{ "info": { "author": "Michael Srocka (Greendelta), Wesley Ingwersen (US Environmental Protection Agency)", "author_email": "ingwersen.wesley@epa.gov", "bugtrack_url": null, "classifiers": [ "Development Status :: 5 - Production/Stable", "Environment :: Console", "Intended Audience :: Science/Research", "License :: CC0 1.0 Universal (CC0 1.0) Public Domain Dedication", "Programming Language :: Python :: 3.5", "Topic :: Utilities" ], "description": "iomb - Input-Output Model Builder\n=================================\n\n``iomb`` is an open source Python library for creating environmentally\nextended input-output models (EEIO models) from CSV files in a simple\n`data format `__. It includes functions to calculate\ndifferent result types (e.g. life cycle assessment results, direct and\nupstream contributions, etc.) from such models and convert them into\n`JSON-LD data packages `__\nthat can be imported into `openLCA `__.\n\nInstallation\n------------\n\n``iomb`` is tested with `Python 3.5 `__ but\nshould also work with older versions of Python 3. The easiest way to\ninstall the package is to do so using pip, which is generally\npackaged with a Python installation. Open up the command line and enter:\n\n::\n\n pip install IO-Model-Builder\n\nThis will also install the dependencies of the IO-Model-Builder\n(`NumPy `__,\n`pandas `__, and\n`matplotlib `__) if required. After this you\nshould be able to use the ``iomb`` package in your Python code. To\nuninstall the package, you can again use pip from the command line:\n\n::\n\n pip uninstall IO-Model-Builder\n\nUsage\n-----\n\nYou can find a more detailed `example here `__ in\nform of a `Jupyter notebook `__ which is a\nconvenient way to use ``iomb``. The following script shows the basic\nusage of ``iomb``. For detailed information about the data format see\nthe `data format specification `__\n\n.. code:: python\n\n import iomb\n\n # optionally show all logging information of iomb\n iomb.log_all()\n\n # create a direct requirements coefficients matrix from a supply and use table\n # and save it to a CSV file\n drc = iomb.coefficients_from_sut('supply_table.csv', 'use_table.csv')\n drc.to_csv('drc.csv')\n\n # create an EEIO model from a coefficients matrix, satellite tables, and a\n # LCIA method\n model = iomb.make_model('drc.csv',\n ['satellite_table1.csv', 'satellite_table2.csv'],\n \"sector_meta_data.csv\",\n ['LCIA_factors1.csv', 'LCIA_factors1.csv'])\n\n # validate the model\n import iomb.validation as val\n vr = validation.validate(model)\n print(vr)\n\n # calculate results for a given demand\n result = iomb.calculate(model, {'1111a0/oilseed farming/us': 1})\n print(result.total_result)\n\n # export the model to a JSON-LD package\n import iomb.olca as olca\n olca.Export(model).to('model_as_json-ld.zip')\n\nLicense\n-------\n\nThis project is in the worldwide public domain, released under the `CC0\n1.0 Universal Public Domain\nDedication `__.\n\n.. figure:: https://licensebuttons.net/p/zero/1.0/88x31.png\n :alt: Public Domain Dedication\n\n Public Domain Dedication\n\nCitation\n--------\n\nPlease cite as: Srocka, M. and W. Ingwersen (2017). IO Model Builder,\nv1.1 (or current version). US Environmental Protection Agency.\nhttps://www.github.com/usepa/io-model-builder\n\nA brief description of the iomb is also included in: Yang, Y.,\nIngwersen, W.W., Hawkins, T.R., Srocka, M., Meyer, D.E., 2017. USEEIO: A\nNew and Transparent United States Environmentally-Extended Input-Output\nModel. Journal of Cleaner Production 158, 308-318. DOI:\n`10.1016/j.jclepro.2017.04.150 `__\n\n\n", "description_content_type": "", "docs_url": null, "download_url": "", "downloads": { "last_day": -1, "last_month": -1, "last_week": -1 }, "home_page": "https://github.com/USEPA/IO-Model-Builder", "keywords": "economic input-output models,supply and use framework,EEIO,life cycle assessment,LCA,USEEIO", "license": "CC0 1.0 Universal (CC0 1.0) Public Domain Dedication", "maintainer": "", "maintainer_email": "", "name": "IO-Model-Builder", "package_url": "https://pypi.org/project/IO-Model-Builder/", "platform": "", "project_url": "https://pypi.org/project/IO-Model-Builder/", "project_urls": { "Homepage": "https://github.com/USEPA/IO-Model-Builder" }, "release_url": "https://pypi.org/project/IO-Model-Builder/1.1.2/", "requires_dist": [ "numpy", "pandas (>=0.17)", "matplotlib", "flask" ], "requires_python": ">=3", "summary": "iomb is a package for creating environmentally extended input-output models", "version": "1.1.2" }, "last_serial": 3874539, "releases": { "1.1.2": [ { "comment_text": "", "digests": { "md5": "50a41107f66fd6cced1cb8e19e1057ff", "sha256": "0b84821b99bdf0537c663bc41661ace9b1afa620d4bc6ee3b9b39ef003209ee2" }, "downloads": -1, "filename": "IO_Model_Builder-1.1.2-py3-none-any.whl", "has_sig": false, "md5_digest": "50a41107f66fd6cced1cb8e19e1057ff", "packagetype": "bdist_wheel", "python_version": "py3", "requires_python": ">=3", "size": 52130, "upload_time": "2018-05-18T03:16:11", "url": "https://files.pythonhosted.org/packages/d1/ec/32e65910e5bb4a59d9a966dd9aeedf1a515ce5c35e81984ba771f7775016/IO_Model_Builder-1.1.2-py3-none-any.whl" } ] }, "urls": [ { "comment_text": "", "digests": { "md5": "50a41107f66fd6cced1cb8e19e1057ff", "sha256": "0b84821b99bdf0537c663bc41661ace9b1afa620d4bc6ee3b9b39ef003209ee2" }, "downloads": -1, "filename": "IO_Model_Builder-1.1.2-py3-none-any.whl", "has_sig": false, "md5_digest": "50a41107f66fd6cced1cb8e19e1057ff", "packagetype": "bdist_wheel", "python_version": "py3", "requires_python": ">=3", "size": 52130, "upload_time": "2018-05-18T03:16:11", "url": "https://files.pythonhosted.org/packages/d1/ec/32e65910e5bb4a59d9a966dd9aeedf1a515ce5c35e81984ba771f7775016/IO_Model_Builder-1.1.2-py3-none-any.whl" } ] }