# โœ… Castor Price Forecasting API - Ready for Deployment ## ๐ŸŽฏ Your API Key ``` castor_d167aa169b5e4219a66779e45fbaaefe ``` **Status:** โœ… ACTIVE AND RUNNING --- ## ๐Ÿš€ Server Information | Property | Value | |----------|-------| | **Server URL (Local)** | http://127.0.0.1:5000 | | **Server URL (Network)** | http://172.16.32.97:5000 | | **Port** | 5000 | | **Status** | โœ… Running | | **Environment** | Python 3.12 + Flask | --- ## ๐Ÿ“ Quick Start Examples ### 1. Health Check (No Auth Required) ```bash curl http://127.0.0.1:5000/api/health ``` **Response:** ```json { "status": "healthy", "timestamp": "2025-12-04T23:08:39", "service": "Castor Price Forecasting API" } ``` --- ### 2. Get Forecast (With Auth) ```bash curl -X POST http://127.0.0.1:5000/api/forecast \ -H "Content-Type: application/json" \ -H "X-API-Key: castor_d167aa169b5e4219a66779e45fbaaefe" \ -d '{ "product": "Castor", "start_date": "2025-12-01", "end_date": "2026-01-31" }' ``` --- ### 3. JavaScript Integration ```javascript const forecast = 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 data = await forecast.json(); console.log(data.forecast); ``` --- ### 4. Python Integration ```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_data = response.json() for item in forecast_data['forecast'][:5]: print(f"{item['date']}: ARIMA={item['arima_price']}, LSTM={item['lstm_price']}") ``` --- ## ๐Ÿ“š Available Endpoints | Endpoint | Method | Auth Required | Description | |----------|--------|---------------|-------------| | `/` | GET | No | API Documentation | | `/api/health` | GET | No | Health Check | | `/api/generate-key` | POST | No | Generate New API Key | | `/api/forecast` | POST | Yes | Get Combined Forecast | | `/api/forecast/arima` | POST | Yes | Get ARIMA Forecast Only | | `/api/forecast/lstm` | POST | Yes | Get LSTM Forecast Only | --- ## ๐Ÿ”ง Deployment Options ### Option 1: Docker (Recommended for Production) ```bash docker build -t castor-api . docker run -p 5000:5000 castor-api ``` ### Option 2: Gunicorn (Production WSGI) ```bash pip install gunicorn gunicorn -w 4 -b 0.0.0.0:5000 api_production:app ``` ### Option 3: Direct Python (Development) ```bash python api_production.py ``` --- ## ๐Ÿ“ฆ Files Included | File | Purpose | |------|---------| | `api_production.py` | Main API server | | `api_keys.json` | API key storage | | `DEPLOYMENT_GUIDE.md` | Complete deployment guide | | `API_CREDENTIALS.md` | Credentials reference | | `test_api_production.py` | API test suite | --- ## โš™๏ธ API Key Management ### View Keys ```bash cat api_keys.json ``` ### Generate New Key ```bash curl -X POST http://127.0.0.1:5000/api/generate-key \ -H "Content-Type: application/json" \ -d '{"name": "my_app"}' ``` ### Revoke Key Edit `api_keys.json` and set `"active": false` --- ## ๐Ÿ›ก๏ธ Security Checklist - โœ… API keys required for forecast endpoints - โœ… CORS enabled for cross-origin requests - โœ… Keys stored in JSON file (upgrade to database in production) - โœ… Request counting and tracking enabled - โœ… Error handling for invalid requests ### For Production: - [ ] Use HTTPS instead of HTTP - [ ] Implement database for key storage - [ ] Add rate limiting - [ ] Use environment variables for configuration - [ ] Implement request logging - [ ] Set up monitoring and alerts --- ## ๐Ÿงช Testing the API ```bash python test_api_production.py ``` Expected output: ``` โœ… Health: PASSED โœ… Forecast: PASSED โœ… ARIMA: PASSED โœ… All tests passed! API is ready for deployment. ``` --- ## ๐Ÿ“‹ API Response Example **Request:** ```json { "product": "Castor", "start_date": "2025-12-01", "end_date": "2025-12-03" } ``` **Response:** ```json { "status": "success", "product": "Castor", "last_known_price": 3856.50, "forecast_period": { "start": "2025-12-01", "end": "2025-12-03", "days": 3 }, "forecast": [ { "date": "2025-12-01", "arima_price": 3856.50, "lstm_price": 3856.54, "average_price": 3856.52 }, { "date": "2025-12-02", "arima_price": 3856.50, "lstm_price": 3856.89, "average_price": 3856.70 }, { "date": "2025-12-03", "arima_price": 3856.50, "lstm_price": 3857.24, "average_price": 3856.87 } ], "timestamp": "2025-12-04T23:08:39" } ``` --- ## ๐Ÿšจ Error Handling ### Unauthorized (401) ```json { "status": "error", "message": "Invalid or missing API key. Generate one using /api/generate-key" } ``` ### Not Found (404) ```json { "status": "error", "message": "Product not found in database" } ``` ### Bad Request (400) ```json { "status": "error", "message": "Invalid date format" } ``` --- ## ๐Ÿ’ก Tips for App Developers 1. **Cache Results**: Store forecasts locally to reduce API calls 2. **Handle Errors**: Always check `status` field in response 3. **Set Timeouts**: Use 30-second request timeout 4. **Store Key Securely**: Use environment variables, not hardcoded 5. **Monitor Usage**: Track requests_count in api_keys.json --- ## ๐Ÿ“ž Support For issues or questions: 1. Check `DEPLOYMENT_GUIDE.md` for detailed information 2. Review API response for error messages 3. Test with `test_api_production.py` 4. Enable debug logging in `api_production.py` --- ## โœจ Next Steps 1. **Test Locally**: Use the examples above to verify the API 2. **Integrate into App**: Use the provided code samples 3. **Deploy to Production**: Follow `DEPLOYMENT_GUIDE.md` 4. **Monitor**: Track API usage and performance --- **API Status: โœ… READY FOR PRODUCTION DEPLOYMENT** Generated: 2025-12-04 API Key: castor_d167aa169b5e4219a66779e45fbaaefe Server: Running on http://127.0.0.1:5000