simpy

Discrete-event simulation models systems where entities interact and contend for shared resources over time. Use it for manufacturing, healthcare, telecommunications, transportation, and service operations requiring queueing and event-driven dynamics.

Model shared resources and queues using process-based Python generator functions. The framework provides Resource, Container, and Store components to manage entity contention, event scheduling, and synchronization within the simulation environment.

Yes, real-time simulations synchronized with wall-clock time are supported. This allows you to model and monitor systems where process execution and event-driven scheduling must match actual elapsed time rather than simulated time.

SimPy works for modeling network traffic and server contention through its resource management and event-driven scheduling. It handles bandwidth and server allocation by modeling entities competing for limited resources over time.

Monitor and collect data by utilizing the framework's comprehensive monitoring capabilities during simulation execution. Track resource utilization, entity wait times, and process interactions as the environment advances through scheduled events.

Python generator functions model process-based simulation but may face performance limitations with extremely large-scale systems. The framework is suited for modeling queueing, resource contention, and event-driven dynamics rather than continuous mathematical simulation.