simpy

SimPy - Discrete Event Simulation

SimPy allows you to model real-world processes as Python generators. Components in SimPy (like customers, cars, or data packets) are "processes" that interact with each other and with limited "resources" (like servers, parking spots, or bandwidth).

When to Use

• Modeling queuing systems (Bank tellers, call centers, hospital emergency rooms)
• Simulating supply chains and logistics (Warehouses, transport networks)
• Analyzing manufacturing processes (Assembly lines, machine maintenance)
• Network simulation (Packet routing, server load balancing)
• Project management (Task dependencies, resource allocation)
• Any system where "events" occur at specific points in time rather than continuously

Reference Documentation

Official docs: https://simpy.readthedocs.io/
GitHub: https://github.com/simpy/simpy
Search patterns: simpy.Environment, simpy.Resource, env.process, yield env.timeout

Core Principles

Virtual Time

SimPy uses an internal clock starting at 0. Time moves forward only when an event is processed. Between events, "nothing" happens, so simulating 100 years takes seconds if only a few events occur.

Processes as Generators

Processes are standard Python functions using yield. When a process yields an event, SimPy suspends it until that event occurs.

Resources

Three types of shared objects:

• Resource: Limited number of slots (e.g., a counter)
• Container: For bulk matter (e.g., a gas tank, RAM)
• Store: For distinct objects (e.g., a buffer of messages)

Quick Reference

Installation

pip install simpy

Standard Imports

import simpy
import random

Basic Pattern - A Simple Process

import simpy

def clock(env, name, tick):
    while True:
        print(f"{name} at {env.now}")
        # 'yield' tells SimPy to wait for this event
        yield env.timeout(tick)

# 1. Create Environment
env = simpy.Environment()

# 2. Add Process
env.process(clock(env, 'Fast', 0.5))
env.process(clock(env, 'Slow', 1.0))

# 3. Run for 2 units of virtual time
env.run(until=2.1)