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Intensity and Accounting","monthly_downloads":127,"total_dependent_repos":0,"total_dependent_packages":0,"readme":"[![DOI](https://joss.theoj.org/papers/10.21105/joss.08251/status.svg)](https://doi.org/10.21105/joss.08251)\n\n![CATS logo](docs/source/_static/cats_dalle_img_200x200px_for_logo.png)\n\n# CATS: **C**limate-**A**ware **T**ask **S**cheduler\n\nCATS is a **C**limate-**A**ware **T**ask **S**cheduler. It schedules cluster jobs to minimize predicted carbon intensity of running the process. It was created as part of the [2023 Collaborations Workshop](https://software.ac.uk/cw23).\n\nThe Climate-Aware Task Scheduler is a lightweight Python package designed to schedule tasks based on the estimated carbon intensity of the electricity grid at any given moment. This tool uses real-time carbon intensity data from the National Grid ESO via their API to estimate the carbon intensity of the electricity grid, and schedules tasks at times when the estimated carbon intensity is lowest. This helps to reduce the carbon emissions associated with running computationally intensive tasks, making it an ideal solution for environmentally conscious developers.\n\n*Demo showing CATS scheduling a 30 minute job using the `at` scheduler*\n![CATS animated usage example](docs/source/_static/cats.gif)\n\n\u003e [!NOTE]\n\u003e Currently CATS only works in the UK. If you are aware of APIs for realtime grid carbon intensity data in other countries please open an issue and let us know.\n\n\n## Features\n\n- Estimates the carbon intensity of the electricity grid in real-time\n- Schedules tasks based on the estimated carbon intensity, minimizing carbon emissions\n- Provides a simple and intuitive API for developers\n- Lightweight and easy to integrate into existing workflows\n- Supports Python 3.9+\n\n## Brief example with plot to illustrate\n\nTo find the minimal carbon intensity window for a 3 hour (`180` minute duration) job running\nat the `RG1` postcode and show visually the carbon intensity curve and optimal window with\nthe `--plot` argument:\n\n```console\n$ cats --duration 180 --location \"RG1\" --plot\n...\n\nThe.____ ..... __ .... ________ . ______...\n.. /  __)...../  \\....(__    __).)  ____)....\n..|  /......./    \\......|  |...(  (___........\n..| |limate./  ()  \\ware.|  |ask.\\___  \\cheduler\n..|  \\__...|   __   |....|  |....____)  )....\n...\\    )..|  (..)  |....|  |...(      (..\n\n\nBest job start time                       = 2026-01-22 10:10:31\nCarbon intensity if job started now       = 217.41 gCO2eq/kWh\nCarbon intensity at optimal time          = 118.65 gCO2eq/kWh\n```\n\nwhich produced at the time run (`Tue 20 Jan 15:40:21 GMT 2026`) a forecast minimum of\n`118.65 gCO2eq/kWh` for job start time `2026-01-22 10:10:31` as reported in the STDOUT above and\nillustrated by the resulting plot of:\n\n![CATS command run plot example output for RG1 and 3 hour job](docs/source/_static/example_plot_output_rg1_180mins.png)\n\n## Installation\n\nInstall via `pip` as follows:\n\n```bash\npip install climate-aware-task-scheduler\n```\n\nTo install the development version:\n\n```bash\npip install git+https://github.com/GreenScheduler/cats\n```\n\n## Documentation\n\nDocumentation is available at https://cats.readthedocs.io\n\nWe recommend the\n[quickstart](https://greenscheduler.github.io/cats/quickstart.html#basic-usage)\nif you are new to CATS. CATS can optionally [display carbon footprint\nsavings](https://greenscheduler.github.io/cats/quickstart.html#displaying-carbon-footprint-estimates)\nusing a [configuration file](cats/config.yml).\n\n## Contributing\n\nWe welcome contributions from the community! If you find a bug or have an idea for a new feature, please open an issue on our GitHub repository or submit a pull request.\n\n## License\n\n[MIT License](https://github.com/GreenScheduler/cats/blob/main/LICENSE)\n","funding_links":[],"readme_doi_urls":["https://doi.org/10.21105/joss.08251"],"works":{},"citation_counts":{},"total_citations":0,"keywords_from_contributors":["earth-system-model"],"project_url":"https://ost.ecosyste.ms/api/v1/projects/3037","html_url":"https://ost.ecosyste.ms/projects/3037"}