Best Mixmax Phone Validation API & Email Verification Integration 2025

import requests
import json
import asyncio
from typing import Dict, List, Optional
from dataclasses import dataclass, asdict
from datetime import datetime

@dataclass
class SmartMixmaxContact:
    email: str
    first_name: Optional[str] = None
    last_name: Optional[str] = None
    position: Optional[str] = None
    company: Optional[str] = None
    domain: Optional[str] = None
    phone: Optional[str] = None
    linkedin_url: Optional[str] = None
    email_validation: Optional[Dict] = None
    phone_validation: Optional[Dict] = None
    engagement_intelligence: Optional[Dict] = None
    tracking_optimization: Optional[Dict] = None
    engagement_score: int = 0
    follow_up_priority: str = "medium"
    best_engagement_time: Optional[str] = None
    productivity_readiness: str = "pending"
    mixmax_optimization: Optional[Dict] = None
    enhancement_timestamp: str = ""

class Mixmax1lookupIntegration:
    def __init__(self, mixmax_api_key: str, lookup_api_key: str):
        self.mixmax_api_key = mixmax_api_key
        self.lookup_api_key = lookup_api_key
        self.mixmax_base_url = "https://api.mixmax.com/v1"
        self.lookup_base_url = "https://api.1lookup.app/v1"
    
    async def optimize_email_tracking(self, contact_list: List[Dict]) -> Dict:
        """
        Optimize Mixmax email tracking with comprehensive contact intelligence
        """
        try:
            # Step 1: Enhance all contacts with productivity intelligence
            enhanced_contacts = await self._bulk_enhance_for_productivity(contact_list)
            
            # Step 2: Generate tracking optimization strategies
            tracking_strategies = await self._generate_tracking_strategies(enhanced_contacts)
            
            # Step 3: Create smart follow-up recommendations
            follow_up_recommendations = self._generate_smart_follow_ups(enhanced_contacts)
            
            # Step 4: Implement engagement optimization
            engagement_optimization = await self._optimize_engagement_timing(enhanced_contacts)
            
            return {
                "total_contacts": len(contact_list),
                "enhanced_contacts": len(enhanced_contacts),
                "productivity_stats": self._calculate_productivity_stats(enhanced_contacts),
                "tracking_strategies": tracking_strategies,
                "follow_up_recommendations": follow_up_recommendations,
                "engagement_optimization": engagement_optimization
            }
            
        except Exception as e:
            return {"error": f"Tracking optimization failed: {e}"}
    
    async def create_smart_mixmax_sequence(self, sequence_name: str,
                                         contacts: List[Dict],
                                         template_config: Dict = None) -> Dict:
        """
        Create intelligent Mixmax sequence with productivity optimization
        """
        try:
            # Step 1: Enhance contacts with comprehensive intelligence
            enhanced_contacts = await self._bulk_enhance_for_productivity(contacts)
            
            # Step 2: Generate personalized sequence structure
            sequence_structure = await self._generate_smart_sequence_structure(
                enhanced_contacts, template_config
            )
            
            # Step 3: Create Mixmax sequence with optimization
            sequence_data = await self._create_mixmax_sequence(sequence_name, sequence_structure)
            
            if not sequence_data:
                return {"error": "Failed to create Mixmax sequence"}
            
            # Step 4: Apply productivity optimizations
            optimization_results = await self._apply_productivity_optimizations(
                sequence_data['id'], enhanced_contacts
            )
            
            return {
                "sequence_id": sequence_data['id'],
                "sequence_name": sequence_name,
                "total_contacts": len(enhanced_contacts),
                "productivity_optimization": self._analyze_productivity_optimization(enhanced_contacts),
                "optimization_results": optimization_results
            }
            
        except Exception as e:
            return {"error": f"Smart sequence creation failed: {e}"}
    
    async def _bulk_enhance_for_productivity(self, contacts: List[Dict]) -> List[SmartMixmaxContact]:
        """Enhance multiple contacts for optimal Mixmax productivity"""
        enhancement_tasks = []
        
        for contact_data in contacts:
            smart_contact = SmartMixmaxContact(
                email=contact_data.get('email', ''),
                first_name=contact_data.get('firstName') or contact_data.get('first_name'),
                last_name=contact_data.get('lastName') or contact_data.get('last_name'),
                position=contact_data.get('position') or contact_data.get('title'),
                company=contact_data.get('company'),
                domain=contact_data.get('domain'),
                linkedin_url=contact_data.get('linkedin_url'),
                enhancement_timestamp=datetime.now().isoformat()
            )
            
            task = self._enhance_single_contact_for_productivity(smart_contact)
            enhancement_tasks.append(task)
        
