timmy-config/wizards/allegro-primus/git_tools/example_parallel_issues.py

#!/usr/bin/env python3
"""
Example: Working on 3 Issues Simultaneously with Allegro-Primus

This example demonstrates how to use the AP Git Worktree Automation
to work on multiple GitHub issues in parallel using isolated worktrees.
"""

import json
import sys
from pathlib import Path

# Add tools to path
sys.path.insert(0, str(Path(__file__).parent.parent))

try:
    from git_tools import WorktreeManager, ParallelAgent, ParallelTask, IssueParallelizer, TaskRunner, TaskBatch
except ImportError:
    # Direct imports for development
    from worktree_manager import WorktreeManager
    from parallel_agent import ParallelAgent, ParallelTask, IssueParallelizer
    from task_runner import TaskRunner, TaskBatch


def example_1_basic_parallel():
    """
    Example 1: Basic parallel execution on 3 issues
    
    Scenario:
    - Issue #101: Fix authentication bug
    - Issue #102: Add user profile endpoint  
    - Issue #103: Update API documentation
    """
    print("\n" + "="*70)
    print("EXAMPLE 1: Basic Parallel Execution on 3 Issues")
    print("="*70)
    
    # Initialize parallel agent
    agent = ParallelAgent(max_workers=3)
    
    # Define tasks for each issue
    tasks = [
        ParallelTask(
            task_id="auth-fix-tests",
            issue_number="101",
            task_type="command",
            payload=["echo", "Running authentication tests for issue #101..."],
            dependencies=[],
            priority=1,
            auto_commit=False
        ),
        ParallelTask(
            task_id="api-endpoint-build",
            issue_number="102",
            task_type="command",
            payload=["echo", "Building user profile endpoint for issue #102..."],
            dependencies=[],
            priority=1,
            auto_commit=False
        ),
        ParallelTask(
            task_id="docs-generate",
            issue_number="103",
            task_type="command",
            payload=["echo", "Generating API docs for issue #103..."],
            dependencies=[],
            priority=2,  # Lower priority
            auto_commit=False
        )
    ]
    
    # Run all tasks in parallel
    print("\nLaunching parallel tasks...")
    results = agent.run_parallel(tasks)
    
    print(f"\n✓ Execution complete!")
    print(f"  Total tasks: {results['stats']['total_tasks']}")
    print(f"  Successful: {results['stats']['successful']}")
    print(f"  Failed: {results['stats']['failed']}")
    print(f"  Worktrees used: {results['stats']['worktrees_used']}")
    
    return results


def example_2_issue_parallelizer():
    """
    Example 2: Using IssueParallelizer for cleaner workflow
    
    Same 3 issues, but using the higher-level interface
    """
    print("\n" + "="*70)
    print("EXAMPLE 2: Using IssueParallelizer")
    print("="*70)
    
    # Create parallelizer
    parallelizer = IssueParallelizer()
    
    # Register issues
    print("\nRegistering issues...")
    parallelizer.register_issue("101", "Fix authentication bug")
    parallelizer.register_issue("102", "Add user profile endpoint")
    parallelizer.register_issue("103", "Update API documentation")
    
    # Add tasks to each issue
    print("Adding tasks...")
    parallelizer.add_task_to_issue(
        "101",
        ["bash", "-c", "echo 'Issue 101: Fixing auth...' && sleep 1 && echo 'Fixed!'"],
        task_id="auth-fix",
        timeout=60
    )
    
    parallelizer.add_task_to_issue(
        "102",
        ["bash", "-c", "echo 'Issue 102: Building API...' && sleep 1 && echo 'Built!'"],
        task_id="api-build",
        timeout=60
    )
    
    parallelizer.add_task_to_issue(
        "103",
        ["bash", "-c", "echo 'Issue 103: Updating docs...' && sleep 1 && echo 'Updated!'"],
        task_id="docs-update",
        timeout=60
    )
    
    # Run in parallel
    print("\nRunning all tasks in parallel...")
    results = parallelizer.run()
    
    print(f"\n✓ Complete!")
    for r in results['results']:
        status = "✓" if r['success'] else "✗"
        print(f"  {status} {r['task_id']}: {r['stdout'].strip()}")
    
    return results


def example_3_task_dependencies():
    """
    Example 3: Tasks with dependencies
    
    Issue #201: Database migration
      - Step 1: Create migration script
      - Step 2: Run migration (depends on step 1)
      - Step 3: Verify migration (depends on step 2)
    
