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.
Fetches simpy from davila7/claude-code-templates and configures it for Cursor.
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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.
Capacity planning - Determining optimal resource levels for desired performance
System validation - Testing system behavior before implementation
Not suitable for:
Continuous simulations with fixed time steps (consider SciPy ODE solvers)
Independent processes without resource sharing
Pure mathematical optimization (consider SciPy optimize)
Quick Start
Basic Simulation Structure
import simpy
defprocess(env, name):"""A simple process that waits and prints."""print(f'{name} starting at {env.now}')yield env.timeout(5)print(f'{name} finishing at {env.now}')# Create environmentenv = simpy.Environment()# Start processesenv.process(process(env,'Process 1'))env.process(process(env,'Process 2'))# Run simulationenv.run(until=10)
Resource Usage Pattern
import simpy
defcustomer(env, name, resource):"""Customer requests resource, uses it, then releases."""with resource.request()as req:yield req # Wait for resourceprint(f'{name} got resource at {env.now}')yield env.timeout(3)# Use resourceprint(f'{name} released resource at {env.now}')env = simpy.Environment()server = simpy.Resource(env, capacity=1)env.process(customer(env,'Customer 1', server))env.process(customer(env,'Customer 2', server))env.run()
Core Concepts
1. Environment
The simulation environment manages time and schedules events.
import simpy
# Standard environment (runs as fast as possible)env = simpy.Environment(initial_time=0)# Real-time environment (synchronized with wall-clock)import simpy.rt
env_rt = simpy.rt.RealtimeEnvironment(factor=1.0)# Run simulationenv.run(until=100)# Run until time 100env.run()# Run until no events remain
2. Processes
Processes are defined using Python generator functions (functions with yield statements).
defmy_process(env, param1, param2):"""Process that yields events to pause execution."""print(f'Starting at {env.now}')# Wait for time to passyield env.timeout(5)print(f'Resumed at {env.now}')# Wait for another eventyield env.timeout(3)print(f'Done at {env.now}')return'result'# Start the processenv.process(my_process(env,'value1','value2'))
3. Events
Events are the fundamental mechanism for process synchronization. Processes yield events and resume when those events are triggered.
Common event types:
env.timeout(delay) - Wait for time to pass
resource.request() - Request a resource
env.event() - Create a custom event
env.process(func()) - Process as an event
event1 & event2 - Wait for all events (AllOf)
event1 | event2 - Wait for any event (AnyOf)
Resources
SimPy provides several resource types for different scenarios. For comprehensive details, see references/resources.md.
›Access to product documentation and roadmap tools (Jira, Notion, etc.)
›Understanding of product management frameworks (RICE, Jobs-to-be-Done, etc.)
›Stakeholder contact information and communication channels
Time Estimate
30-60 minutes to see productivity improvements
Steps
1Install product management skill
2Start with user story generation for known feature
3Progress to competitive analysis: research 2-3 competitors
4Use for roadmap prioritization: apply RICE/ICE scoring
5Draft stakeholder communications and refine based on feedback
6Build template library for recurring PM tasks
7Share effective prompts with product team
Common Pitfalls
⚠Not validating competitive research—verify facts before sharing
⚠Accepting user stories without involving engineering team
⚠Over-relying on frameworks without qualitative judgment
⚠Not customizing outputs to company culture and communication style
⚠Skipping stakeholder validation of generated requirements
Best Practices
✓ Do
+Validate research and competitive analysis with real data
+Collaborate with engineering when generating technical requirements
+Customize frameworks and templates to your company context
+Use skill for first drafts, refine with stakeholder input
+Document successful prompt patterns for PM tasks
+Combine AI efficiency with human judgment and intuition
✗ Don't
−Don't publish competitive analysis without fact-checking
−Don't finalize user stories without engineering review
−Don't make prioritization decisions solely on AI scoring
−Don't skip customer validation of generated requirements
−Don't ignore company-specific context and culture
💡 Pro Tips
★Provide context: company goals, constraints, customer feedback
★Ask for alternatives: 'Show 3 ways to prioritize this roadmap'
★Request stakeholder-specific formatting: 'Executive summary vs. engineering spec'
★Use skill for 70% generation + 30% customization to company needs
When to Use This
✓ Use when
Use for user story writing, competitive research, roadmap prioritization, stakeholder communication, and PRD drafting. Best for reducing repetitive documentation and research work.
✗ Avoid when
Avoid for strategic product vision (requires deep customer empathy), pricing decisions (needs market and financial expertise), or when face-to-face customer discovery is more valuable than speed.
Learning Path
1Basic: user stories, feature specs, status updates