        # Process all enhancements in parallel
        await asyncio.gather(*enhancement_tasks, return_exceptions=True)
        
        return [task.result() for task in enhancement_tasks if not isinstance(task.result(), Exception)]
    
    async def _enhance_single_contact_for_productivity(self, contact: SmartMixmaxContact) -> None:
        """Comprehensive single contact enhancement for productivity"""
        enhancement_tasks = []
        
        # Email validation with tracking optimization
        if contact.email:
            task1 = self._validate_email_for_tracking(contact.email)
            enhancement_tasks.append(task1)
        
        # Phone enrichment for multi-channel follow-up
        if contact.first_name and contact.last_name:
            task2 = self._enrich_phone_for_followup(contact)
            enhancement_tasks.append(task2)
        
        # Engagement intelligence gathering
        task3 = self._gather_engagement_intelligence(contact)
        enhancement_tasks.append(task3)
        
        # Execute all enhancements
        results = await asyncio.gather(*enhancement_tasks, return_exceptions=True)
        
        # Process email validation and tracking optimization
        if len(results) > 0 and not isinstance(results[0], Exception):
            contact.email_validation = results[0]
            contact.tracking_optimization = results[0].get('tracking_optimization', {})
        
        # Process phone enrichment
        if len(results) > 1 and not isinstance(results[1], Exception) and results[1]:
            contact.phone_validation = results[1]
            contact.phone = results[1].get('phone_number')
        
        # Process engagement intelligence
        if len(results) > 2 and not isinstance(results[2], Exception):
            contact.engagement_intelligence = results[2]
            if results[2]:
                contact.best_engagement_time = results[2].get('optimal_contact_time')
        
        # Calculate productivity scores and optimizations
        contact.engagement_score = self._calculate_engagement_productivity_score(contact)
        contact.follow_up_priority = self._determine_followup_priority(contact)
        contact.productivity_readiness = self._assess_productivity_readiness(contact)
        contact.mixmax_optimization = self._generate_mixmax_optimization(contact)
    
    async def _validate_email_for_tracking(self, email: str) -> Dict:
        """Advanced email validation with tracking optimization"""
        url = f"{self.lookup_base_url}/email/validate"
        headers = {
            'Authorization': f'Bearer {self.lookup_api_key}',
            'Content-Type': 'application/json'
        }
        
        payload = {
            'email': email,
            'tracking_optimization': True,
            'engagement_prediction': True,
            'deliverability_intelligence': True,
            'gmail_optimization': True
        }
        
        async with aiohttp.ClientSession() as session:
            async with session.post(url, json=payload, headers=headers) as response:
                if response.status == 200:
                    result = await response.json()
                    
                    # Generate tracking optimization recommendations
                    tracking_optimization = {
                        'open_likelihood': result.get('open_prediction', 0),
                        'click_likelihood': result.get('click_prediction', 0),
                        'response_likelihood': result.get('response_prediction', 0),
                        'optimal_send_time': result.get('optimal_timing', 'morning'),
                        'subject_recommendations': result.get('subject_optimization', []),
                        'tracking_confidence': result.get('tracking_reliability', 85)
                    }
                    
                    result['tracking_optimization'] = tracking_optimization
                    return result
                return {'deliverable': False, 'tracking_optimization': {'open_likelihood': 0}}
    
    async def _enrich_phone_for_followup(self, contact: SmartMixmaxContact) -> Optional[Dict]:
        """Phone enrichment optimized for Mixmax follow-up campaigns"""
        url = f"{self.lookup_base_url}/enrich/phone"
        headers = {
            'Authorization': f'Bearer {self.lookup_api_key}',
            'Content-Type': 'application/json'
        }
        
        payload = {
            'first_name': contact.first_name,
            'last_name': contact.last_name,
            'company': contact.company,
            'domain': contact.domain,
            'email': contact.email,
            'mixmax_optimization': True,
            'follow_up_preference': True
        }
        
        try:
            async with aiohttp.ClientSession() as session:
                async with session.post(url, json=payload, headers=headers) as response:
                    if response.status == 200:
                        result = await response.json()
                        
