CodeCarbon

Track emissions from Compute and recommend ways to reduce their impact on the environment.
https://github.com/mlco2/codecarbon

Category: Consumption
Sub Category: Computation and Communication

Keywords

ai-ethics carbon-emissions carbon-footprint co2-emissions energy-consumption energy-efficiency fairness sustainability

Keywords from Contributors

language-model climate-change natural-language-processing transformer bert climate-science climate-data electricitymap flax speech-recognition

Last synced: about 1 hour ago
JSON representation

Repository metadata

Track emissions from Compute and recommend ways to reduce their impact on the environment.

README.md

banner

Track & reduce CO₂ emissions from your local computing

Estimate and track carbon emissions from your computer, quantify and analyze their impact.

DOI OpenSSF Scorecard codecov Discord

  • A lightweight, easy to use Python library – Simple API to track emissions
  • Open source, free & community driven – Built by and for the community
  • Effective visual outputs – Put emissions in context with real-world equivalents

Tracking GenAI API calls? CodeCarbon measures emissions from local computing (your hardware). To track emissions from remote GenAI API calls (OpenAI, Anthropic, Mistral, etc.), use EcoLogits. Both tools are complementary.

Join the community! Have questions, want to share your work, or contribute? Join us on Discord – we're here to help and excited to hear from you!

Installation

pip install codecarbon

If you use Conda:

conda activate your_env
pip install codecarbon

More installation options: installation docs.

Quickstart (Python)

from codecarbon import EmissionsTracker

tracker = EmissionsTracker()
tracker.start()

# Your code here

emissions = tracker.stop()
print(f"Emissions: {emissions} kg CO₂")

Learn more

Quickstart (CLI)

Track a command without changing your code:

codecarbon monitor --no-api -- python train.py

Detect your hardware:

codecarbon detect

Full CLI guide: CLI tutorial.

Configuration

You can configure CodeCarbon using:

  • ~/.codecarbon.config (global)
  • ./.codecarbon.config (project-local)
  • CODECARBON_* environment variables
  • Python arguments (EmissionsTracker(...))

Configuration precedence and examples: configuration guide.

How it works

We created a Python package that estimates your hardware electricity power consumption (GPU + CPU + RAM) and we apply to it the carbon intensity of the region where the computing is done.

CodeCarbon focuses on the main compute components it can measure or estimate directly: CPU, GPU, and RAM. It does not separately model disk I/O, network transfers, displays, cooling, or other peripherals because those sources are usually much smaller for local code-level experiments and are not exposed through the same low-overhead measurement interfaces.

calculation Summary

We explain more about this calculation in the Methodology section of the documentation.

Visualize

You can visualize your experiment emissions on the dashboard or locally with carbonboard.

dashboard

Quick links

Section Description
Quickstart Get started in 5 minutes
Installation Install CodeCarbon
CLI Tutorial Track emissions from the command line
Python API Tutorial Track emissions in Python code
Comparing Model Efficiency Measure carbon efficiency across ML models
API Reference Full parameter documentation
Framework examples (scikit-learn) Task-oriented ML framework examples
Methodology How emissions are calculated
EcoLogits Track emissions from GenAI API calls
Discord Community Chat with us and the community

Links

  • Main website to learn why we do this.
  • Dashboard to see your emissions.
  • Documentation to learn how to use the package and our methodology.
  • EcoLogits to track emissions from GenAI API calls (OpenAI, Anthropic, etc.).
  • GitHub to look at the source code and contribute.
  • Discord to chat with us.

Contributing

We are hoping that the open-source community will help us edit the code and make it better!

You are welcome to open issues, even suggest solutions and better still contribute the fix/improvement! We can guide you if you're not sure where to start but want to help us out.

Check out our contribution guidelines.

Feel free to chat with us on Discord.

Citation

If you find CodeCarbon useful for your research, you can find a citation under a variety of formats on Zenodo.

