CATS: the Climate-Aware Task Scheduler
A lightweight Python-based tool that calculates the optimal time to run a compute job to minimise its carbon intensity enabling environmentally-conscious scheduling.
https://github.com/GreenScheduler/cats
Category: Emissions
Sub Category: Carbon Intensity and Accounting
Keywords
carbon carbon-footprint climate computing electricity electricity-consumption energy energy-consumption job-scheduler scheduling
Keywords from Contributors
earth-system-model
Last synced: about 13 hours ago
JSON representation
Repository metadata
CATS: the Climate-Aware Task Scheduler 🐈 🐈⬛
- Host: GitHub
- URL: https://github.com/GreenScheduler/cats
- Owner: GreenScheduler
- License: mit
- Created: 2023-05-04T09:16:56.000Z (about 2 years ago)
- Default Branch: main
- Last Pushed: 2025-06-17T16:10:55.000Z (11 days ago)
- Last Synced: 2025-06-24T01:01:46.538Z (5 days ago)
- Topics: carbon, carbon-footprint, climate, computing, electricity, electricity-consumption, energy, energy-consumption, job-scheduler, scheduling
- Language: Python
- Homepage: https://greenscheduler.github.io/cats/
- Size: 8.83 MB
- Stars: 67
- Watchers: 6
- Forks: 9
- Open Issues: 35
- Releases: 3
-
Metadata Files:
- Readme: README.md
- License: LICENSE
- Code of conduct: CODE_OF_CONDUCT.md
README.md
CATS: Climate-Aware Task Scheduler
CATS is a Climate-Aware Task Scheduler. It schedules cluster jobs to minimize predicted carbon intensity of running the process. It was created as part of the 2023 Collaborations Workshop.
The 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.
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.
Features
- Estimates the carbon intensity of the electricity grid in real-time
- Schedules tasks based on the estimated carbon intensity, minimizing carbon emissions
- Provides a simple and intuitive API for developers
- Lightweight and easy to integrate into existing workflows
- Supports Python 3.9+
Installation
Install via pip as follows:
pip install climate-aware-task-scheduler
To install the development version:
pip install git+https://github.com/GreenScheduler/cats
Documentation
Documentation is available at greenscheduler.github.io/cats/.
We recommend the
quickstart
if you are new to CATS. CATS can optionally display carbon footprint
savings
using a configuration file.
Console demonstration
CATS predicting optimal start time for the ls command in the OX1 postcode:
Contributing
We 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.
License
Owner metadata
- Name: GreenScheduler
- Login: GreenScheduler
- Email:
- Kind: organization
- Description:
- Website:
- Location:
- Twitter:
- Company:
- Icon url: https://avatars.githubusercontent.com/u/132558689?v=4
- Repositories: 1
- Last ynced at: 2023-05-04T10:58:20.440Z
- Profile URL: https://github.com/GreenScheduler
GitHub Events
Total
- Create event: 8
- Release event: 1
- Issues event: 21
- Watch event: 18
- Delete event: 20
- Issue comment event: 51
- Push event: 52
- Pull request review comment event: 16
- Pull request review event: 23
- Pull request event: 26
- Fork event: 1
Last Year
- Create event: 8
- Release event: 1
- Issues event: 21
- Watch event: 18
- Delete event: 20
- Issue comment event: 51
- Push event: 52
- Pull request review comment event: 16
- Pull request review event: 23
- Pull request event: 26
- Fork event: 1
Committers metadata
Last synced: 6 days ago
Total Commits: 376
Total Committers: 12
Avg Commits per committer: 31.333
Development Distribution Score (DDS): 0.713
Commits in past year: 51
Committers in past year: 5
Avg Commits per committer in past year: 10.2
Development Distribution Score (DDS) in past year: 0.569
| Name | Commits | |
|---|---|---|
| Thibault Lestang | t****g@i****k | 108 |
