Overview
Unplugg is a forecasting API that predicts future values from your historical time series data using machine learning. You send past measurements and get back forecasted values for upcoming periods automatically. It is handy for predicting demand, resource usage, or any metric that follows a pattern over time.
Beginner Tip
The more historical data you provide — ideally several full seasonal cycles — the more accurate your forecasts will be. Start with the test API at unplu.gg/test_api.html to experiment without creating an account.
Available Data
Example Response
{
"location": "Tokyo",
"temperature": {
"current": 22,
"feels_like": 24,
"min": 18,
"max": 26
},
"condition": "Partly Cloudy",
"humidity": 65,
"wind": {
"speed": 12,
"direction": "NE"
},
"forecast": [
{
"date": "2025-01-16",
"high": 25,
"low": 17,
"condition": "Sunny"
}
]
} Field Reference
forecast Predicted future values for the number of periods specified by horizon. lower_bound Lower confidence interval for each forecasted value. upper_bound Upper confidence interval for each forecasted value. model Name of the forecasting model selected by the API for this series. Implementation Example
const url = "https://unplu.gg/";
// Replace headers or query params with the values required by this API.
const response = await fetch(url, {
headers: {
"X-API-Key": "YOUR_API_KEY"
}
});
if (!response.ok) throw new Error(`Request failed: ${response.status}`);
const data = await response.json();
console.log(data); What Can You Build?
Note: These code examples are AI-generated and unverified. Always refer to the official API documentation for accurate usage.
Common Errors & Troubleshooting
Matrix Score Breakdown
Partially tested on Apr 5, 2026
Technical Specifications
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