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Retrieves comprehensive review statistics from a Neo4j graph database, including counts of review cycles, approval rates, and reviewer decisions.

Purpose

This function queries a Neo4j database to aggregate and calculate statistics about document review cycles and reviewer assignments. It provides metrics such as total reviews, pending/completed reviews, approval/rejection counts, and calculated approval rates for both review cycles and individual reviewer decisions. The function is designed to provide dashboard-level insights into the review system's performance and status.

Source Code

def get_review_statistics() -> Dict[str, Any]:
    """
    Get review statistics for the system.
    
    Returns:
        Dictionary with review statistics
    """
    try:
        query = """
        // Count all review cycles
        MATCH (r:ReviewCycle)
        WITH count(r) as total_reviews
        
        // Count pending and in-progress reviews
        OPTIONAL MATCH (r:ReviewCycle)
        WHERE r.status = 'PENDING' OR r.status = 'IN_PROGRESS'
        WITH count(r) as pending_reviews, total_reviews
        
        // Count completed reviews with approved decision
        OPTIONAL MATCH (r:ReviewCycle)
        WHERE r.status = 'COMPLETED' AND r.decision = 'APPROVED'
        WITH count(r) as approved_reviews, pending_reviews, total_reviews
        
        // Count completed reviews with rejected decision
        OPTIONAL MATCH (r:ReviewCycle)
        WHERE r.status = 'COMPLETED' AND r.decision = 'REJECTED'
        WITH count(r) as rejected_reviews, approved_reviews, pending_reviews, total_reviews
        
        // Count reviewer assignments with approved decisions
        OPTIONAL MATCH (ra:ReviewerAssignment)
        WHERE ra.status = 'COMPLETED' AND 
             (ra.decision = 'APPROVED' OR ra.decision = 'APPROVED_WITH_COMMENTS')
        WITH count(ra) as approved_decisions,
             rejected_reviews, approved_reviews, pending_reviews, total_reviews
        
        // Count reviewer assignments with rejected decisions
        OPTIONAL MATCH (ra:ReviewerAssignment)
        WHERE ra.status = 'COMPLETED' AND ra.decision = 'REJECTED'
        WITH count(ra) as rejected_decisions,
             approved_decisions, rejected_reviews, approved_reviews, 
             pending_reviews, total_reviews
        
        RETURN {
            total_reviews: total_reviews,
            pending_reviews: pending_reviews,
            completed_reviews: (approved_reviews + rejected_reviews),
            approved_reviews: approved_reviews,
            rejected_reviews: rejected_reviews,
            review_approval_rate: CASE 
                WHEN (approved_reviews + rejected_reviews) > 0 
                THEN 100.0 * approved_reviews / (approved_reviews + rejected_reviews)
                ELSE 0
                END,
            approved_decisions: approved_decisions,
            rejected_decisions: rejected_decisions,
            decision_approval_rate: CASE
                WHEN (approved_decisions + rejected_decisions) > 0
                THEN 100.0 * approved_decisions / (approved_decisions + rejected_decisions)
                ELSE 0
                END
        } as statistics
        """
        
        # Execute query
        result = db.run_query(query)
        
        if not result or len(result) == 0 or 'statistics' not in result[0]:
            # Return default statistics if query returned no results
            return {
                "success": True,
                "statistics": {
                    "total_reviews": 0,
                    "pending_reviews": 0,
                    "completed_reviews": 0,
                    "approved_reviews": 0,
                    "rejected_reviews": 0,
                    "review_approval_rate": 0,
                    "approved_decisions": 0,
                    "rejected_decisions": 0,
                    "decision_approval_rate": 0
                }
            }
        
        # Return statistics from query
        return {
            "success": True,
            "statistics": result[0].get('statistics', {})
        }
        
    except Exception as e:
        logger.error(f"Error getting review statistics: {e}")
        logger.error(traceback.format_exc())
        
        # Return error with default statistics
        return {
            "success": False,
            "statistics": {
                "total_reviews": 0,
                "pending_reviews": 0,
                "completed_reviews": 0,
                "approved_reviews": 0,
                "rejected_reviews": 0,
                "review_approval_rate": 0,
                "approved_decisions": 0,
                "rejected_decisions": 0,
                "decision_approval_rate": 0
            },
            "error": str(e)
        }

Return Value

Type: Dict[str, Any]

Returns a dictionary with structure: {'success': bool, 'statistics': dict, 'error': str (optional)}. The 'statistics' dictionary contains: 'total_reviews' (int), 'pending_reviews' (int), 'completed_reviews' (int), 'approved_reviews' (int), 'rejected_reviews' (int), 'review_approval_rate' (float, 0-100), 'approved_decisions' (int), 'rejected_decisions' (int), 'decision_approval_rate' (float, 0-100). On error, 'success' is False and 'error' contains the error message, with statistics defaulting to zeros.

Dependencies

• logging
• uuid
• os
• typing
• datetime
• traceback
• CDocs
• CDocs.db
• CDocs.config
• CDocs.models.document
• CDocs.models.review
• CDocs.models.user_extensions
• CDocs.utils
• CDocs.controllers
• CDocs.controllers.document_controller
• CDocs.controllers.share_controller
• neo4j

Required Imports

import logging
import traceback
from typing import Dict, Any
from CDocs import db
from CDocs.controllers import log_controller_action

Usage Example

from CDocs.controllers.review_controller import get_review_statistics

# Get review statistics
result = get_review_statistics()

if result['success']:
    stats = result['statistics']
    print(f"Total Reviews: {stats['total_reviews']}")
    print(f"Pending Reviews: {stats['pending_reviews']}")
    print(f"Approval Rate: {stats['review_approval_rate']:.2f}%")
    print(f"Decision Approval Rate: {stats['decision_approval_rate']:.2f}%")
else:
    print(f"Error: {result.get('error', 'Unknown error')}")

Best Practices

• Always check the 'success' field in the returned dictionary before accessing statistics
• The function returns default zero values for all statistics on error or when no data exists, ensuring consistent response structure
• The function is decorated with @log_controller_action which logs all invocations for audit purposes
• Approval rates are calculated as percentages (0-100) and return 0 when no completed reviews exist to avoid division by zero
• The function distinguishes between ReviewCycle-level approvals (overall review outcomes) and ReviewerAssignment-level decisions (individual reviewer decisions)
• Error handling is comprehensive - exceptions are logged with full stack traces while returning a safe default response
• The Cypher query uses OPTIONAL MATCH to handle cases where certain node types may not exist in the database

Tags

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