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| author | CoprDistGit <infra@openeuler.org> | 2023-05-05 06:51:52 +0000 |
|---|---|---|
| committer | CoprDistGit <infra@openeuler.org> | 2023-05-05 06:51:52 +0000 |
| commit | bfcb0077c900cc0d827cbb0d9473304b5b3ea21a (patch) | |
| tree | de1ef2d0a424a48f88cb63c3333d791c94b07cbb | |
| parent | 73e9ec8e924f103b286a45fbd2c51d6b66993dcc (diff) | |
automatic import of python-pypsaopeneuler20.03
| -rw-r--r-- | .gitignore | 1 | ||||
| -rw-r--r-- | python-pypsa.spec | 789 | ||||
| -rw-r--r-- | sources | 1 |
3 files changed, 791 insertions, 0 deletions
@@ -0,0 +1 @@ +/pypsa-0.22.1.tar.gz diff --git a/python-pypsa.spec b/python-pypsa.spec new file mode 100644 index 0000000..35a95c1 --- /dev/null +++ b/python-pypsa.spec @@ -0,0 +1,789 @@ +%global _empty_manifest_terminate_build 0 +Name: python-pypsa +Version: 0.22.1 +Release: 1 +Summary: Python for Power Systems Analysis +License: MIT +URL: https://github.com/PyPSA/PyPSA +Source0: https://mirrors.nju.edu.cn/pypi/web/packages/c0/e1/c9fa94dd53fa279d4a66e5ee4447ac4dea93fcd3a882be73de50583bb584/pypsa-0.22.1.tar.gz +BuildArch: noarch + + +%description +# PyPSA - Python for Power System Analysis + + +[](https://pypi.python.org/pypi/pypsa) +[](https://anaconda.org/conda-forge/pypsa) +[](https://github.com/pypsa/pypsa/actions/workflows/CI.yml) +[](https://github.com/pypsa/pypsa/actions/workflows/CI-conda.yml) +[](https://codecov.io/gh/PyPSA/PyPSA) +[](https://pypsa.readthedocs.io/en/latest/?badge=latest) +[](LICENSE.txt) +[](https://doi.org/10.5281/zenodo.3946412) +[](https://mybinder.org/v2/gh/PyPSA/PyPSA/master?filepath=examples%2Fnotebooks) +[](https://results.pre-commit.ci/latest/github/PyPSA/PyPSA/master) +[](https://github.com/psf/black) +[](https://discord.gg/AnuJBk23FU) +[](CODE_OF_CONDUCT.md) + +PyPSA stands for "Python for Power System Analysis". It is pronounced +"pipes-ah". + +PyPSA is an open source toolbox for simulating and optimising modern power and +energy systems that include features such as conventional generators with unit +commitment, variable wind and solar generation, storage units, coupling to other +energy sectors, and mixed alternating and direct current networks. PyPSA is +designed to scale well with large networks and long time series. + +This project is maintained by the [Department of Digital Transformation in +Energy Systems](https://tub-ensys.github.io) at the [Technical University of +Berlin](https://www.tu.berlin). Previous versions were developed by the Energy +System Modelling group at the [Institute for Automation and Applied +Informatics](https://www.iai.kit.edu/english/index.php) at the [Karlsruhe +Institute of Technology](http://www.kit.edu/english/index.php) funded by the +[Helmholtz Association](https://www.helmholtz.de/en/), and by the [Renewable +Energy +Group](https://fias.uni-frankfurt.de/physics/schramm/renewable-energy-system-and-network-analysis/) +at [FIAS](https://fias.uni-frankfurt.de/) to carry out simulations for the +[CoNDyNet project](http://condynet.de/), financed by the [German Federal +Ministry for Education and Research (BMBF)](https://www.bmbf.de/en/index.html) +as part of the [Stromnetze Research +Initiative](http://forschung-stromnetze.info/projekte/grundlagen-und-konzepte-fuer-effiziente-dezentrale-stromnetze/). + +## Functionality + +PyPSA can calculate: + +- static power flow (using both the full non-linear network equations and the + linearised network equations) +- linear optimal power flow (least-cost optimisation of power plant and + storage dispatch within network constraints, using the linear network + equations, over several snapshots) +- security-constrained linear optimal power flow +- total electricity/energy system least-cost investment optimisation (using + linear network equations, over several snapshots and investment periods + simultaneously for optimisation of generation and storage dispatch and + investment in the capacities of generation, storage, transmission and other + infrastructure) + +It has models for: + +- meshed multiply-connected AC and DC networks, with controllable converters + between AC and DC networks +- standard types for lines