lib/python3.10/site-packages/codecarbon-2.8.3.dist-info/METADATA

Metadata-Version: 2.4
Name: codecarbon
Version: 2.8.3
Project-URL: Homepage, https://codecarbon.io/
Project-URL: Repository, https://github.com/mlco2/codecarbon
Project-URL: Dashboard, http://dashboard.codecarbon.io/
Project-URL: Documentation, https://mlco2.github.io/codecarbon/
Project-URL: Issues, https://github.com/mlco2/codecarbon/issues
Project-URL: Changelog, https://github.com/mlco2/codecarbon/releases
Author: Mila, DataForGood, BCG GAMMA, Comet.ml, Haverford College
License-File: LICENSE
Classifier: License :: OSI Approved :: MIT License
Classifier: Natural Language :: English
Classifier: Programming Language :: Python :: 3.7
Classifier: Programming Language :: Python :: 3.8
Classifier: Programming Language :: Python :: 3.9
Classifier: Programming Language :: Python :: 3.10
Classifier: Programming Language :: Python :: 3.11
Classifier: Programming Language :: Python :: 3.12
Classifier: Programming Language :: Python :: 3.13
Requires-Python: >=3.7
Requires-Dist: arrow
Requires-Dist: click
Requires-Dist: fief-client[cli]
Requires-Dist: pandas
Requires-Dist: prometheus-client
Requires-Dist: psutil
Requires-Dist: py-cpuinfo
Requires-Dist: pynvml
Requires-Dist: questionary
Requires-Dist: rapidfuzz
Requires-Dist: requests
Requires-Dist: rich
Requires-Dist: typer
Provides-Extra: viz
Requires-Dist: dash; extra == 'viz'
Requires-Dist: dash-bootstrap-components<1.0.0; extra == 'viz'
Requires-Dist: fire; extra == 'viz'
Description-Content-Type: text/markdown

![banner](docs/edit/images/banner.png)

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

[**Documentation**](https://mlco2.github.io/codecarbon)

<br/>

[![](https://anaconda.org/conda-forge/codecarbon/badges/version.svg)](https://anaconda.org/conda-forge/codecarbon)
[![](https://anaconda.org/codecarbon/codecarbon/badges/version.svg)](https://anaconda.org/codecarbon/codecarbon)
[![](https://img.shields.io/pypi/v/codecarbon?color=024758)](https://pypi.org/project/codecarbon/)
[![DOI](https://zenodo.org/badge/263364731.svg)](https://zenodo.org/badge/latestdoi/263364731)
[![Downloads](https://static.pepy.tech/badge/codecarbon/month)](https://pepy.tech/project/codecarbon)


- [About CodeCarbon 💡](#about-codecarbon-)
- [Quickstart 🚀](#quickstart-)
    - [Installation 🔧](#installation-)
    - [Start to estimate your impact 📏](#start-to-estimate-your-impact-)
      - [Monitoring your whole machine](#monitoring-your-machine-)
      - [In your python code](#in-your-python-code-)
      - [Visualize](#visualize-)
- [Contributing 🤝](#contributing-)
- [How To Cite 📝](#how-to-cite-)
- [Contact 📝](#contact-)

# About CodeCarbon 💡

**CodeCarbon** started with a quite simple question: 

**What is the carbon emission impact of my computer program? :shrug:**

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 CO<sub>2</sub> 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](docs/edit/images/calculation.png)

We explain more about this calculation in the [**Methodology**](https://mlco2.github.io/codecarbon/methodology.html#) 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**
```python
pip install codecarbon
```

**From Conda repository**
```python
conda install -c codecarbon codecarbon
```
To see more installation options please refer to the documentation: [**Installation**](https://mlco2.github.io/codecarbon/installation.html#)

## Start to estimate your impact 📏

To get an experiment_id enter:
```python
! codecarbon init
```
You can now store it in a **.codecarbon.config** at the root of your project 
```python
[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 🐍
```python
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**](https://mlco2.github.io/codecarbon/usage.html#)

## Visualize 📊

You can now visualize your experiment emissions on the [dashboard](https://dashboard.codecarbon.io/).
![dashboard](docs/edit/images/dashboard.png)

*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**](https://mlco2.github.io/codecarbon) 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 :arrow_upper_right:](https://github.com/mlco2/codecarbon/blob/master/CONTRIBUTING.md)

Contact [@vict0rsch](https://github.com/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](https://zenodo.org/records/11171501).

Here is a sample for BibTeX: 
```tex 
@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](https://github.com/vict0rsch) [@benoit-cty](https://github.com/benoit-cty) and [@SaboniAmine](https://github.com/saboniamine). Codecarbon is developed by volunteers from [**Mila**](http://mila.quebec) and the [**DataForGoodFR**](https://twitter.com/dataforgood_fr) community alongside donated professional time of engineers at [**Comet.ml**](https://comet.ml) and [**BCG GAMMA**](https://www.bcg.com/en-nl/beyond-consulting/bcg-gamma/default).