    Issue #202: Add feature
      - Step 1: Implement feature (parallel with #201)
    """
    print("\n" + "="*70)
    print("EXAMPLE 3: Task Dependencies")
    print("="*70)
    
    agent = ParallelAgent(max_workers=3)
    
    tasks = [
        # Issue 201 - Sequential tasks with dependencies
        ParallelTask(
            task_id="db-create-migration",
            issue_number="201",
            task_type="command",
            payload=["echo", "Creating migration script..."],
            dependencies=[],
            priority=1
        ),
        ParallelTask(
            task_id="db-run-migration",
            issue_number="201",
            task_type="command",
            payload=["echo", "Running database migration..."],
            dependencies=["db-create-migration"],  # Wait for creation
            priority=1
        ),
        ParallelTask(
            task_id="db-verify",
            issue_number="201",
            task_type="command",
            payload=["echo", "Verifying migration..."],
            dependencies=["db-run-migration"],  # Wait for migration
            priority=1
        ),
        
        # Issue 202 - Parallel independent task
        ParallelTask(
            task_id="feature-implement",
            issue_number="202",
            task_type="command",
            payload=["echo", "Implementing new feature..."],
            dependencies=[],
            priority=1
        )
    ]
    
    print("\nTask dependency graph:")
    print("  db-create-migration → db-run-migration → db-verify")
    print("  feature-implement (parallel)")
    
    print("\nRunning tasks...")
    results = agent.run_parallel(tasks)
    
    print(f"\n✓ Execution complete!")
    print(f"  Total: {results['stats']['total_tasks']}")
    print(f"  Successful: {results['stats']['successful']}")
    
    return results


def example_4_script_execution():
    """
    Example 4: Running Python scripts in parallel worktrees
    
    Execute different analysis scripts on 3 issues simultaneously
    """
    print("\n" + "="*70)
    print("EXAMPLE 4: Python Script Execution in Parallel")
    print("="*70)
    
    agent = ParallelAgent(max_workers=3)
    
    # Python script for code analysis
    analysis_script = '''
import os
import json

print(f"Running in worktree: {os.environ.get('AP_WORKTREE', 'unknown')}")
print(f"Processing issue: {os.environ.get('AP_ISSUE', 'unknown')}")
print(f"Task ID: {os.environ.get('AP_TASK_ID', 'unknown')}")

# Simulate analysis
results = {
    "files_analyzed": 42,
    "issues_found": 3,
    "suggestions": ["Refactor module X", "Add tests for Y"]
}

print(json.dumps(results, indent=2))
'''
    
    # Python script for testing
    test_script = '''
import os
import time

print(f"Running tests for issue {os.environ.get('AP_ISSUE')}")

# Simulate test run
tests = ["test_auth.py", "test_api.py", "test_models.py"]
for test in tests:
    print(f"  ✓ {test} passed")
    time.sleep(0.1)

print("\\nAll tests passed!")
'''
    
    # Python script for documentation
    docs_script = '''
import os

print(f"Generating documentation for issue {os.environ.get('AP_ISSUE')}")
print("  - Processing docstrings...")
print("  - Building HTML...")
print("  - Done!")
'''
    
    tasks = [
        ParallelTask(
            task_id="analyze-issue-301",
            issue_number="301",
            task_type="script",
            payload=analysis_script,
            dependencies=[]
        ),
        ParallelTask(
            task_id="test-issue-302",
            issue_number="302",
            task_type="script",
            payload=test_script,
            dependencies=[]
        ),
        ParallelTask(
            task_id="docs-issue-303",
            issue_number="303",
            task_type="script",
            payload=docs_script,
            dependencies=[]
        )
    ]
    
    print("\nExecuting Python scripts in parallel worktrees...")
    results = agent.run_parallel(tasks)
    
    print(f"\n✓ Complete!")
    for r in results['results']:
        print(f"\n--- {r['task_id']} ---")
        print(r['stdout'])
    
    return results


def example_5_worktree_management():
    """
    Example 5: Worktree management workflow
    
    Demonstrate creating, listing, syncing, and cleaning worktrees
    """
    print("\n" + "="*70)
    print("EXAMPLE 5: Worktree Management Workflow")
    print("="*70)
    
    wm = WorktreeManager()
    
    # Step 1: Create worktrees for 3 issues
    print("\n1. Creating worktrees...")
    issues = [
        ("401", "Bug fix for login"),
        ("402", "Feature: dark mode"),
        ("403", "Refactor auth module")
    ]
    
    paths = {}
    for num, desc in issues:
        try:
            path = wm.create_worktree(num, desc)
            paths[num] = path
            print(f"   ✓ Issue #{num}: {path}")
        except Exception as e:
            print(f"   ✗ Issue #{num}: {e}")
    