and transformers following the implementation in + [pandapower](https://www.pandapower.org/) +- conventional dispatchable generators with unit commitment +- generators with time-varying power availability, such as wind and solar + generators +- storage units with efficiency losses +- simple hydroelectricity with inflow and spillage +- coupling with other energy carriers (e.g. resistive Power-to-Heat (P2H), + Power-to-Gas (P2G), battery electric vehicles (BEVs), Fischer-Tropsch, + direct air capture (DAC)) +- basic components out of which more complicated assets can be built, such as + Combined Heat and Power (CHP) units and heat pumps. + +## Documentation + +[Documentation](https://pypsa.readthedocs.io/en/latest/index.html) + +[Quick start](https://pypsa.readthedocs.io/en/latest/quick_start.html) + +[Examples](https://pypsa.readthedocs.io/en/latest/examples-basic.html) + +[Known users of +PyPSA](https://pypsa.readthedocs.io/en/latest/users.html) + +## Installation + +pip: + +```pip install pypsa``` + +conda/mamba: + +```conda install -c conda-forge pypsa``` + +Additionally, install a solver. + +## Usage + +```py +import pypsa + +# create a new network +n = pypsa.Network() +n.add("Bus", "mybus") +n.add("Load", "myload", bus="mybus", p_set=100) +n.add("Generator", "mygen", bus="mybus", p_nom=100, marginal_cost=20) + +# load an example network +n = pypsa.examples.ac_dc_meshed() + +# run the optimisation +n.lopf() + +# plot results +n.generators_t.p.plot() +n.plot() +``` + +There are [more extensive +examples](https://pypsa.readthedocs.io/en/latest/examples-basic.html) available +as [Jupyter notebooks](https://jupyter.org/). They are also described in the +[doc/examples.rst](doc/examples.rst) and are available as Python scripts in +[examples/](examples/). + +## Screenshots + +[PyPSA-Eur](https://github.com/PyPSA/pypsa-eur) optimising capacities of +generation, storage and transmission lines (9% line volume expansion allowed) +for a 95% reduction in CO2 emissions in Europe compared to 1990 levels + + + +[SciGRID model](https://power.scigrid.de/) simulating the German power system +for 2015. + + + + + +## Dependencies + +PyPSA is written and tested to be compatible with Python 3.7 and above. +The last release supporting Python 2.7 was PyPSA 0.15.0. + +It leans heavily on the following Python packages: + +- [pandas](http://pandas.pydata.org/) for storing data about + components and time series +- [numpy](http://www.numpy.org/) and [scipy](http://scipy.org/) for + calculations, such as linear algebra and sparse matrix calculations +- [networkx](https://networkx.github.io/) for some network + calculations +- [matplotlib](https://matplotlib.org/) for static plotting +- [pyomo](http://www.pyomo.org/) for preparing optimisation problems + (currently only linear) +- [cartopy](https://scitools.org.uk/cartopy) for plotting the + baselayer map +- [pytest](http://pytest.org/) for unit testing +- [logging](https://docs.python.org/3/library/logging.html) for + managing messages + +The optimisation uses interface libraries like `pyomo` which are +independent of the preferred solver. You can use e.g. one of the free +solvers [GLPK](https://www.gnu.org/software/glpk/) and +[CLP/CBC](https://github.com/coin-or/Cbc/) or the commercial solver +[Gurobi](http://www.gurobi.com/) for which free academic licenses are +available. + +## Documentation + +Please check the [documentation](https://pypsa.readthedocs.io). + +## Contributing and Support + +We strongly welcome anyone interested in contributing to this project. If you have any ideas, suggestions or encounter problems, feel invited to file +issues or make pull requests on GitHub. + +PyPSA has a Google Group [forum / mailing +list](https://groups.google.com/group/pypsa) where announcements of new +releases can be made and questions can be asked. + +To discuss issues and suggest/contribute features for future development +we prefer ticketing through the [PyPSA Github Issues +page](https://github.com/PyPSA/PyPSA/issues). + +A `Discord server <https://discord.gg/AnuJBk23FU>` hosts every tool +in the PyPSA ecosystem. We have there public voice and text channels +that are suitable to organise