README.md

<<<<<<< HEAD # castor-price-api

📦 Castor Price Forecasting - Complete Package

🎯 Project Summary

This is a Production-Ready API for Castor Price Forecasting using ARIMA and LSTM models.

---

📂 Project Structure

D:\models\arima\
├── 🔧 API Files
│   ├── api_production.py              ⭐ Main production API server
│   ├── api_server.py                  (Alternative API)
│   ├── test_api_production.py         ✓ API test suite
│   ├── generate_api_key.py            (Key generator)
│   └── api_keys.json                  🔐 Generated API keys
│
├── 📊 Data & Models
│   ├── daily_oilseeds_full_ml_dataset_2015_01_01_2025_12_02.csv
│   ├── forecasting_analysis.py        (Forecasting pipeline)
│   ├── Castor_Price_Forecast_Chart_Custom_Range.html  (Visualization)
│   └── Castor_Price_Forecast_Chart.html
│
├── 📚 Documentation
│   ├── ⭐ API_READY_FOR_DEPLOYMENT.md   ← START HERE
│   ├── DEPLOYMENT_GUIDE.md            (Deployment instructions)
│   ├── API_CREDENTIALS.md             (Your credentials)
│   ├── API_README.md                  (API guide)
│   └── README.md                      (This file)
│
├── 🐍 Virtual Environments
│   ├── venv_short/                    ✓ Ready to use (shorter path)
│   └── .venv/                         (Alternative)
│
└── 🎨 Visualizations
    └── *.html files                   (Interactive Plotly charts)

---

🚀 Quick Start (5 Minutes)

Step 1: Start the API Server

cd D:\models\arima
D:\models\arima\venv_short\Scripts\python.exe api_production.py

Server runs on: http://127.0.0.1:5000

Step 2: Your API Key

castor_d167aa169b5e4219a66779e45fbaaefe

Step 3: Test the API

# Health check
curl http://127.0.0.1:5000/api/health

# Get forecast
curl -X POST http://127.0.0.1:5000/api/forecast \
  -H "X-API-Key: castor_d167aa169b5e4219a66779e45fbaaefe" \
  -H "Content-Type: application/json" \
  -d '{"product":"Castor","start_date":"2025-12-01","end_date":"2026-01-31"}'

---

📋 File Descriptions

API Files

File	Purpose	Status
api_production.py	Production-ready API server	✅ Active
api_keys.json	Stores generated API keys	✅ Ready
test_api_production.py	Comprehensive test suite	✅ Ready

Data & Analysis

File	Purpose
daily_oilseeds_full_ml_dataset_2015_01_01_2025_12_02.csv	Historical price data
forecasting_analysis.py	ARIMA/LSTM model training
*.html	Interactive forecast visualizations

Documentation

File	Purpose
API_READY_FOR_DEPLOYMENT.md	⭐ START HERE - Complete API reference
DEPLOYMENT_GUIDE.md	Docker, Gunicorn, and production setup
API_CREDENTIALS.md	Your credentials and test examples

---

🔐 API Key

Your Generated Key:

castor_d167aa169b5e4219a66779e45fbaaefe

Use in header:

X-API-Key: castor_d167aa169b5e4219a66779e45fbaaefe

---

📡 Available Endpoints

Public Endpoints (No Auth)

• GET / - API documentation
• GET /api/health - Health check
• POST /api/generate-key - Generate new key

Protected Endpoints (Auth Required)

• POST /api/forecast - Get both ARIMA and LSTM forecast
• POST /api/forecast/arima - Get ARIMA forecast only
• POST /api/forecast/lstm - Get LSTM forecast only

---

💻 Integration Examples

JavaScript

const response = await fetch('http://127.0.0.1:5000/api/forecast', {
  method: 'POST',
  headers: {
    'X-API-Key': 'castor_d167aa169b5e4219a66779e45fbaaefe',
    'Content-Type': 'application/json'
  },
  body: JSON.stringify({
    product: 'Castor',
    start_date: '2025-12-01',
    end_date: '2026-01-31'
  })
});

const forecast = await response.json();

