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version](https://img.shields.io/conda/vn/conda-forge/calliope.svg?label=conda)](https://anaconda.org/conda-forge/calliope)\n[![JOSS DOI](https://img.shields.io/badge/JOSS-10.21105/joss.00825-green.svg)](https://doi.org/10.21105/joss.00825)\n\n---\n\n\u003cimg src=\"https://raw.githubusercontent.com/calliope-project/calliope/main/docs/img/logo.png\" width=\"364\"\u003e\n\n*A multi-scale energy systems modelling framework* | [www.callio.pe](http://www.callio.pe/)\n\n---\n\n## Contents\n\n- [Contents](#contents)\n- [About](#about)\n- [Quick start](#quick-start)\n- [Documentation](#documentation)\n- [Contributing](#contributing)\n- [What's new](#whats-new)\n- [Citing Calliope](#citing-calliope)\n- [License](#license)\n\n---\n\n## About\n\nCalliope is a framework to develop energy system models, with a focus on flexibility, high spatial and temporal resolution, the ability to execute many runs based on the same base model, and a clear separation of framework (code) and model (data). Its primary focus is on planning energy systems at scales ranging from urban districts to entire continents. In an optional operational it can also test a pre-defined system under different operational conditions.\n\nA Calliope model consists of a collection of text files (in YAML and CSV formats) that fully define a model, with details on technologies, locations, resource potentials, etc. Calliope takes these files, constructs an optimization problem, solves it, and reports back results. Results can be saved to CSV or NetCDF files for further processing, or analysed directly in Python through Python's extensive scientific data processing capabilities provided by libraries like [Pandas](http://pandas.pydata.org/) and [xarray](https://docs.xarray.dev/en/stable/).\n\nCalliope comes with several built-in analysis and visualisation tools. 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