Quickstart Guide

Get started with ForecastAPI in just 5 minutes. This guide will walk you through making your first forecast request.

Prerequisites

You'll need an API key to get started. Sign up for a free account to get your key and 1,000 free API calls per month.

Step 1: Get Your API Key

  1. 1
    Sign up for a free account at /register
  2. 2
    Navigate to your Dashboard and click "API Keys"
  3. 3
    Click "Generate New Key" and copy your API key

Step 2: Prepare Your Data

ForecastAPI works with time series data in a simple JSON format. Your data should include:

  • date: The time period (YYYY-MM-DD) in UTC
  • value: The numeric value for that period

Example Data Format

{
  "data": [
    {"date": "2024-01-01", "value": 120},
    {"date": "2024-02-27", "value": 135},
    {"date": "2024-03-31", "value": 155},
    {"date": "2024-04-01", "value": 142},
    {"date": "2024-05-01", "value": 168}
  ],
  "periods": 6,
  "frequency": "M",
  "data_type": "sales"
}

Step 3: Make Your First Request

api.forecastapi.com
curl -X POST https://forecastapi.com/v2/forecast \
  -H "Authorization: Bearer YOUR_API_KEY" \
  -H "Content-Type: application/json" \
  -d '{
    "data": [
      {"date": "2024-01", "value": 120},
      {"date": "2024-02", "value": 135},
      {"date": "2024-03", "value": 155}
    ],
    "periods": 6,
    "frequency": "M"
  }'

# Response in 287ms
{
  "forecast": [
    {"date": "2024-04", "value": 168.5, "lower": 162.3, "upper": 174.7},
    {"date": "2024-05", "value": 175.2, "lower": 168.1, "upper": 182.3},
    ...
  ],
  "method": "exponential_smoothing",
  "confidence": 0.95
}

Understanding the Response

ForecastAPI returns a comprehensive response with your forecast and additional insights:

{
  "forecast": [
    {
      "date": "2024-06",
      "value": 175.2,
      "lower": 168.1,
      "upper": 182.3
    },
    {
      "date": "2024-07",
      "value": 181.5,
      "lower": 173.8,
      "upper": 189.2
    }
  ],
  "method": "exponential_smoothing",
  "confidence": 0.95,
  "analysis": {
    "pattern_type": "regular",
    "trend": "increasing",
    "seasonality": "none_detected"
  }
}

Response Fields

Field Description
forecast Array of forecast periods with predicted values and confidence intervals
method The forecasting algorithm that was automatically selected
confidence Confidence level for the prediction intervals (typically 0.95)
analysis Additional insights about your data patterns and trends

Common Parameters

Data Type

Specify your data type for optimized model selection:

  • "sales" - Sales data (uses intermittent demand methods for sparse data)
  • "demand" - Demand forecasting
  • "inventory" - Inventory levels
  • "web_traffic" - Website analytics
  • Custom values - Any string for custom data types

Frequency

Specify your data frequency:

  • "D" - Daily
  • "W" - Weekly
  • "M" - Monthly
  • "Q" - Quarterly
  • "Y" - Yearly
  • "H" - Hourly

What's Next?