": "",
    "docs_url": null,
    "requires_python": ">=3.4",
    "maintainer_email": "",
    "keywords": "LCA,simulation,sustainability",
    "author": "Hedi ROMDHANA",
    "author_email": "hedi.romdhana@agroparistech.fr",
    "download_url": "",
    "platform": null,
    "description": "# PyEcoSim\n`PyEcoSim` performs a comprehensive Life Cycle Assessment (LCA) calculation. By default, it includes pre-installed data, such as life cycle inventories and two environmental impact calculation methods. It offers flexibility to add other calculation methods and inventories, enabling complete customization of the LCA to suit specific needs for simulating or optimizing processes with environmental criteria. \n",
    "bugtrack_url": null,
    "license": "GPLv3",
    "summary": "Python-based Eco-friendly Simulation and Lifecycle Assessment Model",
    "version": "0.0.0",
    "project_urls": null,
    "split_keywords": [
        "lca",
        "simulation",
        "sustainability"
    ],
    "urls": [
        {
            "comment_text": "",
            "digests": {
                "blake2b_256": "16ea91be0a46e622eb61a85106797b2184c9cb5937c43eeb3f7ddd1d41726e3c",
                "md5": "a4bebcd393d584bf533a008f3c9736e4",
                "sha256": "85e36d3fb2ff0a75dc8d529bbfd8413c7c269e6b8e9a7612ec889cf7a1336920"
            },
            "downloads": -1,
            "filename": "pyecosim-0.0.0-py3-none-any.whl",
            "has_sig": false,
            "md5_digest": "a4bebcd393d584bf533a008f3c9736e4",
            "packagetype": "bdist_wheel",
            "python_version": "py3",
            "requires_python": ">=3.4",
            "size": 5667,
            "upload_time": "2023-08-06T19:12:31",
            "upload_time_iso_8601": "2023-08-06T19:12:31.103722Z",
            "url": "https://files.pythonhosted.org/packages/16/ea/91be0a46e622eb61a85106797b2184c9cb5937c43eeb3f7ddd1d41726e3c/pyecosim-0.0.0-py3-none-any.whl",
            "yanked": false,
            "yanked_reason": null
        }
    ],
    "upload_time": "2023-08-06 19:12:31",
    "github": false,
    "gitlab": false,
    "bitbucket": false,
    "codeberg": false,
    "lcname": "pyecosim"
}
        
Elapsed time: 0.51468s