Start Forecasting in 5 Minutes

import os
import requests
from dotenv import load_dotenv

load_dotenv()

def upload_and_train():
    # Upload historical data
    url = f"{os.getenv('ONA_API_URL')}/upload_historical"
    headers = {"x-api-key": os.getenv('ONA_API_KEY')}
    
    params = {
        "customer_id": "your-customer-id",
        "filename": "historical_data.csv",
        "manufacturer": "SolarEdge", 
        "location": "CapeTown",
        "region": "af-south-1"
    }
    
    with open('historical_data.csv', 'rb') as file:
        response = requests.post(url, params=params, headers=headers, data=file)
        print(f"Upload: {response.status_code}")
    
    # Train forecasting model
    train_url = f"{os.getenv('ONA_API_URL')}/train"
    train_params = {
        "customer_id": "your-customer-id",
        "location": "CapeTown",
        "manufacturer": "SolarEdge",
        "serial_number": "SE123456",
        "region": "af-south-1",
        "testing": "True"
    }
    
    train_response = requests.post(train_url, params=train_params, headers=headers)
    print(f"Training: {train_response.status_code}")
    return train_response.json()

# Run it
result = upload_and_train()
print("✅ Model training started! Check your email for results.")

from ona_sdk import OnaClient

# Initialize client
client = OnaClient(api_key="your-api-key")

# Upload and train in one step
result = client.upload_and_train(
    file_path="energy_data.csv",
    customer_id="your-id",
    location="CapeTown",
    manufacturer="SolarEdge"
)

print("✅ Training started! Results will be emailed to you.")