    # Step 2: List all worktrees
    print("\n2. Active worktrees:")
    for wt in wm.list_worktrees():
        if not wt.is_main:
            print(f"   - {wt.branch} at {wt.path}")
    
    # Step 3: Get status of each
    print("\n3. Worktree status:")
    for num, _ in issues:
        status = wm.get_worktree_status(num)
        print(f"   Issue #{num}: branch={status.get('branch', 'N/A')}, "
              f"changes={status.get('has_uncommitted_changes', False)}")
    
    # Step 4: Clean up
    print("\n4. Cleaning up worktrees...")
    for num, _ in issues:
        if wm.remove_worktree(num):
            print(f"   ✓ Removed issue #{num}")
    
    return paths


def example_6_conflict_detection():
    """
    Example 6: Conflict detection between parallel worktrees
    
    Shows how the system detects when multiple issues modify the same files
    """
    print("\n" + "="*70)
    print("EXAMPLE 6: Conflict Detection")
    print("="*70)
    
    print("""
This example shows conflict detection capabilities:

Scenario:
  Issue #501 - Modifies src/auth.py and src/login.py
  Issue #502 - Modifies src/auth.py and src/api.py
  Issue #503 - Modifies src/utils.py only

The system will detect that Issues #501 and #502 both modify src/auth.py
and flag this as a potential conflict.
""")
    
    from parallel_agent import ConflictDetector
    
    wm = WorktreeManager()
    detector = ConflictDetector(wm)
    
    # Simulate file ownership registration
    print("\nRegistering file modifications...")
    detector.register_files("task-501", ["src/auth.py", "src/login.py"])
    print("  Task 501: src/auth.py, src/login.py")
    
    conflict = detector.register_files("task-502", ["src/auth.py", "src/api.py"])
    print("  Task 502: src/auth.py, src/api.py")
    if conflict:
        print(f"  ⚠ CONFLICT DETECTED: src/auth.py already owned by {conflict}")
    
    detector.register_files("task-503", ["src/utils.py"])
    print("  Task 503: src/utils.py (no conflict)")
    
    print("\n✓ Conflict detection active")


def save_example_tasks_json():
    """
    Create an example JSON file with tasks for CLI usage
    """
    tasks = [
        {
            "task_id": "fix-auth-101",
            "issue_number": "101",
            "task_type": "command",
            "payload": ["echo", "Fixing authentication..."],
            "dependencies": [],
            "priority": 1,
            "auto_commit": False,
            "timeout": 300
        },
        {
            "task_id": "add-api-102",
            "issue_number": "102",
            "task_type": "command",
            "payload": ["echo", "Adding API endpoint..."],
            "dependencies": [],
            "priority": 1,
            "auto_commit": False,
            "timeout": 300
        },
        {
            "task_id": "update-docs-103",
            "issue_number": "103",
            "task_type": "command",
            "payload": ["echo", "Updating documentation..."],
            "dependencies": [],
            "priority": 2,
            "auto_commit": False,
            "timeout": 300
        }
    ]
    
    output_path = Path(__file__).parent / "example_tasks.json"
    with open(output_path, 'w') as f:
        json.dump(tasks, f, indent=2)
    
    print(f"\n✓ Saved example tasks to {output_path}")
    print(f"\nUsage: python cli.py parallel run -f {output_path}")


def main():
    """Run all examples"""
    print("\n" + "="*70)
    print("ALLEGRO-PRIMUS GIT WORKTREE AUTOMATION")
    print("Example: Working on 3 Issues Simultaneously")
    print("="*70)
    
    try:
        # Run examples
        example_1_basic_parallel()
        example_2_issue_parallelizer()
        example_3_task_dependencies()
        example_4_script_execution()
        example_5_worktree_management()
        example_6_conflict_detection()
        
        # Save example JSON
        save_example_tasks_json()
        
        print("\n" + "="*70)
        print("All examples completed successfully!")
        print("="*70)
        print("""
CLI Usage:
  python cli.py worktree list              # List worktrees
  python cli.py worktree create 101        # Create worktree for issue 101
  python cli.py parallel run -f example_tasks.json
  python cli.py demo                       # Run full demo
        """)
        
    except Exception as e:
        print(f"\n✗ Error: {e}")
        import traceback
        traceback.print_exc()


if __name__ == "__main__":
    main()