projects, ask questions, +share news, or chat with the community. + +## Code of Conduct + +Please respect our [code of conduct](CODE_OF_CONDUCT.md). + +## Citing PyPSA + +If you use PyPSA for your research, we would appreciate it if you would +cite the following paper: + +- T. Brown, J. Hörsch, D. Schlachtberger, [PyPSA: Python for Power + System Analysis](https://arxiv.org/abs/1707.09913), 2018, [Journal + of Open Research + Software](https://openresearchsoftware.metajnl.com/), 6(1), + [arXiv:1707.09913](https://arxiv.org/abs/1707.09913), + [DOI:10.5334/jors.188](https://doi.org/10.5334/jors.188) + +Please use the following BibTeX: + + @article{PyPSA, + author = {T. Brown and J. H\"orsch and D. Schlachtberger}, + title = {{PyPSA: Python for Power System Analysis}}, + journal = {Journal of Open Research Software}, + volume = {6}, + issue = {1}, + number = {4}, + year = {2018}, + eprint = {1707.09913}, + url = {https://doi.org/10.5334/jors.188}, + doi = {10.5334/jors.188} + } + +If you want to cite a specific PyPSA version, each release of PyPSA is +stored on [Zenodo](https://zenodo.org/) with a release-specific DOI. The +release-specific DOIs can be found linked from the overall PyPSA Zenodo +DOI for Version 0.17.1 and onwards: + +[](https://doi.org/10.5281/zenodo.3946412) + +or from the overall PyPSA Zenodo DOI for Versions up to 0.17.0: + +[](https://doi.org/10.5281/zenodo.786605) + +# Licence + +Copyright 2015-2023 [PyPSA +Developers](https://pypsa.readthedocs.io/en/latest/developers.html) + +PyPSA is licensed under the open source [MIT +License](https://github.com/PyPSA/PyPSA/blob/master/LICENSE.txt). + +%package -n python3-pypsa +Summary: Python for Power Systems Analysis +Provides: python-pypsa +BuildRequires: python3-devel +BuildRequires: python3-setuptools +BuildRequires: python3-pip +%description -n python3-pypsa +# PyPSA - Python for Power System Analysis + + +[](https://pypi.python.org/pypi/pypsa) +[](https://anaconda.org/conda-forge/pypsa) +[](https://github.com/pypsa/pypsa/actions/workflows/CI.yml) +[](https://github.com/pypsa/pypsa/actions/workflows/CI-conda.yml) +[](https://codecov.io/gh/PyPSA/PyPSA) +[](https://pypsa.readthedocs.io/en/latest/?badge=latest) +[](LICENSE.txt) +[](https://doi.org/10.5281/zenodo.3946412) +[](https://mybinder.org/v2/gh/PyPSA/PyPSA/master?filepath=examples%2Fnotebooks) +[](https://results.pre-commit.ci/latest/github/PyPSA/PyPSA/master) +[](https://github.com/psf/black) +[](https://discord.gg/AnuJBk23FU) +[](CODE_OF_CONDUCT.md) + +PyPSA stands for "Python for Power System Analysis". It is pronounced +"pipes-ah". + +PyPSA is an open source toolbox for simulating and optimising modern power and +energy systems that include features such as conventional generators with unit +commitment, variable wind and solar generation, storage units, coupling to other +energy sectors, and mixed alternating and direct current networks. PyPSA is +designed to scale well with large networks and long time series. + +This project is maintained by the [Department of Digital Transformation in +Energy Systems](https://tub-ensys.github.io) at the [Technical University of +Berlin](https://www.tu.berlin). Previous versions were developed by the Energy +System Modelling group at the [Institute for Automation and Applied +Informatics](https://www.iai.kit.edu/english/index.php) at the [Karlsruhe +Institute of Technology](http://www.kit.edu/english/index.php) funded by the +[Helmholtz Association](https://www.helmholtz.de/en/), and by the [Renewable +Energy +Group](https://fias.uni-frankfurt.de/physics/schramm/renewable-energy-system-and-network-analysis/) +at [FIAS](https://fias.uni-frankfurt.de/) to carry out simulations for the +[CoNDyNet project](http://condynet.de/), financed by the [German Federal +Ministry for Education and Research (BMBF)](https://www.bmbf.de/en/index.html) +as part of the [Stromnetze Research +Initiative](http://forschung-stromnetze.info/projekte/grundlagen-und-konzepte-fuer-effiziente-dezentrale-stromnetze/). + +## Functionality + +PyPSA can calculate: + +- static power flow (using both the full non-linear network equations and the + linearised network equations) +- linear