| Abhishek Dasgupta | a****a@d****k | 73 |
| Sadie L. Bartholomew | s****w@n****k | 57 |
| Loïc Lannelongue | l****e@p****t | 44 |
| Andrew Walker | a****r@e****k | 28 |
| Colin Sauze | c****e@n****k | 26 |
| Adam Ward | a****a@n****k | 17 |
| Lincoln Colling | l****n@c****z | 13 |
| Tony Greenberg | i****o@b****g | 6 |
| Carlos Martinez | c****z@e****l | 2 |
| Nicolas Payette | n****e@g****m | 1 |
| Andy Turner | a****r@e****k | 1 |
Committer domains:
- noc.ac.uk: 2
- epcc.ed.ac.uk: 1
- esciencecenter.nl: 1
- bayesicresearch.org: 1
- colling.net.nz: 1
- earth.ox.ac.uk: 1
- posteo.net: 1
- ncas.ac.uk: 1
- dtc.ox.ac.uk: 1
- imperial.ac.uk: 1
Issue and Pull Request metadata
Last synced: 1 day ago
Total issues: 81
Total pull requests: 72
Average time to close issues: 3 months
Average time to close pull requests: 19 days
Total issue authors: 11
Total pull request authors: 10
Average comments per issue: 1.56
Average comments per pull request: 2.15
Merged pull request: 64
Bot issues: 0
Bot pull requests: 0
Past year issues: 28
Past year pull requests: 25
Past year average time to close issues: 5 months
Past year average time to close pull requests: about 1 month
Past year issue authors: 9
Past year pull request authors: 6
Past year average comments per issue: 0.89
Past year average comments per pull request: 2.24
Past year merged pull request: 21
Past year bot issues: 0
Past year bot pull requests: 0
Top Issue Authors
- abhidg (18)
- andreww (17)
- sadielbartholomew (15)
- colinsauze (10)
- mkbane (6)
- Llannelongue (6)
- tlestang (3)
- LiamPattinson (3)
- elichad (1)
- ip2location (1)
- thomasferte (1)
Top Pull Request Authors
- andreww (20)
- abhidg (19)
- tlestang (16)
- Llannelongue (5)
- sadielbartholomew (5)
- colinsauze (3)
- c-martinez (1)
- aturner-epcc (1)
- ljcolling (1)
- nicolaspayette (1)
Top Issue Labels
- enhancement (18)
- catsV2 (7)
- documentation (5)
- bug (4)
- carbonIntensityAPI (3)
- carbonFootprint (3)
- question (3)
- refactoring (3)
- JOSS requirement (2)
- testing (2)
- wrapper (1)
- timeOptimiser (1)
Top Pull Request Labels
- documentation (2)
Package metadata
- Total packages: 1
-
Total downloads:
- pypi: 85 last-month
- Total dependent packages: 0
- Total dependent repositories: 0
- Total versions: 3
- Total maintainers: 1
pypi.org: climate-aware-task-scheduler
Climate aware task scheduler
- Homepage: https://github.com/GreenScheduler/cats
- Documentation: https://climate-aware-task-scheduler.readthedocs.io/
- Licenses: MIT License Copyright (c) 2023 GreenScheduler Permission is hereby granted, free of charge, to any person obtaining a copy of this software and associated documentation files (the "Software"), to deal in the Software without restriction, including without limitation the rights to use, copy, modify, merge, publish, distribute, sublicense, and/or sell copies of the Software, and to permit persons to whom the Software is furnished to do so, subject to the following conditions: The above copyright notice and this permission notice shall be included in all copies or substantial portions of the Software. THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY, FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM, OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE SOFTWARE.
- Latest release: 1.1.0 (published 2 days ago)
- Last Synced: 2025-06-27T02:31:11.570Z (1 day ago)
- Versions: 3
- Dependent Packages: 0
- Dependent Repositories: 0
- Downloads: 85 Last month
-
Rankings:
- Dependent packages count: 10.607%
- Average: 35.17%
- Dependent repos count: 59.732%
- Maintainers (1)
Dependencies
- actions/checkout v3 composite
- actions/setup-python v4 composite
- PyYAML >=6.0
- requests-cache >=1.0
Score: 11.564226759325779