@software{benoit_courty_2024_11171501,
  author       = {Benoit Courty and
                  Victor Schmidt and
                  Sasha Luccioni and
                  Goyal-Kamal and
                  MarionCoutarel and
                  Boris Feld and
                  Jérémy Lecourt and
                  LiamConnell and
                  Amine Saboni and
                  Inimaz and
                  supatomic and
                  Mathilde Léval and
                  Luis Blanche and
                  Alexis Cruveiller and
                  ouminasara and
                  Franklin Zhao and
                  Aditya Joshi and
                  Alexis Bogroff and
                  Hugues de Lavoreille and
                  Niko Laskaris and
                  Edoardo Abati and
                  Douglas Blank and
                  Ziyao Wang and
                  Armin Catovic and
                  Marc Alencon and
                  Michał Stęchły and
                  Christian Bauer and
                  Lucas Otávio N. de Araújo and
                  JPW and
                  MinervaBooks},
  title        = {mlco2/codecarbon: v2.4.1},
  month        = may,
  year         = 2024,
  publisher    = {Zenodo},
  version      = {v2.4.1},
  doi          = {10.5281/zenodo.11171501},
  url          = {https://doi.org/10.5281/zenodo.11171501}
}

Contact

Feel free to chat with us on Discord.

Codecarbon was formerly developed by volunteers from Mila and the DataForGoodFR community alongside donated professional time of engineers at Comet.ml and BCG GAMMA.

Now CodeCarbon is supported by Code Carbon, a French non-profit organization whose mission is to accelerate the development and adoption of CodeCarbon.

Star History

Star History Chart


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GitHub Events

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Committers metadata

Last synced: 2 days ago

Total Commits: 2,360
Total Committers: 122
Avg Commits per committer: 19.344
Development Distribution Score (DDS): 0.86

Commits in past year: 504
Committers in past year: 40
Avg Commits per committer in past year: 12.6
Development Distribution Score (DDS) in past year: 0.786

Name Email Commits
benoit-cty 4****y@u****v 331
benoit-cty 6****y 327
vict0rsch v****h@p****e 193
Kamal Goyal g****l@b****m 182
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MarionCoutarel m****z@g****m 108
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dependabot[bot] 4****] 64
jl-datascientist j****e@g****m 51
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Liam Connell c****m@b****m 39
davidberenstein1957 d****n@g****m 39
Amine Saboni a****i@o****m 37
patrick.lloret@protonmail.com p****t@p****m 37
benoit-cty b****y@l****v 31
benoit-cty b****y@e****m 30
Cian Cullinan c****n@g****m 25
Alexis Cruveiller a****r@g****m 24
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OUMINA-SARA o****a@b****m 22
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IamLRBA j****s@g****m 21
Mathilde Leval m****l@c****m 18
MyGodItsFull0fStars c****r@e****t 18
Sasha Luccioni l****s@m****c 17
Aditya Joshi 1****i@g****m 17
Kamal Nayan Goyal k****l 16
copilot-swe-agent[bot] 1****t 14
and 92 more...

Committer domains:


Issue and Pull Request metadata

Last synced: 2 days ago

Total issues: 412
Total pull requests: 860
Average time to close issues: 7 months
Average time to close pull requests: 22 days
Total issue authors: 195
Total pull request authors: 111
Average comments per issue: 2.55
Average comments per pull request: 0.92
Merged pull request: 657
Bot issues: 0
Bot pull requests: 77

Past year issues: 66
Past year pull requests: 178
Past year average time to close issues: about 1 month
Past year average time to close pull requests: 10 days
Past year issue authors: 30
Past year pull request authors: 32
Past year average comments per issue: 1.73
Past year average comments per pull request: 0.92
Past year merged pull request: 91
Past year bot issues: 0
Past year bot pull requests: 26

More stats: https://issues.ecosyste.ms/repositories/lookup?url=https://github.com/mlco2/codecarbon

Top Issue Authors

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Top Pull Request Authors

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  • inimaz (138)
  • dependabot[bot] (77)
  • prmths128 (69)
  • SaboniAmine (68)
  • vict0rsch (30)
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Top Issue Labels

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  • bug (57)
  • good first issue (56)
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  • help wanted (14)
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  • Dashboard (8)
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  • wontfix (6)
  • P3 (6)
  • docs (5)
  • invalid (1)
  • Expand contributors (1)
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Top Pull Request Labels

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  • docs (2)
  • good first issue (1)

Package metadata

pypi.org: codecarbon

  • Homepage: https://codecarbon.io/
  • Documentation: https://docs.codecarbon.io/
  • Licenses: MIT
  • Latest release: 3.2.7 (published 13 days ago)
  • Last Synced: 2026-05-29T14:00:55.186Z (about 16 hours ago)
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conda-forge.org: codecarbon

Emissions Tracker is a Python package for tracking the carbon emissions produced by various kinds of computer programs, from straightforward algorithms to deep neural networks. By taking into account your computing infrastructure, location, usage and running time, Emissions Tracker can provide an estimate of how much CO2 you produced, and give you some comparisons with common modes of transporation to give you an order of magnitude.

