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 from Contributors

language-model transformer archiving climate-change measur tensors autograd generic annotation sustainability

Last synced: about 16 hours ago
JSON representation

Repository metadata

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

Host: GitHub
URL: https://github.com/mlco2/codecarbon
Owner: mlco2
License: mit
Created: 2020-05-12T14:44:03.000Z (almost 5 years ago)
Default Branch: master
Last Pushed: 2025-04-20T14:51:18.000Z (7 days ago)
Last Synced: 2025-04-23T21:59:24.838Z (3 days ago)
Language: Python
Homepage: https://mlco2.github.io/codecarbon
Size: 27.6 MB
Stars: 1,371
Watchers: 22
Forks: 204
Open Issues: 104
Releases: 48
Metadata Files:
- Readme: README.md
- Contributing: CONTRIBUTING.md
- Funding: .github/FUNDING.yml
- License: LICENSE

README.md

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

Documentation

About CodeCarbon 💡
Quickstart 🚀
- Installation 🔧
- Start to estimate your impact 📏
Contributing 🤝
How To Cite 📝
Contact 📝

About CodeCarbon 💡

CodeCarbon started with a quite simple question:

What is the carbon emission impact of my computer program? 🤷

We found some global data like "computing currently represents roughly 0.5% of the world’s energy consumption" but nothing on our individual/organisation level impact.

At CodeCarbon, we believe, along with Niels Bohr, that "Nothing exists until it is measured". So we found a way to estimate how much CO2 we produce while running our code.

How?

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.

calculation Summary

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

Our hope is that this package will be used widely for estimating the carbon footprint of computing, and for establishing best practices with regards to the disclosure and reduction of this footprint.

So ready to "change the world one run at a time"? Let's start with a very quick set up.

Quickstart 🚀

Installation 🔧

From PyPI repository

pip install codecarbon

From Conda repository

conda install -c codecarbon codecarbon

To see more installation options please refer to the documentation: Installation

Start to estimate your impact 📏

To get an experiment_id enter:

! codecarbon init

You can now store it in a .codecarbon.config at the root of your project

[codecarbon]
log_level = DEBUG
save_to_api = True
experiment_id = 2bcbcbb8-850d-4692-af0d-76f6f36d79b2 #the experiment_id you get with init

Now you have 2 main options:

Monitoring your machine 💻

In your command prompt use:
codecarbon monitor
The package will track your emissions independently from your code.

In your Python code 🐍

from codecarbon import track_emissions
@track_emissions()
def your_function_to_track():
  # your code

The package will track the emissions generated by the execution of your function.

There is other ways to use codecarbon package, please refer to the documentation to learn more about it: Usage

Visualize 📊

You can now visualize your experiment emissions on the dashboard.

Note that for now, all emissions data send to codecarbon API are public.

Hope you enjoy your first steps monitoring your carbon computing impact!
Thanks to the incredible codecarbon community 💪🏼 a lot more options are available using codecarbon including:

offline mode

cloud mode

comet integration...

Please explore the Documentation to learn about it
If ever what your are looking for is not yet implemented, let us know through the issues and even better become one of our 🦸🏼‍♀️🦸🏼‍♂️ contributors! more info 👇🏼

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 🥇

In order to contribute a change to our code base, please submit a pull request (PR) via GitHub and someone from our team will go over it and accept it.

Check out our contribution guidelines ↗️

Contact @vict0rsch to be added to our slack workspace if you want to contribute regularly!

How To Cite 📝

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

Here is a sample for BibTeX:

@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 📝

Maintainers are @vict0rsch @benoit-cty and @SaboniAmine. Codecarbon is developed by volunteers from Mila and the DataForGoodFR community alongside donated professional time of engineers at Comet.ml and BCG GAMMA.

Star History

Comparison of the number of stars accumulated by the different Python CO2 emissions projects:

Owner metadata

Name: mlco2
Login: mlco2
Email:
Kind: organization
Description:
Website:
Location:
Twitter:
Company:
Icon url: https://avatars.githubusercontent.com/u/54071934?v=4
Repositories: 3
Last ynced at: 2023-03-04T16:29:39.216Z
Profile URL: https://github.com/mlco2

GitHub Events

Total

Create event: 85
Release event: 12
Issues event: 56
Watch event: 225
Delete event: 61
Issue comment event: 174
Push event: 358
Pull request event: 163
Pull request review event: 165
Pull request review comment event: 60
Fork event: 28

Last Year

Create event: 85
Release event: 12
Issues event: 56
Watch event: 225
Delete event: 61
Issue comment event: 174
Push event: 358
Pull request event: 163
Pull request review event: 165
Pull request review comment event: 60
Fork event: 28

