# SQL Query Troubleshooting

## Common Issues

### Issue: `invalid value "09" for "AM"`

**Problem:** PostgreSQL's `HH12` format doesn't accept leading zeros like "09 AM". It expects "9 AM".

**Solution:** The SQL query has been updated to handle this by:
1. Normalizing times like "09 AM" to "9:00 AM" before parsing
2. Adding regex replacements to remove leading zeros
3. Handling edge cases for times without colons

**If you still see this error:**
- Check your data format in `OptionsFlow_monthly.CreatedTime`
- The query now handles: "09 AM", "9 AM", "09:00 AM", "9:00 AM", etc.
- If you have other formats, you may need to add additional normalization

### Issue: Python Service Unavailable

**This is normal if:**
- Python service is not running
- Python service is on a different port
- Network/firewall issues

**The system will automatically:**
- Fall back to SQL query
- Continue working normally
- Log the fallback for monitoring

**To fix:**
1. Start Python service: `cd backend/python_service && uvicorn main:app --port 8000`
2. Check `PYTHON_SERVICE_URL` in `.env` matches the service URL
3. Verify network connectivity

### Issue: Date Parsing Errors

**Common causes:**
- Invalid date formats in database
- Missing date/time values
- Timezone issues

**Solutions:**
- The query handles multiple date formats (YYYY-MM-DD, MM/DD/YYYY)
- Handles multiple time formats (12-hour with AM/PM, 24-hour)
- Returns NULL for invalid dates (won't crash)

## Data Validation

To check your data format:

```sql
SELECT 
  "CreatedDate",
  "CreatedTime",
  COUNT(*) as count
FROM "OptionsFlow_monthly"
GROUP BY "CreatedDate", "CreatedTime"
ORDER BY count DESC
LIMIT 20;
```

This will show you the most common date/time formats in your data.

## Testing SQL Query

Test the query directly in PostgreSQL:

```sql
-- Test with a small date range
SELECT * FROM (
  -- Your full query here with date parameters
) subquery
LIMIT 10;
```

## Performance

If the SQL query is slow:
1. Check indexes on `OptionsFlow_monthly`
2. Verify date range is reasonable
3. Consider using Python service (faster for complex processing)