Dynamic WUE / PUE / carbon intensity data
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- Dominant language
- Python
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Description
Is your feature request related to a problem? Please describe.
Currently, data used to estimate the carbon impact ouf of electrical consumption is stored in the package, stored manually.
CPU references & their TDP values are often requested by users, and must be integrated in a manual way.
Data center carbon impact & global energy mix values are updated at most yearly when we get the data, with heterogeneous sources.
Describe the solution you'd like
A clear process to update data, which can be applied to the following paramters :
- Datacenter PUE, when available
- Location-based energy mix
- Country-based energy mix
- Datacenter WUE
- Processors TDP
- Other ?
It could be exposed to the user via multiple ways :
- Make it available through the public API, and make the OnlineTracker query it periodically
- Export a new version of the datasets at each release, for a full offline fallback
- Other ?
Both ways would require an ingestion task, which could be automated quite easily.
Describe alternatives you've considered
A clear and concise description of any alternative solutions or features you've considered.
Additional context
Could help solving following issues: #894, #513, #503, #435, #403 (with a better support / doc of electricitymaps), #384, #365, #336, #222, #138
What could be interesting data sources ?
Contributor guide
First steps
- Read the whole issue, then the project's contributing guide.
- Comment on the issue to say you are picking it up — it saves two people doing the same work.
- Fork the repository and make your change on a branch.
- Open a pull request that references the issue number.
Research direction
Start by locating the package's manually stored carbon, energy-mix, PUE, WUE, and processor TDP data. Review how the public API, OnlineTracker, release datasets, and any existing ingestion task could expose or update it. Done requires an agreed update process and a defined choice between online access, release exports, or both.
Written by the indexing model from the issue text.
Assessment
- Tech stack
- python
- Domain
- data-engineering
- Issue type
- Feature
- Difficulty
- 5/5
- Estimated time
- Over a week
- Activity status
- Quiet
- Clarity
- Needs clarification
- Newbie friendliness
- 25/100