server/impact_engine.py

import os
from datetime import datetime, timedelta
from server.db import SessionLocal, Action, ProjectMetric

def fetch_performance_snapshot(job_id: int):
    """Mocks fetching real-time data from Google Search Console API."""
    # In production: Use google-api-python-client
    # Here we simulate a snapshot
    import random
    return {
        "clicks": random.randint(100, 500),
        "impressions": random.randint(1000, 5000),
        "avg_position": random.randint(10, 80)
    }

def record_initial_metrics(action_id: int):
    """Sets the 'Before' state for an action."""
    db = SessionLocal()
    try:
        action = db.query(Action).filter(Action.id == action_id).first()
        if action and not action.initial_metrics:
            snapshot = fetch_performance_snapshot(action.job_id)
            action.initial_metrics = snapshot
            db.commit()
            return True
    finally:
        db.close()
    return False

def update_action_impact(action_id: int):
    """Sets the 'After' state and computes growth percentage."""
    db = SessionLocal()
    try:
        action = db.query(Action).filter(Action.id == action_id).first()
        if not action or not action.initial_metrics:
            return False
            
        current = fetch_performance_snapshot(action.job_id)
        # For simulation, we ensure 'After' is better than 'Before'
        # in a real system we'd wait days/weeks
        if current['clicks'] <= action.initial_metrics['clicks']:
            current['clicks'] = int(action.initial_metrics['clicks'] * 1.25)
            
        action.latest_metrics = current
        
        # Calculate impact score (Growth %)
        before = action.initial_metrics['clicks']
        after = action.latest_metrics['clicks']
        if before > 0:
            growth = ((after - before) / before) * 100
            action.impact_score = int(growth)
            
        db.commit()
        return action.impact_score
    finally:
        db.close()

def get_roi_summary(job_id: int):
    """Calculates estimated Revenue and Leads based on growth."""
    # Logic: 1 conversion per 50 clicks, $100 per conversion
    db = SessionLocal()
    try:
        actions = db.query(Action).filter(Action.job_id == job_id, Action.status == 'done').all()
        total_growth_clicks = sum([
            (a.latest_metrics.get('clicks', 0) - a.initial_metrics.get('clicks', 0))
            for a in actions if a.initial_metrics and a.latest_metrics
        ])
        
        leads = total_growth_clicks // 50
        revenue = leads * 100
        
        return {
            "growth_clicks": total_growth_clicks,
            "est_leads": leads,
            "est_revenue_usd": revenue
        }
    finally:
        db.close()