pvlearn
Teach your home to predict its own solar production.
A self-learning PV production forecast library and REST service. Trains on a plant's own historical measurements instead of a generic physical plant model — no orientation, tilt, or kWp input required.
Development is in progress; see pvlearn-umsetzungsplan.md for the
architecture, canonical data model, and phased roadmap, and AGENTS.md for
contributor and AI-agent conventions.
1 maintainer
Release files for pvlearn 0.2.0
For a detailed explanation of source distributions (sdists) and built distributions (wheels), please see the package formats documentation.
Source distribution (sdist)
| File | Size | Uploaded | |
|---|---|---|---|
| pvlearn-0.2.0.tar.gz | 372.2 kB | Details |
Built distribution (wheel)
| File | Interpreter | ABI | Platform | Reset |
|---|---|---|---|---|
| pvlearn-0.2.0-py3-none-any.whl | Python 3 | none | any | Details |
Total release size: 389.0 kB
Release files / pvlearn-0.2.0.tar.gz
| Download URL | pvlearn-0.2.0.tar.gz |
|---|---|
| Size | 372.2 kB |
| Tags | Source |
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SHA-256 checksum How to use checksums |
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Transparency logRelease files / pvlearn-0.2.0-py3-none-any.whl
| Download URL | pvlearn-0.2.0-py3-none-any.whl |
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| Size | 16.8 kB |
| Tags | Python 3 |
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SHA-256 checksum How to use checksums |
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twine/7.0.0 CPython/3.13.14
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