#!/usr/bin/env python3"""Basic SimPy Simulation Template This template provides a starting point for building SimPy simulations.Customize the process functions and parameters for your specific use case.""" import simpyimport random  class SimulationConfig:    """Configuration parameters for the simulation."""     def __init__(self):        self.random_seed = 42        self.num_resources = 2        self.num_processes = 10        self.sim_time = 100        self.arrival_rate = 5.0  # Average time between arrivals        self.service_time_mean = 3.0  # Average service time        self.service_time_std = 1.0  # Service time standard deviation  class SimulationStats:    """Collect and report simulation statistics."""     def __init__(self):        self.arrival_times = []        self.service_start_times = []        self.departure_times = []        self.wait_times = []        self.service_times = []     def record_arrival(self, time):        self.arrival_times.append(time)     def record_service_start(self, time):        self.service_start_times.append(time)     def record_departure(self, time):        self.departure_times.append(time)     def record_wait_time(self, wait_time):        self.wait_times.append(wait_time)     def record_service_time(self, service_time):        self.service_times.append(service_time)     def report(self):        print("\n" + "=" * 50)        print("SIMULATION STATISTICS")        print("=" * 50)         if self.wait_times:            print(f"Total customers: {len(self.wait_times)}")            print(f"Average wait time: {sum(self.wait_times) / len(self.wait_times):.2f}")            print(f"Max wait time: {max(self.wait_times):.2f}")            print(f"Min wait time: {min(self.wait_times):.2f}")         if self.service_times:            print(f"Average service time: {sum(self.service_times) / len(self.service_times):.2f}")         if self.arrival_times and self.departure_times:            throughput = len(self.departure_times) / max(self.departure_times)            print(f"Throughput: {throughput:.2f} customers/time unit")         print("=" * 50)  def customer_process(env, name, resource, stats, config):    """    Simulate a customer process.     Args:        env: SimPy environment        name: Customer identifier        resource: Shared resource (e.g., server, machine)        stats: Statistics collector        config: Simulation configuration    """    # Record arrival    arrival_time = env.now    stats.record_arrival(arrival_time)    print(f"{name} arrived at {arrival_time:.2f}")     # Request resource    with resource.request() as request:        yield request         # Record service start and calculate wait time        service_start = env.now        wait_time = service_start - arrival_time        stats.record_service_start(service_start)        stats.record_wait_time(wait_time)        print(f"{name} started service at {service_start:.2f} (waited {wait_time:.2f})")         # Service time (normally distributed)        service_time = max(0.1, random.gauss(            config.service_time_mean,            config.service_time_std        ))        stats.record_service_time(service_time)         yield env.timeout(service_time)         # Record departure        departure_time = env.now        stats.record_departure(departure_time)        print(f"{name} departed at {departure_time:.2f}")  def customer_generator(env, resource, stats, config):    """    Generate customers arriving at random intervals.     Args:        env: SimPy environment        resource: Shared resource        stats: Statistics collector        config: Simulation configuration    """    customer_count = 0     while True:        # Wait for next customer arrival (exponential distribution)        inter_arrival_time = random.expovariate(1.0 / config.arrival_rate)        yield env.timeout(inter_arrival_time)         # Create new customer process        customer_count += 1        customer_name = f"Customer {customer_count}"        env.process(customer_process(env, customer_name, resource, stats, config))  def run_simulation(config):    """    Run the simulation with given configuration.     Args:        config: SimulationConfig object with simulation parameters     Returns:        SimulationStats object with collected statistics    """    # Set random seed for reproducibility    random.seed(config.random_seed)     # Create environment    env = simpy.Environment()     # Create shared resource    resource = simpy.Resource(env, capacity=config.num_resources)     # Create statistics collector    stats = SimulationStats()     # Start customer generator    env.process(customer_generator(env, resource, stats, config))     # Run simulation    print(f"Starting simulation for {config.sim_time} time units...")    print(f"Resources: {config.num_resources}")    print(f"Average arrival rate: {config.arrival_rate:.2f}")    print(f"Average service time: {config.service_time_mean:.2f}")    print("-" * 50)     env.run(until=config.sim_time)     return stats  def main():    """Main function to run the simulation."""    # Create configuration    config = SimulationConfig()     # Customize configuration if needed    config.num_resources = 2    config.sim_time = 50    config.arrival_rate = 2.0    config.service_time_mean = 3.0     # Run simulation    stats = run_simulation(config)     # Report statistics    stats.report()  if __name__ == "__main__":    main()