bentso 0.4

Copyright (c) 2019, Chris Mutel All rights reserved.

Redistribution and use in source and binary forms, with or without modification, are permitted provided that the following conditions are met:

• Redistributions of source code must retain the above copyright notice, this list of conditions and the following disclaimer.

• Redistributions in binary form must reproduce the above copyright notice, this list of conditions and the following disclaimer in the documentation and/or other materials provided with the distribution.

• Neither the name of the copyright holder nor the names of its contributors may be used to endorse or promote products derived from this software without specific prior written permission.

THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS “AS IS” AND ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE ARE DISCLAIMED. IN NO EVENT SHALL THE COPYRIGHT HOLDER OR CONTRIBUTORS BE LIABLE FOR ANY DIRECT, INDIRECT, INCIDENTAL, SPECIAL, EXEMPLARY, OR CONSEQUENTIAL DAMAGES (INCLUDING, BUT NOT LIMITED TO, PROCUREMENT OF SUBSTITUTE GOODS OR SERVICES; LOSS OF USE, DATA, OR PROFITS; OR BUSINESS INTERRUPTION) HOWEVER CAUSED AND ON ANY THEORY OF LIABILITY, WHETHER IN CONTRACT, STRICT LIABILITY, OR TORT (INCLUDING NEGLIGENCE OR OTHERWISE) ARISING IN ANY WAY OUT OF THE USE OF THIS SOFTWARE, EVEN IF ADVISED OF THE POSSIBILITY OF SUCH DAMAGE.

Description: # bentso

A library to process ENTSO-E electricity data for use in industrial ecology and life cycle assessment. Developed as part of the [BONSAI](https://bonsai.uno/) network.

[](https://travis-ci.org/BONSAMURAIS/bentso) [](https://ci.appveyor.com/project/cmutel/bentso) [](https://coveralls.io/github/BONSAMURAIS/bentso?branch=master) [](https://bentso.readthedocs.io/en/latest/?badge=latest)

See the [documentation](https://bentso.readthedocs.io/en/latest/) for more.

## Example living life cycle inventory model

Living life cycle inventory models can:

• Automatically update themselves

• Provide results on multiple spatial scales

• Provide results on multiple time scales

This particular model is quite simple - we will gather the necessary data from the [ENTSO-E API](https://github.com/BONSAMURAIS/hackathon-2019), and return it in the specified RDF format. The model should support the following capabilities:

• Be able to specify what kind of input parameters it accepts

• Validate inputs and return sensible error messages

• Cache data to avoid unncessary ENTSO-E API calls

• Function both as a command-line utility and a normal Python library

Inputs can be a list of countries (default is all countries in ENTSO-E), and a time period (default is a given year - maybe 2018?).

This model should also follow the [BONSAI Python library skeleton](https://github.com/BONSAMURAIS/python-skeleton).

Platform: UNKNOWN Classifier: Intended Audience :: End Users/Desktop Classifier: Intended Audience :: Developers Classifier: Intended Audience :: Science/Research Classifier: License :: OSI Approved :: BSD License Classifier: Operating System :: MacOS :: MacOS X Classifier: Operating System :: Microsoft :: Windows Classifier: Operating System :: POSIX Classifier: Programming Language :: Python Classifier: Programming Language :: Python :: 3 Classifier: Programming Language :: Python :: 3.5 Classifier: Programming Language :: Python :: 3.6 Classifier: Programming Language :: Python :: 3.7 Classifier: Topic :: Scientific/Engineering :: Information Analysis Classifier: Topic :: Scientific/Engineering :: Mathematics Classifier: Topic :: Scientific/Engineering :: Visualization