Rhylthyme Examples

A comprehensive collection of example programs and environments for the Rhylthyme real-time scheduling system.

Overview

This repository contains working examples of Rhylthyme programs and environments that demonstrate various features and use cases. All examples are validated against the Rhylthyme schema and can be run with the rhylthyme-cli-runner.

Quick Start

1. Install the CLI runner:

   pip install rhylthyme-cli-runner

2. Validate an example:

   rhylthyme validate programs/breakfast_schedule.json

3. Run an example:

   rhylthyme run programs/breakfast_schedule.json

Program Examples

🍳 Kitchen & Food Service

Basic Examples

• breakfast_schedule.json - Simple breakfast preparation with eggs, bacon, and toast
• breakfast_manual_triggers.json - Breakfast with manual step completion
• breakfast_with_buffers.json - Breakfast with setup and cleanup buffers
• breakfast_from_tracks.json - Breakfast using track templates
• breakfast_with_environment.json - Breakfast referencing an environment file

Restaurant & Commercial

• restaurant_breakfast.json - Restaurant breakfast service
• commercial_kitchen_service.json - Commercial kitchen operations
• kitchen_actors_example.json - Kitchen with multiple actor types

Bakery & Artisan

• bakery_program_example.json - Commercial bakery operations
• artisan_bread_production.json - Artisan bread making process

🧪 Laboratory & Research

Academic & Research

• lab_experiment.json - Basic laboratory experiment
• cell_culture_experiment.json - Cell culture procedures
• protein_lysate_immunoblotting.json - Protein analysis workflow
• rat_psychopharmacology.json - Animal research protocol
• drug_screening_from_tracks.json - Drug screening using track templates

Industry & Pharma

• biotech-company-lab.json - Biotech company laboratory environment
• small-academic-lab.json - Small academic laboratory environment
• large_pharma_lab.json - Large pharmaceutical laboratory environment

✈️ Aviation & Transportation

• airport_program_example.json - Airport operations and scheduling
• airport_batch_example.json - Batch processing for airport operations
• go_around_example.yaml - Aircraft go-around procedures

🎭 Events & Entertainment

• academy_awards_ceremony.json - Complex event scheduling for awards ceremony

🔧 Advanced Features

Resource Management

• resource_contention_example.yaml - Demonstrates resource contention and optimization
• multi_resource_example.json - Multiple resource types and constraints
• fractional_resource_example.json - Fractional resource usage
• test_overutilization.json - Resource overutilization scenarios

Timing & Triggers

• time_format_stagger_example.yaml - Time format variations and staggering
• flexible_time_format_example.yaml - Flexible time format usage
• staggered_batch_example.yaml - Batch processing with staggered starts
• test_offset_example.json - Offset-based timing
• simple_trigger_test.json - Basic trigger testing
• simple_on_test.json - Simple trigger conditions

Code Execution

• code_execution_example.yaml - Python code execution in steps
• simplified_code_example.yaml - Simplified code execution
• variable_substitution_example.yaml - Variable substitution in code

Optimization & Planning

• optimal_duration_example.yaml - Optimal duration calculations
• test_flex_auto_plan.json - Flexible auto-planning features
• comprehensive_example.json - Comprehensive feature demonstration
• comprehensive_manual_demo.json - Manual control demonstration
• manual_controls_demo.json - Manual step controls

Environment Examples

🏠 Home & Residential

• home-kitchen.json - Standard home kitchen with 2 cooks
• restaurant.json - Restaurant environment

🏢 Commercial & Industrial

• commercial-kitchen.json - Commercial kitchen with professional staff
• bakery.json - Bakery environment
• artisan-bakery-detailed.json - Detailed artisan bakery setup

🧪 Laboratory & Research

• laboratory.json - Basic laboratory environment
• biotech-company-lab.json - Biotech company laboratory
• small-academic-lab.json - Small academic laboratory
• large_pharma_lab.json - Large pharmaceutical laboratory

✈️ Transportation

• airport.json - Airport operations environment

Example Categories

By Complexity

Beginner Examples

• breakfast_schedule.json - Simple sequential cooking
• simple_trigger_test.json - Basic triggers
• lab_experiment.json - Basic laboratory workflow

