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human-readable files. Model data is handled in the efficient protobuf format.\u003cbr\u003e\n[FAME](https://gitlab.com/fame-framework/wiki/-/wikis/home) is the open **F**ramework for distributed **A**gent-based **M**odels of **E**nergy systems.\nCheck out the full [FAME-Io documentation](https://fame-framework.gitlab.io/fame-io).\n\n## What is FAME-Io?\n\nFAME-Io is the input-output toolkit for FAME-based simulation models.\nThe relationship to other components can be seen below.\n\n\u003cimg src=\"https://gitlab.com/fame-framework/wiki/-/wikis/architecture/diagrams/Workflow.png\" alt=\"FAME component workflow\" width=\"75%\"\u003e\n\nFAME-Io combines model data and user's agent configurations to create a simulation input file for computations with FAME-Core.\nOnce these computations have finished, FAME-Io converts the simulation output file and returns its contents in a readable format.\n\nThus, with FAME-Io you can:\n\n* Compile input binaries for simulation models built with FAME,\n* Extract output binaries to human-readable formats like CSV and JSON,\n* Edit large CSV files to enhance compilation speed.\n\n## Who is FAME-Io for?\n\nFAME-Io is a vital file-conversion component for FAME-based workflows. If your model is not built with [FAME](https://gitlab.com/fame-framework/wiki/-/wikis/home), you will probably not profit from FAME-Io.\n\n## Applications\n\nFAME-Io is used with any model that is based on FAME.\nAn example of its application is the electricity market model [AMIRIS](https://helmholtz.software/software/amiris).\n\n## Installation\n\nFAME-Io requires Python 3.10 or higher.\nWe recommend installing `fameio` using PyPI: `pip install fameio`\n\n## Usage\n\nFAME-Io offers three command-line scripts:\n\n* [compile](https://fame-framework.gitlab.io/fame-io/usage/compile.html): compiles a protobuf file for FAME applications using YAML definition files and CSV files,\n* [extract](https://fame-framework.gitlab.io/fame-io/usage/extract.html): takes an output file in protobuf format of FAME-based applications and converts it into files in CSV / JSON format,\n* [transform](https://fame-framework.gitlab.io/fame-io/usage/transform.html): takes CSV time series files and reformats them into FAME time format to speed up the first command.\n\n## Community\n\nFAME-Io is mainly developed by the German Aerospace Center, Institute of Networked Energy Systems.\nWe provide support via the dedicated email address [fame@dlr.de](mailto:fame@dlr.de).\n\n**We welcome all contributions**: bug reports, feature requests, documentation enhancements, and code.\u003cbr\u003e\nFor substantial enhancements, we recommend that you contact us via [fame@dlr.de](mailto:fame@dlr.de) for working together on the code in common projects or towards common publications and thus further develop FAME-Io.\n\u003cbr\u003ePlease see our [Contribution Guidelines](https://fame-framework.gitlab.io/fame-io/contribute/contribute.html) and [Code of Conduct](https://fame-framework.gitlab.io/fame-io/contribute/conduct.html).\n\n## Citing FAME-Io\n\nIf you use FAME-Io in academic work, please cite: [DOI 10.21105/joss.04958](https://doi.org/10.21105/joss.04958)\n\n```\n@article{fameio2023joss,\n  author  = {Felix Nitsch and Christoph Schimeczek and Ulrich Frey and Benjamin Fuchs},\n  title   = {FAME-Io: Configuration tools for complex agent-based simulations},\n  journal = {Journal of Open Source Software},\n  year    = {2023},\n  doi     = {doi: https://doi.org/10.21105/joss.04958}\n}\n```\n\nIn other contexts, please include a link to our [Gitlab repository](https://gitlab.com/fame-framework/fame-io).\n\n## Acknowledgements\n\nThe development of FAME-Io was funded by the German Aerospace Center (DLR).\nWe express our gratitude to all [contributors](CONTRIBUTING.md#list-of-contributors).\n","funding_links":[],"readme_doi_urls":["https://doi.org/10.21105/joss.04958"],"works":{},"citation_counts":{},"total_citations":0,"keywords_from_contributors":["agent-based-modeling","electricity market modelling","energy transition"],"project_url":"https://ost.ecosyste.ms/api/v1/projects/328777","html_url":"https://ost.ecosyste.ms/projects/328777"}