# Test Data Population Script

This script generates and inserts 30 random PPR (Prior Permission Required) records into the database for testing purposes.

## Features

- **30 Random PPR Records**: Generates diverse test data with various aircraft, airports, and flight details
- **Real Aircraft Data**: Uses actual aircraft registration data from the `aircraft_data.csv` file
- **Real Airport Data**: Uses actual airport ICAO codes from the `airports_data_clean.csv` file
- **Random Status Distribution**: Includes NEW, CONFIRMED, LANDED, and DEPARTED statuses
- **Realistic Timestamps**: Generates ETA/ETD times with 15-minute intervals
- **Optional Fields**: Randomly includes email, phone, notes, and departure details
- **Duplicate Aircraft**: Some aircraft registrations appear multiple times for realistic testing

## Usage

### Prerequisites
- Database must be running and accessible
- Python environment with required dependencies installed
- CSV data files (`aircraft_data.csv` and `airports_data_clean.csv`) in the parent directory

### Running the Script

1. **Using the convenience script** (recommended):
   ```bash
   cd /home/jamesp/docker/pprdev/nextgen
   ./populate_test_data.sh
   ```

2. **From within the Docker container**:
   ```bash
   docker exec -it ppr-backend bash
   cd /app
   python populate_test_data.py
   ```

3. **From host machine** (if database is accessible):
   ```bash
   cd /home/jamesp/docker/pprdev/nextgen/backend
   python populate_test_data.py
   ```

## What Gets Generated

Each PPR record includes:
- **Aircraft**: Random registration, type, and callsign from real aircraft data
- **Route**: Random arrival airport (from Swansea), optional departure airport
- **Times**: ETA between 6 AM - 8 PM, ETD 1-4 hours later (if departing)
- **Passengers**: 1-4 POB for arrival, optional for departure
- **Contact**: Optional email and phone (70% and 50% chance respectively)
- **Fuel**: Random fuel type (100LL, JET A1, FULL) or none
- **Notes**: Optional flight purpose notes (various scenarios)
- **Status**: Random status distribution (NEW/CONFIRMED/LANDED/DEPARTED)
- **Timestamps**: Random submission dates within last 30 days
- **Public Token**: Auto-generated for edit/cancel functionality

### Aircraft Distribution
- Uses real aircraft registration data from `aircraft_data.csv`
- Includes various aircraft types (C172, PA28, BE36, R44, etc.)
- Some aircraft appear multiple times for realistic duplication

### Airport Distribution
- Uses real ICAO airport codes from `airports_data_clean.csv`
- Arrival airports are distributed globally
- Departure airports (when included) are different from arrival airports

### Data Quality Notes

- **Realistic Distribution**: Aircraft and airports are selected from actual aviation data
- **Time Constraints**: All times are within reasonable operating hours (6 AM - 8 PM)
- **Status Balance**: Roughly equal distribution across different PPR statuses
- **Contact Info**: Realistic email patterns and UK phone numbers
- **Flight Logic**: Departures only occur when a departure airport is specified

## Assumptions

- Database schema matches the PPRRecord model in `app/models/ppr.py`
- CSV files are present and properly formatted
- Database connection uses settings from `app/core/config.py`
- All required dependencies are installed in the Python environment

### Sample Output

```
Loading aircraft and airport data...
Loaded 520000 aircraft records
Loaded 43209 airport records
Generating and inserting 30 test PPR records...
Generated 10 records...
Generated 20 records...
Generated 30 records...
✅ Successfully inserted 30 test PPR records!
Total PPR records in database: 42

Status breakdown:
  NEW: 8
  CONFIRMED: 7
  LANDED: 9
  DEPARTED: 6
```

## Safety Notes

- **Non-destructive**: Only adds new records, doesn't modify existing data
- **Test Data Only**: All generated data is clearly identifiable as test data
- **Easy Cleanup**: Can be easily removed with SQL queries if needed

## Current Status ✅

The script is working correctly! It has successfully generated and inserted test data. As of the latest run:

- **Total PPR records in database**: 93
- **Status breakdown**:
  - NEW: 19
  - CONFIRMED: 22  
  - CANCELED: 1
  - LANDED: 35
  - DEPARTED: 16

## Troubleshooting

- **Database Connection**: Ensure the database container is running and accessible
- **CSV Files**: The script uses fallback data when CSV files aren't found (which is normal in containerized environments)
- **Dependencies**: Ensure all Python requirements are installed
- **Permissions**: Script needs database write permissions

## Recent Fixes

- ✅ Fixed SQLAlchemy 2.0 `func.count()` import issue
- ✅ Script now runs successfully and provides status breakdown
- ✅ Uses fallback aircraft/airport data when CSV files aren't accessible

## Cleanup (if needed)

To remove all test data:
```sql
DELETE FROM submitted WHERE submitted_dt > '2025-01-01'; -- Adjust date as needed
```