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conda-forge.org: codecarbon-test

Emissions Tracker is a Python package for tracking the carbon emissions produced by various kinds of computer programs, from straightforward algorithms to deep neural networks. By taking into account your computing infrastructure, location, usage and running time, Emissions Tracker can provide an estimate of how much CO2 you produced, and give you some comparisons with common modes of transporation to give you an order of magnitude.

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  • Licenses: MIT
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  • Last Synced: 2026-03-10T03:28:10.264Z (3 months ago)
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conda-forge.org: codecarbon-viz

Emissions Tracker is a Python package for tracking the carbon emissions produced by various kinds of computer programs, from straightforward algorithms to deep neural networks. By taking into account your computing infrastructure, location, usage and running time, Emissions Tracker can provide an estimate of how much CO2 you produced, and give you some comparisons with common modes of transporation to give you an order of magnitude.

  • Homepage: https://pypi.org/project/codecarbon/
  • Licenses: MIT
  • Latest release: 2.1.4 (published over 3 years ago)
  • Last Synced: 2026-03-10T03:25:28.554Z (3 months ago)
  • Versions: 6
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  • Downloads: 19,055 Total
  • Rankings:
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conda-forge.org: codecarbon-dev

Emissions Tracker is a Python package for tracking the carbon emissions produced by various kinds of computer programs, from straightforward algorithms to deep neural networks. By taking into account your computing infrastructure, location, usage and running time, Emissions Tracker can provide an estimate of how much CO2 you produced, and give you some comparisons with common modes of transporation to give you an order of magnitude.

  • Homepage: https://pypi.org/project/codecarbon/
  • Licenses: MIT
  • Latest release: 2.1.4 (published over 3 years ago)
  • Last Synced: 2026-04-08T09:55:27.014Z (about 2 months ago)
  • Versions: 6
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nixpkgs-unstable: python313Packages.codecarbon

Track emissions from Compute and recommend ways to reduce their impact on the environment

nixpkgs-unstable: python314Packages.codecarbon

Track emissions from Compute and recommend ways to reduce their impact on the environment


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  • @types/react 19.1.0 development
  • @types/react-dom 19.1.1 development
  • eslint ^9.39.2 development
  • eslint-config-next 15.2.4 development
  • eslint-config-prettier ^9.1.2 development
  • postcss ^8.5.6 development
  • prettier 3.3.3 development
  • typescript ^5.9.3 development
  • @radix-ui/react-dialog ^1.1.15
  • @radix-ui/react-dropdown-menu ^2.1.16
  • @radix-ui/react-label ^2.1.8
  • @radix-ui/react-navigation-menu ^1.2.14
  • @radix-ui/react-popover ^1.1.15
  • @radix-ui/react-select ^2.2.6
  • @radix-ui/react-separator ^1.1.8
  • @radix-ui/react-slot ^1.2.4
  • @radix-ui/react-switch ^1.2.6
  • @radix-ui/react-tabs ^1.1.13
  • @radix-ui/react-tooltip ^1.2.8
  • class-variance-authority ^0.7.1
  • clsx ^2.1.1
  • copy-to-clipboard ^3.3.3
  • date-fns ^3.6.0
  • glob ^11.1.0
  • lucide-react ^0.411.0
  • next 15.4.10
  • next-themes ^0.4.6
  • react 19.1.0
  • react-day-picker ^9.13.0
  • react-dom 19.1.0
  • recharts ^2.15.4
  • sonner ^2.0.7
  • swr ^2.3.8
  • tailwind-merge ^2.6.1
  • tailwindcss ^3.4.19
  • tailwindcss-animate ^1.0.7
  • zod ^3.25.76

Score: 25.794865848996324