This is your go-to for modeling discrete-event systems where entities compete for shared resources over time. Think customer queues, manufacturing lines, network traffic, or logistics systems. It's built on Python generators, so processes read naturally: yield to wait, request resources with context managers, and SimPy handles all the event scheduling. The framework gives you Resources for servers, Containers for bulk materials, and Stores for object pools, plus all the monitoring hooks you need to extract wait times and utilization stats. If your system has irregular events and resource contention rather than continuous differential equations, this is the right abstraction. The learning curve is gentle if you understand generators.
- skills.sh installs
- 265
- GitHub stars
- 33.2K
- last updated
- Aug 21, 2026
Install
$ npx -y skills add davila7/claude-code-templates --skill simpy --agent claude-codeInstalls into .claude/skills of the current project.
Files
SimPy - Discrete-Event Simulation
Overview
SimPy is a process-based discrete-event simulation framework based on standard Python. Use SimPy to model systems where entities (customers, vehicles, packets, etc.) interact with each other and compete for shared resources (servers, machines, bandwidth, etc.) over time.
Core capabilities:
- Process modeling using Python generator functions
- Shared resource management (servers, containers, stores)
- Event-driven scheduling and synchronization
- Real-time simulations synchronized with wall-clock time
- Comprehensive monitoring and data collection
When to Use This Skill
Use the SimPy skill when:
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- Repository
- github.com/davila7/claude-code-templates
- Categories
- Python, Marketing & SEO
- First seen
- Jun 3, 2026
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