Committers metadata

Last synced: 7 days ago

Total Commits: 1,820
Total Committers: 87
Avg Commits per committer: 20.92
Development Distribution Score (DDS): 0.841

Commits in past year: 454
Committers in past year: 27
Avg Commits per committer in past year: 16.815
Development Distribution Score (DDS) in past year: 0.641

Name	Email	Commits
benoit-cty	6****y	290
benoit-cty	4**y@u**v	225
vict0rsch	v**h@p**e	193
Kamal Goyal	g**l@b**m	182
MarionCoutarel	m**z@g**m	108
LuisBlanche	l**r@g**m	83
inimaz	4****z	76
jl-datascientist	j**e@g**m	51
Boris Feld	l**n@g**m	48
Liam Connell	c**m@b**m	39
Amine Saboni	a**i@o**m	37
[email protected]	p**t@p**m	32
benoit-cty	b**y@e**m	30
Amine Saboni	4****e	28
Alexis Cruveiller	a**r@g**m	24
Mathilde Léval	m**l@g**m	22
OUMINA-SARA	o**a@b**m	22
Zhao Franklin	q**o@b**u	22
dependabot[bot]	4****]	22
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
Hugues Souchard de Lavoreille	h**l@g**m	14
AlexisBogroff	a**f@g**m	14
Alexandre Phiev	a**v@g**m	13
Nikolas Laskaris	l**k@g**m	13
rosekelly6400	r**0@g**m	9
Edoardo Abati	2****i	9
and 57 more...

Committer domains:

Issue and Pull Request metadata

Last synced: 1 day ago

Total issues: 349
Total pull requests: 506
Average time to close issues: 6 months
Average time to close pull requests: 23 days
Total issue authors: 166
Total pull request authors: 83
Average comments per issue: 3.09
Average comments per pull request: 1.05
Merged pull request: 428
Bot issues: 0
Bot pull requests: 34

Past year issues: 88
Past year pull requests: 231
Past year average time to close issues: 27 days
Past year average time to close pull requests: 12 days
Past year issue authors: 57
Past year pull request authors: 28
Past year average comments per issue: 3.09
Past year average comments per pull request: 0.69
Past year merged pull request: 183
Past year bot issues: 0
Past year bot pull requests: 34

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

Top Issue Authors

benoit-cty (42)
vict0rsch (26)
inimaz (14)
LiamConnell (13)
SaboniAmine (9)
dsblank (8)
mkbane (8)
stas00 (7)
kngoyal (6)
RafiullahOmar (6)
headscott (6)
qxpBlog (4)
pugantsov (4)
Lothiraldan (4)
TECO-Octo (3)

Top Pull Request Authors

benoit-cty (97)
inimaz (68)
prmths128 (36)
SaboniAmine (34)
dependabot[bot] (34)
vict0rsch (30)
Lothiraldan (20)
kngoyal (19)
LiamConnell (12)
MyGodItsFull0fStars (12)
mathilde-leval (8)
LuisBlanche (8)
dsblank (6)
MarionCoutarel (6)
adijo (5)

Top Issue Labels

enhancement (82)
good first issue (52)
bug (46)
documentation (35)
question (32)
dataforgood (20)
API (17)
help wanted (15)
P1 (10)
P2 (7)
P3 (7)
wontfix (7)
docs (4)
Dashboard (4)
duplicate (2)
invalid (1)
Expand contributors (1)

Top Pull Request Labels

dependencies (34)
API (13)
javascript (10)
python (8)
enhancement (8)
bug (3)
docs (2)
dataforgood (2)
Dashboard (2)
good first issue (1)
documentation (1)
invalid (1)

Package metadata

Total packages: 5
Total downloads:
- pypi: 59,633 last-month
Total docker downloads: 430,060
Total dependent packages: 39 (may contain duplicates)
Total dependent repositories: 807 (may contain duplicates)
Total versions: 78
Total maintainers: 3

pypi.org: codecarbon

Homepage: https://codecarbon.io/
Documentation: https://mlco2.github.io/codecarbon/
Licenses: MIT License
Latest release: 3.0.0 (published 9 days ago)
Last Synced: 2025-04-18T07:31:27.775Z (9 days ago)
Versions: 53
Dependent Packages: 36
Dependent Repositories: 806
Downloads: 59,633 Last month
Docker Downloads: 430,060
Rankings:
- Dependent packages count: 0.372%
- Dependent repos count: 0.423%
- Average: 0.73%
- Docker downloads count: 0.955%
- Downloads: 1.169%
Maintainers (3)

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.