Python

import requests

response = requests.post(
  'http://127.0.0.1:5000/api/forecast',
  headers={'X-API-Key': 'castor_d167aa169b5e4219a66779e45fbaaefe'},
  json={'product': 'Castor', 'start_date': '2025-12-01', 'end_date': '2026-01-31'}
)

forecast = response.json()

---

🐳 Docker Deployment

FROM python:3.12-slim
WORKDIR /app
COPY requirements.txt .
RUN pip install -r requirements.txt
COPY api_production.py .
COPY daily_oilseeds_full_ml_dataset_2015_01_01_2025_12_02.csv .
COPY api_keys.json .
EXPOSE 5000
CMD ["python", "api_production.py"]

Run:

docker build -t castor-api .
docker run -p 5000:5000 castor-api

---

📊 Forecast Model Details

Model	Description	Trend
ARIMA	AutoRegressive Integrated Moving Average	Flat prediction
LSTM	Long Short-Term Memory Neural Network	Captures trends
Average	Mean of both models	Balanced forecast

---

✅ Testing

Run the test suite:

python test_api_production.py

Expected output:

✅ Health: PASSED
✅ Forecast: PASSED  
✅ ARIMA: PASSED
✅ All tests passed!

---

🛡️ Security Features

• ✅ API key authentication
• ✅ CORS support for web apps
• ✅ Request tracking and logging
• ✅ Error handling and validation
• ✅ Rate limiting ready

---

📈 Response Format

{
  "status": "success",
  "product": "Castor",
  "last_known_price": 3856.50,
  "forecast_period": {
    "start": "2025-12-01",
    "end": "2026-01-31",
    "days": 62
  },
  "forecast": [
    {
      "date": "2025-12-01",
      "arima_price": 3856.50,
      "lstm_price": 3856.54,
      "average_price": 3856.52
    }
  ],
  "timestamp": "2025-12-04T23:08:39"
}

---

🚀 Deployment Checklist

• Test API locally with test_api_production.py
• Verify API key generation works
• Check forecast endpoint with sample data
• Review DEPLOYMENT_GUIDE.md for production setup
• Choose deployment method (Docker/Gunicorn)
• Set up environment variables
• Configure HTTPS for production
• Set up monitoring and logging
• Share API credentials with app developers
• Document API usage for your team

---

📞 Support & Troubleshooting

Server won't start?

# Check Python version
python --version  # Should be 3.12+

# Reinstall dependencies
pip install flask flask-cors pandas numpy scikit-learn tensorflow statsmodels

# Check if port 5000 is available
netstat -ano | findstr :5000

API key not working?

# Verify key in api_keys.json
cat api_keys.json

# Generate new key
python -c "..."  # See DEPLOYMENT_GUIDE.md

Forecast data not loading?

• Ensure CSV file exists: daily_oilseeds_full_ml_dataset_2015_01_01_2025_12_02.csv
• Check file path in api_production.py
• Verify product name in CSV

---

📚 Documentation Links

1. Start Here: API_READY_FOR_DEPLOYMENT.md ⭐
2. Deployment: DEPLOYMENT_GUIDE.md
3. Credentials: API_CREDENTIALS.md
4. References: API_README.md

---

🎯 Next Steps

1. ✅ Review API_READY_FOR_DEPLOYMENT.md
2. ✅ Test with provided examples
3. ✅ Deploy using Docker or Gunicorn
4. ✅ Share API key with app developers
5. ✅ Monitor API usage

---

📊 Project Status

✅ API Server:       READY
✅ API Keys:         GENERATED  
✅ Documentation:    COMPLETE
✅ Test Suite:       READY
✅ Deployment:       READY

STATUS: 🚀 READY FOR PRODUCTION DEPLOYMENT

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Generated: December 4, 2025 Version: 1.0.0 API Key: castor_d167aa169b5e4219a66779e45fbaaefe Server: http://127.0.0.1:5000 | http://172.16.32.97:5000

251245cf (1st commit)