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[Renewables.ninja](https://www.renewables.ninja/) uses `GSEE`.\n\nThe development of `GSEE` predates the existence of [`pvlib-python`](https://pvlib-python.readthedocs.io/) but builds on its functionality as of v0.4.0. Use `GSEE` if you want fast simulations with sensible defaults and solar energy technologies other than PV, and `pvlib-python` if you need control over the nuts and bolts of simulating PV systems.\n\n## Installation\n\n`GSEE` requires Python 3. The recommended way to install is through the [Anaconda Python distribution](https://www.continuum.io/downloads) and `conda-forge`:\n\n    conda install -c conda-forge gsee\n\nYou can also install with `pip install gsee`, but if you do so, and do not already have `numpy` installed, you will get a compiler error when pip tries to build to `climatedata_interface` Cython extension.\n\n## Documentation\n\nSee the [documentation](https://gsee.readthedocs.io/) for more information on `GSEE`'s functionality and for examples.\n\n## Credits and contact\n\nContact [Stefan Pfenninger](mailto:stefan.pfenninger@usys.ethz.ch) for questions about `GSEE`. `GSEE` is also a component of the [Renewables.ninja](https://www.renewables.ninja) project, developed by Stefan Pfenninger and Iain Staffell. Use the [contact page](https://www.renewables.ninja/about) there if you want more information about Renewables.ninja.\n\n## Citation\n\nIf you use `GSEE` or code derived from it in academic work, please cite:\n\nStefan Pfenninger and Iain Staffell (2016). Long-term patterns of European PV output using 30 years of validated hourly reanalysis and satellite data. *Energy* 114, pp. 1251-1265. 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