Homepage: https://pypi.org/project/codecarbon/
Licenses: MIT
Latest release: 2.1.4 (published over 2 years ago)
Last Synced: 2025-04-25T14:08:02.158Z (1 day ago)
Versions: 7
Dependent Packages: 2
Dependent Repositories: 1
Rankings:
- Stargazers count: 15.742%
- Forks count: 18.727%
- Average: 19.538%
- Dependent packages count: 19.581%
- Dependent repos count: 24.103%

conda-forge.org: codecarbon-test

Homepage: https://pypi.org/project/codecarbon/
Licenses: MIT
Latest release: 2.1.4 (published over 2 years ago)
Last Synced: 2025-04-25T14:08:00.299Z (1 day ago)
Versions: 6
Dependent Packages: 1
Dependent Repositories: 0
Rankings:
- Stargazers count: 15.583%
- Forks count: 19.206%
- Average: 24.409%
- Dependent packages count: 28.82%
- Dependent repos count: 34.025%

conda-forge.org: codecarbon-viz

Homepage: https://pypi.org/project/codecarbon/
Licenses: MIT
Latest release: 2.1.4 (published over 2 years ago)
Last Synced: 2025-04-25T14:08:01.941Z (1 day ago)
Versions: 6
Dependent Packages: 0
Dependent Repositories: 0
Rankings:
- Stargazers count: 15.583%
- Forks count: 19.206%
- Average: 29.998%
- Dependent repos count: 34.025%
- Dependent packages count: 51.175%

conda-forge.org: codecarbon-dev

Homepage: https://pypi.org/project/codecarbon/
Licenses: MIT
Latest release: 2.1.4 (published over 2 years ago)
Last Synced: 2025-04-02T02:57:09.631Z (25 days ago)
Versions: 6
Dependent Packages: 0
Dependent Repositories: 0
Rankings:
- Stargazers count: 15.583%
- Forks count: 19.206%
- Average: 29.998%
- Dependent repos count: 34.025%
- Dependent packages count: 51.175%

Dependencies

carbonserver/docker/requirements-dev.txt pypi

alembic * development
fastapi * development
fastapi-pagination * development
psycopg2 * development
pydantic * development
requests * development
sqlalchemy * development
tox * development
uvicorn * development

carbonserver/requirements-dev.txt pypi

alembic * development
bcrypt * development
dependency-injector * development
fastapi * development
fastapi-pagination * development
psycopg2-binary * development
pydantic * development
python-dateutil * development
requests * development
sqlalchemy * development
tox * development
uvicorn * development

carbonserver/requirements.txt pypi

alembic *
bcrypt *
dependency-injector *
fastapi *
fastapi-pagination *
psycopg2-binary *
pydantic *
python-dateutil *
requests *
sqlalchemy *
tox *
uvicorn *

examples/requirements-examples.txt pypi

keras-tuner *
tensorflow *
torch ==1.8.1
torchvision *

requirements-dev.txt pypi

arrow * development
black * development
dash * development
dash_bootstrap_components * development
dataclasses * development
fire * development
flake8 * development
fuzzywuzzy * development
isort * development
mypy * development
pandas * development
psutil * development
py-cpuinfo * development
pynvml * development
requests * development
responses * development
sphinx * development
sphinx-rtd-theme * development

requirements-test.txt pypi

fuzzywuzzy * test
mock * test
numpy * test
psutil * test
pytest * test
requests-mock * test
responses * test
tox * test

.github/workflows/build.yml actions

actions/checkout v2 composite
actions/setup-python v1 composite
actions/setup-python v2 composite
postgres 12 docker

.github/workflows/package.yml actions

actions/checkout v2 composite
actions/setup-python v1 composite
actions/upload-artifact v1 composite

.github/workflows/pre-commit.yml actions

actions/cache v1 composite
actions/checkout v2 composite
actions/setup-python v2 composite
pre-commit/action v3.0.0 composite

.github/workflows/python-publish.yml actions

actions/checkout v3 composite
actions/setup-python v3 composite
pypa/gh-action-pypi-publish 27b31702a0e7fc50959f5ad993c78deac1bdfc29 composite

.github/workflows/release-drafter.yml actions

release-drafter/release-drafter v5.7.0 composite

act/Dockerfile docker

ubuntu 20.04 build

carbonserver/docker/Dockerfile docker

ubuntu 20.04 build

docker/Dockerfile docker

python 3.8 build

docker-compose.yml docker

dpage/pgadmin4 latest
postgres 12

dashboard/requirements-new.txt pypi

codecarbon >=2.0.0
dash >=2.2.0
dash_bootstrap_components *
plotly >=5.6.0

dashboard/requirements.txt pypi

codecarbon >=2.0.0
dash >=2.2.0
gunicorn *
plotly >=5.6.0

requirements.txt pypi

codecarbon >=2.0.0
dash >=2.2.0
dash_bootstrap_components *
plotly >=5.6.0

carbonserver/setup.py pypi

setup.py pypi

Score: 24.86582197575033

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