Panzer III Serials Generator/CSV File

import pandas as pd
import random

# Define Panzer III variants with their production numbers
variants_production = {
    'Ausf. A': 10,
    'Ausf. B': 10,
    'Ausf. C': 15,
    'Ausf. D': 75,
    'Ausf. E': 96,
    'Ausf. F': 450,
    'Ausf. G': 594,
    'Ausf. H': 286,
    'Ausf. J': 1521,
    'Ausf. L': 1470,
    'Ausf. M': 517,
    'Ausf. N': 614,
    'Command D': 30,
    'Command E': 45,
    'Command H': 175,
    'Command J': 81,
    'Command K': 50,
    'Flame Tank': 100
}

# Total production limit
total_production_limit = 5774

# Define the production periods with their overlaps
production_periods = {
    'Ausf. A': ('1937-01', '1937-12'),
    'Ausf. B': ('1937-01', '1937-12'),
    'Ausf. C': ('1937-07', '1938-06'),
    'Ausf. D': ('1938-01', '1940-12'),
    'Ausf. E': ('1939-01', '1941-12'),
    'Ausf. F': ('1939-06', '1941-12'),
    'Ausf. G': ('1940-06', '1943-06'),
    'Ausf. H': ('1941-06', '1943-12'),
    'Ausf. J': ('1942-01', '1943-12'),
    'Ausf. L': ('1941-01', '1942-12'),
    'Ausf. M': ('1942-01', '1943-12'),
    'Ausf. N': ('1942-01', '1943-12'),
    'Command D': ('1938-01', '1939-12'),
    'Command E': ('1939-01', '1940-12'),
    'Command H': ('1940-01', '1941-12'),
    'Command J': ('1941-01', '1942-12'),
    'Command K': ('1942-01', '1943-12'),
    'Flame Tank': ('1943-01', '1943-12')
}

def generate_serial_numbers(start_serial_number, total_produced, limit):
    """Generate a range of unique serial numbers based on total production."""
    end_serial_number = min(start_serial_number + total_produced - 1, limit)
    if end_serial_number < start_serial_number:
        return []
    num_serials = min(4, end_serial_number - start_serial_number + 1)
    return random.sample(range(start_serial_number, end_serial_number + 1), num_serials)

# Create an empty DataFrame to hold the serial numbers
serials_data = {
    'Variant': [],
    'Serial Numbers': []
}

# Initialize the starting serial number
current_serial_number = 1

for variant, total_produced in variants_production.items():
    # Adjust total_produced if it exceeds the remaining production limit
    if current_serial_number + total_produced - 1 > total_production_limit:
        total_produced = total_production_limit - current_serial_number + 1

    # Generate serial numbers for the current variant
    if total_produced > 0:
        serial_numbers = generate_serial_numbers(current_serial_number, total_produced, total_production_limit)
    else:
        # If total_produced is 0 or the range is too small, generate 4 random serial numbers within the remaining limit
        remaining_range = range(current_serial_number, total_production_limit + 1)
        if len(remaining_range) < 4:
            serial_numbers = list(remaining_range)[:4]
        else:
            serial_numbers = random.sample(remaining_range, 4)

    # Handle case when there are fewer than 4 available numbers
    if len(serial_numbers) < 4:
        additional_numbers = random.sample(range(1, total_production_limit + 1), 4 - len(serial_numbers))
        serial_numbers.extend(additional_numbers)

    # Store the serial numbers in the DataFrame
    serials_data['Variant'].append(variant)
    serials_data['Serial Numbers'].append(serial_numbers)

    # Update the current serial number to the next available number
    current_serial_number += total_produced

# Create a DataFrame to hold the serial numbers
serials_df = pd.DataFrame(serials_data)

# Save the DataFrame to a CSV file
serials_df.to_csv('panzer_iii_serials.csv', index=False)

# Print the DataFrame
print(serials_df)