optimal power flow (least-cost optimisation of power plant and + storage dispatch within network constraints, using the linear network + equations, over several snapshots) +- security-constrained linear optimal power flow +- total electricity/energy system least-cost investment optimisation (using + linear network equations, over several snapshots and investment periods + simultaneously for optimisation of generation and storage dispatch and + investment in the capacities of generation, storage, transmission and other + infrastructure) + +It has models for: + +- meshed multiply-connected AC and DC networks, with controllable converters + between AC and DC networks +- standard types for lines and transformers following the implementation in + [pandapower](https://www.pandapower.org/) +- conventional dispatchable generators with unit commitment +- generators with time-varying power availability, such as wind and solar + generators +- storage units with efficiency losses +- simple hydroelectricity with inflow and spillage +- coupling with other energy carriers (e.g. resistive Power-to-Heat (P2H), + Power-to-Gas (P2G), battery electric vehicles (BEVs), Fischer-Tropsch, + direct air capture (DAC)) +- basic components out of which more complicated assets can be built, such as + Combined Heat and Power (CHP) units and heat pumps. + +## Documentation + +[Documentation](https://pypsa.readthedocs.io/en/latest/index.html) + +[Quick start](https://pypsa.readthedocs.io/en/latest/quick_start.html) + +[Examples](https://pypsa.readthedocs.io/en/latest/examples-basic.html) + +[Known users of +PyPSA](https://pypsa.readthedocs.io/en/latest/users.html) + +## Installation + +pip: + +```pip install pypsa``` + +conda/mamba: + +```conda install -c conda-forge pypsa``` + +Additionally, install a solver. + +## Usage + +```py +import pypsa + +# create a new network +n = pypsa.Network() +n.add("Bus", "mybus") +n.add("Load", "myload", bus="mybus", p_set=100) +n.add("Generator", "mygen", bus="mybus", p_nom=100, marginal_cost=20) + +# load an example network +n = pypsa.examples.ac_dc_meshed() + +# run the optimisation +n.lopf() + +# plot results +n.generators_t.p.plot() +n.plot() +``` + +There are [more extensive +examples](https://pypsa.readthedocs.io/en/latest/examples-basic.html) available +as [Jupyter notebooks](https://jupyter.org/). They are also described in the +[doc/examples.rst](doc/examples.rst) and are available as Python scripts in +[examples/](examples/). + +## Screenshots + +[PyPSA-Eur](https://github.com/PyPSA/pypsa-eur) optimising capacities of +generation, storage and transmission lines (9% line volume expansion allowed) +for a 95% reduction in CO2 emissions in Europe compared to 1990 levels + + + +[SciGRID model](https://power.scigrid.de/) simulating the German power system +for 2015. + + + + + +## Dependencies + +PyPSA is written and tested to be compatible with Python 3.7 and above. +The last release supporting Python 2.7 was PyPSA 0.15.0. + +It leans heavily on the following Python packages: + +- [pandas](http://pandas.pydata.org/) for storing data about + components and time series +- [numpy](http://www.numpy.org/) and [scipy](http://scipy.org/) for + calculations, such as linear algebra and sparse matrix calculations +- [networkx](https://networkx.github.io/) for some network + calculations +- [matplotlib](https://matplotlib.org/) for static plotting +- [pyomo](http://www.pyomo.org/) for preparing optimisation problems + (currently only linear) +- [cartopy](https://scitools.org.uk/cartopy) for plotting the + baselayer map +- [pytest](http://pytest.org/) for unit testing +- [logging](https://docs.python.org/3/library/logging.html) for + managing messages + +The optimisation uses interface libraries like `pyomo` which are +independent of the preferred solver. You can use e.g. one of the free +solvers [GLPK](https://www.gnu.org/software/glpk/) and +[CLP/CBC](https://github.com/coin-or/Cbc/) or the commercial solver +[Gurobi](http://www.gurobi.com/) for which free academic licenses are +available. + +## Documentation + +Please check the [documentation](https://pypsa.readthedocs.io). + +## Contributing and Support + +We strongly