Intermediate Examples

• breakfast_with_buffers.json - Buffers and cleanup
• resource_contention_example.yaml - Resource management
• kitchen_actors_example.json - Multiple actor types

Advanced Examples

• academy_awards_ceremony.json - Complex event scheduling
• rat_psychopharmacology.json - Complex research protocols
• comprehensive_example.json - All features combined

By Environment Type

Kitchen Environments

• Home kitchen examples
• Restaurant examples
• Commercial kitchen examples
• Bakery examples

Laboratory Environments

• Academic lab examples
• Industry lab examples
• Research protocol examples

Specialized Environments

• Airport operations
• Event management
• Manufacturing processes

Current Status

✅ Working Examples

Most program examples validate successfully against the schema:

• breakfast_schedule.json - ✅ Validates correctly
• lab_experiment.json - ✅ Validates correctly
• restaurant_breakfast.json - ✅ Validates correctly
• And many more...

⚠️ Environment Files

The environment files in the environments/ directory have some validation issues:

• Missing required tasks for specific environment types
• Resource constraint mismatches
• These issues prevent some programs from running with environment references

🔧 Recommended Usage

1. Start with validation: Use rhylthyme validate to check program files
2. Focus on programs: Most program examples work well for learning
3. Environment info: Use rhylthyme environment-info to learn about environment types
4. Fix environments: Environment files can be corrected to resolve validation issues

Running Examples

Basic Validation

# Validate a single program
rhylthyme validate programs/breakfast_schedule.json

# Validate with verbose output
rhylthyme validate programs/breakfast_schedule.json --verbose

Running Programs

# Note: Some programs may require properly configured environments
# The environment files in this repository may have validation issues

# Run with interactive UI (if environment is properly configured)
rhylthyme run programs/breakfast_schedule.json

# Run with automatic start (no manual trigger needed)
rhylthyme run programs/breakfast_schedule.json --auto-start

# Run with time scaling (2x faster)
rhylthyme run programs/breakfast_schedule.json --time-scale 2.0

Using Environments

# Run without environment (uses embedded resource constraints)
rhylthyme run programs/breakfast_schedule.json

# Run with automatic start (no manual trigger needed)
rhylthyme run programs/breakfast_schedule.json --auto-start

# List available environments (if any are properly configured)
rhylthyme environments

# Get environment information for a specific type
rhylthyme environment-info kitchen

# Validate environment files (may show validation errors)
rhylthyme validate-environments --environments-dir environments

Optimization

# Create optimized version
rhylthyme plan programs/resource_contention_example.yaml optimized_program.json

# Run the optimized version
rhylthyme run optimized_program.json

Example Features Demonstrated

Core Features

• ✅ Sequential Steps - Basic step-by-step execution
• ✅ Parallel Tracks - Multiple concurrent workflows
• ✅ Resource Constraints - Limited resource management
• ✅ Manual Triggers - Human-controlled step completion
• ✅ Variable Durations - Flexible timing with min/max ranges

Advanced Features

• ✅ Buffer Times - Setup and cleanup periods
• ✅ Code Execution - Python code in steps
• ✅ Track Templates - Reusable track definitions
• ✅ Environment References - External environment files
• ✅ Fractional Resources - Partial resource usage
• ✅ Batch Processing - Multiple iterations
• ✅ Time Offsets - Delayed starts
• ✅ Complex Triggers - Multiple trigger conditions

Environment Features

• ✅ Actor Types - Different types of workers
• ✅ Qualified Actors - Skill-based resource allocation
• ✅ Resource Constraints - Equipment and space limits
• ✅ Metadata - Additional environment information

Contributing

To add new examples:

1. Create your program file in the programs/ directory
2. Validate it using rhylthyme validate your_program.json
3. Test it using rhylthyme run your_program.json
4. Add documentation in this README
5. Submit a pull request

Example Guidelines

• Use descriptive names that indicate the feature being demonstrated
• Include comments in the JSON/YAML for clarity
• Keep examples focused on specific features
• Ensure all examples validate successfully
• Test that examples run without errors

Schema Reference

All examples conform to the Rhylthyme Schema version 0.1.0-alpha.

Related Repositories

• rhylthyme-spec - Schema definitions and specifications
• rhylthyme-cli-runner - Command-line interface and runner
• rhylthyme-web - Web-based interface

License

Apache License 2.0