6cb51c270c
- Remove excessive completion checkmarks and status markers throughout document - Consolidate redundant sections on completed features - Streamline executive summary and current status sections - Focus content on upcoming quick wins and active tasks - Remove duplicate phase completion listings - Clean up success metrics and KPI sections - Maintain essential planning information while reducing noise
117 lines
3.9 KiB
Python
117 lines
3.9 KiB
Python
#!/usr/bin/env python3
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"""
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Enhanced Planning Document Analyzer
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Analyzes planning documents to identify completed tasks
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"""
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import os
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import re
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import json
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from pathlib import Path
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def analyze_planning_document(file_path):
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"""Analyze a single planning document"""
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tasks = []
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try:
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with open(file_path, 'r', encoding='utf-8') as f:
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content = f.read()
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# Find completed task patterns
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completion_patterns = [
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r'✅\s*\*\*COMPLETE\*\*:?\s*(.+)',
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r'✅\s*\*\*IMPLEMENTED\*\*:?\s*(.+)',
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r'✅\s*\*\*OPERATIONAL\*\*:?\s*(.+)',
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r'✅\s*\*\*DEPLOYED\*\*:?\s*(.+)',
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r'✅\s*\*\*WORKING\*\*:?\s*(.+)',
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r'✅\s*\*\*FUNCTIONAL\*\*:?\s*(.+)',
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r'✅\s*\*\*ACHIEVED\*\*:?\s*(.+)',
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r'✅\s*COMPLETE\s*:?\s*(.+)',
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r'✅\s*IMPLEMENTED\s*:?\s*(.+)',
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r'✅\s*OPERATIONAL\s*:?\s*(.+)',
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r'✅\s*DEPLOYED\s*:?\s*(.+)',
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r'✅\s*WORKING\s*:?\s*(.+)',
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r'✅\s*FUNCTIONAL\s*:?\s*(.+)',
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r'✅\s*ACHIEVED\s*:?\s*(.+)',
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r'✅\s*COMPLETE:\s*(.+)',
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r'✅\s*IMPLEMENTED:\s*(.+)',
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r'✅\s*OPERATIONAL:\s*(.+)',
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r'✅\s*DEPLOYED:\s*(.+)',
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r'✅\s*WORKING:\s*(.+)',
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r'✅\s*FUNCTIONAL:\s*(.+)',
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r'✅\s*ACHIEVED:\s*(.+)',
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r'✅\s*\*\*COMPLETE\*\*:\s*(.+)',
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r'✅\s*\*\*IMPLEMENTED\*\*:\s*(.+)',
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r'✅\s*\*\*OPERATIONAL\*\*:\s*(.+)',
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r'✅\s*\*\*DEPLOYED\*\*:\s*(.+)',
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r'✅\s*\*\*WORKING\*\*:\s*(.+)',
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r'✅\s*\*\*FUNCTIONAL\*\*:\s*(.+)',
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r'✅\s*\*\*ACHIEVED\*\*:\s*(.+)'
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]
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lines = content.split('\n')
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for i, line in enumerate(lines):
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for pattern in completion_patterns:
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match = re.search(pattern, line, re.IGNORECASE)
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if match:
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task_description = match.group(1).strip()
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tasks.append({
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'line_number': i + 1,
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'line_content': line.strip(),
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'task_description': task_description,
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'status': 'completed',
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'file_path': str(file_path),
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'pattern_used': pattern
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})
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return {
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'file_path': str(file_path),
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'total_lines': len(lines),
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'completed_tasks': tasks,
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'completed_task_count': len(tasks)
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}
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except Exception as e:
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print(f"Error analyzing {file_path}: {e}")
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return {
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'file_path': str(file_path),
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'error': str(e),
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'completed_tasks': [],
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'completed_task_count': 0
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}
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def analyze_all_planning_documents(planning_dir):
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"""Analyze all planning documents"""
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results = []
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planning_path = Path(planning_dir)
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# Find all markdown files
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for md_file in planning_path.rglob('*.md'):
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if md_file.is_file():
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result = analyze_planning_document(md_file)
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results.append(result)
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return results
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if __name__ == "__main__":
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import sys
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planning_dir = sys.argv[1] if len(sys.argv) > 1 else '/opt/aitbc/docs/10_plan'
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output_file = sys.argv[2] if len(sys.argv) > 2 else 'analysis_results.json'
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results = analyze_all_planning_documents(planning_dir)
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# Save results
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with open(output_file, 'w') as f:
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json.dump(results, f, indent=2)
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# Print summary
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total_completed = sum(r.get('completed_task_count', 0) for r in results)
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print(f"Analyzed {len(results)} planning documents")
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print(f"Found {total_completed} completed tasks")
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for result in results:
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if result.get('completed_task_count', 0) > 0:
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print(f" {result['file_path']}: {result['completed_task_count']} completed tasks")
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