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Castor Price Forecasting API - Ready for Deployment
## π― Your API Key
```
castor_d167aa169b5e4219a66779e45fbaaefe
```
**Status:** β
ACTIVE AND RUNNING
---
## π 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** | β
Running |
| **Environment** | Python 3.12 + Flask |
---
## π 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']}")
```
---
## π 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 |
---
## π§ 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
```
---
## π¦ 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 |
---
## βοΈ 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`
---
## π‘οΈ Security Checklist
- β
API keys required for forecast endpoints
- β
CORS enabled for cross-origin requests
- β
Keys stored in JSON file (upgrade to database in production)
- β
Request counting and tracking enabled
- β
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
---
## π§ͺ Testing the API
```bash
python test_api_production.py
```
Expected output:
```
β
Health: PASSED
β
Forecast: PASSED
β
ARIMA: PASSED
β
All tests passed! API is ready for deployment.
```
---
## π 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"
}
```
---
## π¨ 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"
}
```
---
## π‘ 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
---
## π 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`
---
## β¨ 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: β
READY FOR PRODUCTION DEPLOYMENT**
Generated: 2025-12-04
API Key: castor_d167aa169b5e4219a66779e45fbaaefe
Server: Running on http://127.0.0.1:5000
|