simpy

Build and run discrete-event simulations with SimPy in Python.

13|3|Updated Jun 10, 2026
One-click install
npx skills add https://github.com/tassiovale/claude-code-kit --skill simpy-tassiovale
Or copy as Structured Prompt for Agent▼
Please help me install this Agent Skill.
Skill: simpy
Source: https://github.com/tassiovale/claude-code-kit/tree/main/skills/simpy
Command: npx skills add https://github.com/tassiovale/claude-code-kit --skill simpy-tassiovale

SYSTEM DOCUMENTATION & REQUIREMENTS

💡 This Skill requires simpy, and includes scripts (resource) and references (resource) components.

What problem does it solve?

SimPy provides a framework to build process-based discrete-event simulations using Python, helping to model complex systems with events and interactions over time.

Core Features & Use Cases

  • Process-Based Simulation: Model systems where entities interact with shared resources over time.

  • Event-Driven Scheduling: Handle time-based events and resource allocation dynamically.

  • Real-Time Simulation: Run simulations in real-time to mimic physical behavior.

  • Use Case: Model the scheduling of manufacturing machines to determine the most efficient use of resources and production speed.

Quick Start

Create a new SimPy environment and add a process, a resource, and events.

Frequently Asked Questions about simpy

High-intent search queries and answers about installing and using this skill.

FAQPage Schema
How do I build a discrete-event simulation in Python?▼

You can build a discrete-event simulation in Python by creating a SimPy environment, adding processes using standard Python generator functions, and defining events for dynamic time-based scheduling. This Skill facilitates constructing and executing such process-based simulations.

What is process-based simulation and when should I use it?▼

Process-based simulation models complex systems where entities interact with shared resources over time. You should use this discrete-event technique for system analysis like modeling manufacturing machine scheduling to determine the most efficient use of resources and production speed.

How do I model shared resource allocation dynamically with SimPy?▼

To model shared resource allocation dynamically with SimPy, you define Python generator functions that request resources from the simulation environment. The event-driven scheduling handles resource allocation dynamically as entities interact over time.

Can I run real-time simulations using Python's SimPy library?▼

Yes, you can run real-time simulations using Python's SimPy library. This Skill supports real-time simulation execution to mimic physical behavior, allowing your discrete-event models to operate and schedule events in real-time.

Do I need Python generator functions to use SimPy for event-driven execution?▼

Yes, you need Python generator functions to use SimPy for event-driven execution. This Skill assumes generator functions and event-driven execution as standard features for constructing and running process-based discrete-event simulations within the Python environment.

What is the best way to simulate manufacturing machine scheduling in Python?▼

The best way to simulate manufacturing machine scheduling in Python is using process-based discrete-event simulation. This approach models the scheduling of machines to determine the most efficient use of resources and production speed through dynamic event-driven interactions.