welcome anyone interested in contributing to this project. If you have any ideas, suggestions or encounter problems, feel invited to file +issues or make pull requests on GitHub. + +PyPSA has a Google Group [forum / mailing +list](https://groups.google.com/group/pypsa) where announcements of new +releases can be made and questions can be asked. + +To discuss issues and suggest/contribute features for future development +we prefer ticketing through the [PyPSA Github Issues +page](https://github.com/PyPSA/PyPSA/issues). + +A `Discord server <https://discord.gg/AnuJBk23FU>` hosts every tool +in the PyPSA ecosystem. We have there public voice and text channels +that are suitable to organise projects, ask questions, +share news, or chat with the community. + +## Code of Conduct + +Please respect our [code of conduct](CODE_OF_CONDUCT.md). + +## Citing PyPSA + +If you use PyPSA for your research, we would appreciate it if you would +cite the following paper: + +- T. Brown, J. Hörsch, D. Schlachtberger, [PyPSA: Python for Power + System Analysis](https://arxiv.org/abs/1707.09913), 2018, [Journal + of Open Research + Software](https://openresearchsoftware.metajnl.com/), 6(1), + [arXiv:1707.09913](https://arxiv.org/abs/1707.09913), + [DOI:10.5334/jors.188](https://doi.org/10.5334/jors.188) + +Please use the following BibTeX: + + @article{PyPSA, + author = {T. Brown and J. H\"orsch and D. Schlachtberger}, + title = {{PyPSA: Python for Power System Analysis}}, + journal = {Journal of Open Research Software}, + volume = {6}, + issue = {1}, + number = {4}, + year = {2018}, + eprint = {1707.09913}, + url = {https://doi.org/10.5334/jors.188}, + doi = {10.5334/jors.188} + } + +If you want to cite a specific PyPSA version, each release of PyPSA is +stored on [Zenodo](https://zenodo.org/) with a release-specific DOI. The +release-specific DOIs can be found linked from the overall PyPSA Zenodo +DOI for Version 0.17.1 and onwards: + +[](https://doi.org/10.5281/zenodo.3946412) + +or from the overall PyPSA Zenodo DOI for Versions up to 0.17.0: + +[](https://doi.org/10.5281/zenodo.786605) + +# Licence + +Copyright 2015-2023 [PyPSA +Developers](https://pypsa.readthedocs.io/en/latest/developers.html) + +PyPSA is licensed under the open source [MIT +License](https://github.com/PyPSA/PyPSA/blob/master/LICENSE.txt). + +%package help +Summary: Development documents and examples for pypsa +Provides: python3-pypsa-doc +%description help +# PyPSA - Python for Power System Analysis + + +[](https://pypi.python.org/pypi/pypsa) +[](https://anaconda.org/conda-forge/pypsa) +[](https://github.com/pypsa/pypsa/actions/workflows/CI.yml) +[](https://github.com/pypsa/pypsa/actions/workflows/CI-conda.yml) +[](https://codecov.io/gh/PyPSA/PyPSA) +[](https://pypsa.readthedocs.io/en/latest/?badge=latest) +[](LICENSE.txt) +[](https://doi.org/10.5281/zenodo.3946412) +[](https://mybinder.org/v2/gh/PyPSA/PyPSA/master?filepath=examples%2Fnotebooks) +[](https://results.pre-commit.ci/latest/github/PyPSA/PyPSA/master) +[](https://github.com/psf/black) +[](https://discord.gg/AnuJBk23FU) +[](CODE_OF_CONDUCT.md) + +PyPSA stands for "Python for Power System Analysis". It is pronounced +"pipes-ah". + +PyPSA is an open source toolbox for simulating and optimising modern power and +energy systems that include features such as conventional generators with unit +commitment, variable wind and solar generation, storage units, coupling to other +energy sectors, and mixed alternating and direct current networks. PyPSA is +designed to scale well with large networks and long time series. + +This project is maintained by the [Department of Digital Transformation in +Energy Systems](https://tub-ensys.github.io) at the [Technical University of +Berlin](https://www.tu.berlin). Previous versions were developed by the Energy +System Modelling group at the [Institute for Automation and Applied +Informatics](https://www.iai.kit.edu/english/index.php) at the [Karlsruhe +Institute of Technology](http://www.kit.edu/english/index.php) funded by the +[Helmholtz Association](https://www.helmholtz.de/en/), and by the [Renewable +Energy +Group](https://fias.uni-frankfurt.de/physics/schramm/renewable-energy-system-and-network-analysis/) +at [FIAS](https://fias.uni-frankfurt.de/) to carry out simulations for the +[CoNDyNet project](http://condynet.de/), financed by the [German Federal +Ministry for Education and Research (BMBF)](https://www.bmbf.de/en/index.html) +as part of the [Stromnetze Research +Initiative](http://forschung-stromnetze.info/projekte/grundlagen-und-konzepte-fuer-effiziente-dezentrale-stromnetze/). + +## Functionality + +PyPSA can calculate: + +- static power flow (using both the full non-linear network equations and the + linearised network equations) +- linear optimal power flow (least-cost optimisation of power plant and + storage dispatch within network constraints, using the linear network + equations, over several snapshots) +- security-constrained linear optimal power flow +- total electricity/energy system least-cost investment optimisation (using + linear network equations, over several snapshots and investment periods + simultaneously for optimisation of generation and storage dispatch and + investment in the capacities of generation, storage, transmission and other + infrastructure) + +It has models for: + +- meshed multiply-connected AC and DC networks, with controllable converters + between AC and DC networks +- standard types for lines and transformers following the implementation in + [pandapower](https://www.pandapower.org/) +- conventional dispatchable generators with unit commitment +- generators with time-varying power availability, such as wind and solar + generators +- storage units with efficiency losses +- simple hydroelectricity with inflow and spillage +- coupling with other energy carriers (e.g. resistive Power-to-Heat (P2H), + Power-to-Gas (P2G), battery electric vehicles (BEVs), Fischer-Tropsch, + direct air capture (DAC)) +- basic components out of which more complicated assets can be built, such as + Combined Heat and Power (CHP) units and heat pumps. + +## Documentation + +[Documentation](https://pypsa.readthedocs.io/en/latest/index.html) + +[Quick start](https://pypsa.readthedocs.io/en/latest/quick_start.html) + +[Examples](https://pypsa.readthedocs.io/en/latest/examples-basic.html) + +[Known users of +PyPSA](https://pypsa.readthedocs.io/en/latest/users.html) + +## Installation + +pip: + +```pip install pypsa``` + +conda/mamba: + +```conda install -c conda-forge pypsa``` + +Additionally, install a solver. + +## Usage + +```py +import pypsa + +# create a new network +n = pypsa.Network() +n.add("Bus", "mybus") +n.add("Load", "myload", bus="mybus", p_set=100) +n.add("Generator", "mygen", bus="mybus", p_nom=100, marginal_cost=20) + +# load an example network +n = pypsa.examples.ac_dc_meshed() + +# run the optimisation +n.lopf() + +# plot results +n.generators_t.p.plot() +n.plot() +``` + +There are [more extensive +examples](https://pypsa.readthedocs.io/en/latest/examples-basic.html) available +as [Jupyter notebooks](https://jupyter.org/). They are also described in the +[doc/examples.rst](doc/examples.rst) and are available as Python scripts in +[examples/](examples/). + +## Screenshots + +[PyPSA-Eur](https://github.com/PyPSA/pypsa-eur) optimising capacities of +generation, storage and transmission lines (9% line volume expansion allowed) +for a 95% reduction in CO2 emissions in Europe compared to 1990 levels + + + +[SciGRID model](https://power.scigrid.de/) simulating the German power system +for 2015. + + + + + +## Dependencies + +PyPSA is written and tested to be compatible with Python 3.7 and above. +The last release supporting Python 2.7 was PyPSA 0.15.0. + +It leans heavily on the following Python packages: + +- [pandas](http://pandas.pydata.org/) for storing data about + components and time series +- [numpy](http://www.numpy.org/) and [scipy](http://scipy.org/) for + calculations, such as linear algebra and sparse matrix calculations +- [networkx](https://networkx.github.io/) for some network + calculations +- [matplotlib](https://matplotlib.org/) for static plotting +- [pyomo](http://www.pyomo.org/) for preparing optimisation problems + (currently only linear) +- [cartopy](https://scitools.org.uk/cartopy) for plotting the + baselayer map +- [pytest](http://pytest.org/) for unit testing +- [logging](https://docs.python.org/3/library/logging.html) for + managing messages + +The optimisation uses interface libraries like `pyomo` which are +independent of the preferred solver. You can use e.g. one of the free +solvers [GLPK](https://www.gnu.org/software/glpk/) and +[CLP/CBC](https://github.com/coin-or/Cbc/) or the commercial solver +[Gurobi](http://www.gurobi.com/) for which free academic licenses are +available. + +## Documentation + +Please check the [documentation](https://pypsa.readthedocs.io). + +## Contributing and Support + +We strongly welcome anyone interested in contributing to this project. If you have any ideas, suggestions or encounter problems, feel invited to file +issues or make pull requests on GitHub. + +PyPSA has a Google Group [forum / mailing +list](https://groups.google.com/group/pypsa) where announcements of new +releases can be made and questions can be asked. + +To discuss issues and suggest/contribute features for future development +we prefer ticketing through the [PyPSA Github Issues +page](https://github.com/PyPSA/PyPSA/issues). + +A `Discord server <https://discord.gg/AnuJBk23FU>` hosts every tool +in the PyPSA ecosystem. We have there public voice and text channels +that are suitable to organise projects, ask questions, +share news, or chat with the community. + +## Code of Conduct + +Please respect our [code of conduct](CODE_OF_CONDUCT.md). + +## Citing PyPSA + +If you use PyPSA for your research, we would appreciate it if you would +cite the following paper: + +- T. Brown, J. Hörsch, D. Schlachtberger, [PyPSA: Python for Power + System Analysis](https://arxiv.org/abs/1707.09913), 2018, [Journal + of Open Research + Software](https://openresearchsoftware.metajnl.com/), 6(1), + [arXiv:1707.09913](https://arxiv.org/abs/1707.09913), + [DOI:10.5334/jors.188](https://doi.org/10.5334/jors.188) + +Please use the following BibTeX: + + @article{PyPSA, + author = {T. Brown and J. H\"orsch and D. Schlachtberger}, + title = {{PyPSA: Python for Power System Analysis}}, + journal = {Journal of Open Research Software}, + volume = {6}, + issue = {1}, + number = {4}, + year = {2018}, + eprint = {1707.09913}, + url = {https://doi.org/10.5334/jors.188}, + doi = {10.5334/jors.188} + } + +If you want to cite a specific PyPSA version, each release of PyPSA is +stored on [Zenodo](https://zenodo.org/) with a release-specific DOI. The +release-specific DOIs can be found linked from the overall PyPSA Zenodo +DOI for Version 0.17.1 and onwards: + +[](https://doi.org/10.5281/zenodo.3946412) + +or from the overall PyPSA Zenodo DOI for Versions up to 0.17.0: + +[](https://doi.org/10.5281/zenodo.786605) + +# Licence + +Copyright 2015-2023 [PyPSA +Developers](https://pypsa.readthedocs.io/en/latest/developers.html) + +PyPSA is licensed under the open source [MIT +License](https://github.com/PyPSA/PyPSA/blob/master/LICENSE.txt). + +%prep +%autosetup -n pypsa-0.22.1 + +%build +%py3_build + +%install +%py3_install +install -d -m755 %{buildroot}/%{_pkgdocdir} +if [ -d doc ]; then cp -arf doc %{buildroot}/%{_pkgdocdir}; fi +if [ -d docs ]; then cp -arf docs %{buildroot}/%{_pkgdocdir}; fi +if [ -d example ]; then cp -arf example %{buildroot}/%{_pkgdocdir}; fi +if [ -d examples ]; then cp -arf examples %{buildroot}/%{_pkgdocdir}; fi +pushd %{buildroot} +if [ -d usr/lib ]; then + find usr/lib -type f -printf "/%h/%f\n" >> filelist.lst +fi +if [ -d usr/lib64 ]; then + find usr/lib64 -type f -printf "/%h/%f\n" >> filelist.lst +fi +if [ -d usr/bin ]; then + find usr/bin -type f -printf "/%h/%f\n" >> filelist.lst +fi +if [ -d usr/sbin ]; then + find usr/sbin -type f -printf "/%h/%f\n" >> filelist.lst +fi +touch doclist.lst +if [ -d usr/share/man ]; then + find usr/share/man -type f -printf "/%h/%f.gz\n" >> doclist.lst +fi +popd +mv %{buildroot}/filelist.lst . +mv %{buildroot}/doclist.lst . + +%files -n python3-pypsa -f filelist.lst +%dir %{python3_sitelib}/* + +%files help -f doclist.lst +%{_docdir}/* + +%changelog +* Fri May 05 2023 Python_Bot <Python_Bot@openeuler.org> - 0.22.1-1 +- Package Spec generated @@ -0,0 +1 @@ +d8dc9c9d84e327d5695309800792fd9e pypsa-0.22.1.tar.gz |