forecast-solar
Asynchronous Python client for getting forecast solar information
Decision gist · record as of 2026-08-14
Yes, if you have solar panels and need programmatic access to production forecasts. The package is actively maintained, has low install friction, and integrates cleanly with async Python applications. Requires a forecast.solar API key (free tier available) and Python 3.12+; some advanced features require a paid subscription.AI-flagged interpretation of the facts on this page — verify before relying
Before you install
- Requires an API key from forecast.solar; some features (multiple planes) require a Personal Plus subscription or higher.
- Low install friction with only two lightweight runtime dependencies (aiohttp and yarl).
- Active maintenance with recent release (69 days ago) and ongoing commits; supports modern Python versions (3.12, 3.13, 3.14).
License · maintenance · safety
MIT (permissive) — MIT license permits unrestricted use, modification, and distribution with minimal restrictions—suitable for both open-source and commercial projects.
last release 2026-06-06 (69 days) · last repo commit 2026-08-11 · 32 stars
0 known vulnerabilities (OSV.dev, 2026-08-14) · 74,555 downloads/mo, #14,818 on PyPI
Alternatives
Verify before relying
import asyncio
from forecast_solar import ForecastSolar
async def main():
async with ForecastSolar(
api_key="YOUR_API_KEY",
latitude=52.16,
longitude=4.47,
declination=20,
azimuth=10,
kwp=2.160
) as forecast:
estimate = await forecast.estimate()
print(estimate)
asyncio.run(main())- Whether free tier API access provides sufficient rate limits for typical use cases.
- Accuracy of forecasts under various weather conditions and geographic regions.
- Performance characteristics when querying multiple planes simultaneously.
What it is and what it does
forecast-solar is an async Python wrapper around the forecast.solar API that retrieves solar panel production forecasts for specific geographic locations and panel configurations. It returns energy production estimates (in kWh) for various time windows—today, tomorrow, this hour, next hour, and remaining daylight—along with power output predictions (in watts) at multiple future intervals and peak timing information.
The library is designed for integration with home automation systems and energy management applications. It supports single or multiple solar panel planes (with appropriate subscription), accepts panel configuration parameters like tilt angle (declination), direction (azimuth), and capacity (kWp), and provides optional damping factors to account for weather variability. All API calls are asynchronous, making it suitable for non-blocking integration into event-driven applications.
Use it for
- Home automation systems that adjust energy consumption based on predicted solar output.
- Energy management dashboards displaying hourly and daily solar production forecasts.
- Battery charging optimization that schedules charging during predicted peak solar production hours.
- Grid-tied solar systems that need to forecast excess production for export planning.
- Renewable energy monitoring applications tracking multiple roof-facing solar arrays.
Worth the install?
AI-flagged interpretation of the facts on this page. Verify before relying on it.
Yes, if you have solar panels and need programmatic access to production forecasts.
The package is actively maintained, has low install friction, and integrates cleanly with async Python applications. Requires a forecast.solar API key (free tier available) and Python 3.12+; some advanced features require a paid subscription.
Install
forecast-solar on PyPI
Before you install
Low install friction with only two lightweight runtime dependencies (aiohttp and yarl). Active maintenance with recent release (69 days ago) and ongoing commits; supports modern Python versions (3.12, 3.13, 3.14).
Requires an API key from forecast.solar; some features (multiple planes) require a Personal Plus subscription or higher.
License in practice
MIT license permits unrestricted use, modification, and distribution with minimal restrictions—suitable for both open-source and commercial projects.
Quickstart
import asyncio
from forecast_solar import ForecastSolar
async def main():
async with ForecastSolar(
api_key="YOUR_API_KEY",
latitude=52.16,
longitude=4.47,
declination=20,
azimuth=10,
kwp=2.160
) as forecast:
estimate = await forecast.estimate()
print(estimate)
asyncio.run(main())Verify before relying
- Whether free tier API access provides sufficient rate limits for typical use cases.
- Accuracy of forecasts under various weather conditions and geographic regions.
- Performance characteristics when querying multiple planes simultaneously.
Package facts
| License | MIT permissive |
| Python support | Supports the current Python release >=3.12 |
| Install friction | Low. Pure-Python wheel |
| Runtime dependencies | 2 packagesaiohttpyarl |
| Maintenance | Actively maintained 69 days since the last release |
| Last repo commit | |
| First released | |
| Downloads | 74,555 / month, #14,818 on PyPI 30-day window, as of 2026-08-14 |
| Known vulnerabilities | None known OSV.dev, checked 2026-08-14 |
| Classifiers | Framework :: AsyncIOIntended Audience :: DevelopersLicense :: OSI Approved :: MIT LicenseNatural Language :: EnglishProgramming Language :: Python :: 3Programming Language :: Python :: 3.12Programming Language :: Python :: 3.13Programming Language :: Python :: 3.14Topic :: Software Development :: Libraries :: Python Modules |
Evidence: forecast_solar-5.0.1-py3-none-any.whl
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