                        # Assess follow-up potential
                        if result.get('valid'):
                            result['follow_up_score'] = 90 if result.get('mobile') else 70
                            result['mixmax_integration'] = 'high' if result.get('call_capability') else 'medium'
                        else:
                            result['follow_up_score'] = 0
                            result['mixmax_integration'] = 'low'
                        
                        return result
        except:
            pass
        
        return None
    
    async def _gather_engagement_intelligence(self, contact: SmartMixmaxContact) -> Optional[Dict]:
        """Gather comprehensive engagement intelligence for productivity optimization"""
        url = f"{self.lookup_base_url}/enrich/engagement"
        headers = {
            'Authorization': f'Bearer {self.lookup_api_key}',
            'Content-Type': 'application/json'
        }
        
        payload = {
            'first_name': contact.first_name,
            'last_name': contact.last_name,
            'company': contact.company,
            'email': contact.email,
            'linkedin_url': contact.linkedin_url,
            'productivity_analysis': True,
            'timing_optimization': True
        }
        
        try:
            async with aiohttp.ClientSession() as session:
                async with session.post(url, json=payload, headers=headers) as response:
                    if response.status == 200:
                        return await response.json()
        except:
            pass
        
        return None
    
    def _calculate_engagement_productivity_score(self, contact: SmartMixmaxContact) -> int:
        """Calculate comprehensive engagement productivity score"""
        score = 0
        
        # Email tracking potential (0-40 points)
        if contact.tracking_optimization:
            tracking_score = (
                contact.tracking_optimization.get('open_likelihood', 0) * 0.15 +
                contact.tracking_optimization.get('click_likelihood', 0) * 0.15 +
                contact.tracking_optimization.get('response_likelihood', 0) * 0.10
            )
            score += tracking_score
        
        # Multi-channel capability (0-25 points)
        if contact.phone_validation and contact.phone_validation.get('valid'):
            score += 25
        elif contact.linkedin_url:
            score += 15
        
        # Professional engagement potential (0-20 points)
        if contact.position:
            position_lower = contact.position.lower()
            if any(title in position_lower for title in ['ceo', 'founder', 'director']):
                score += 20
            elif any(title in position_lower for title in ['manager', 'lead', 'vp']):
                score += 15
            else:
                score += 10
        
        # Contact completeness (0-10 points)
        completeness = 0
        if contact.email: completeness += 3
        if contact.phone: completeness += 3
        if contact.company and contact.position: completeness += 4
        score += completeness
        
        # Engagement intelligence bonus (0-5 points)
        if contact.engagement_intelligence:
            score += 5
        
        return min(score, 100)
    
    def _determine_followup_priority(self, contact: SmartMixmaxContact) -> str:
        """Determine smart follow-up priority for Mixmax optimization"""
        if contact.engagement_score >= 80:
            return "high"
        elif contact.engagement_score >= 60:
            return "medium"
        else:
            return "low"
    
    def _assess_productivity_readiness(self, contact: SmartMixmaxContact) -> str:
        """Assess contact's readiness for Mixmax productivity optimization"""
        readiness_factors = 0
        
        # Email deliverability
        if contact.email_validation and contact.email_validation.get('deliverable'):
            readiness_factors += 2
        
        # Tracking optimization potential
        if contact.tracking_optimization and contact.tracking_optimization.get('open_likelihood', 0) > 60:
            readiness_factors += 2
        
        # Multi-channel capability
        if contact.phone_validation and contact.phone_validation.get('valid'):
            readiness_factors += 2
        
        # Professional level
        if contact.position and contact.company:
            readiness_factors += 2
        
        # Engagement intelligence
        if contact.engagement_intelligence:
            readiness_factors += 1
        
        if readiness_factors >= 7:
            return "excellent"
        elif readiness_factors >= 5:
            return "good"
        elif readiness_factors >= 3:
            return "fair"
        else:
            return "limited"
    
    def _generate_mixmax_optimization(self, contact: SmartMixmaxContact) -> Dict:
        """Generate specific Mixmax optimization recommendations"""
        optimization = {
            'tracking_strategy': 'standard',
            'follow_up_channels': ['email'],
            'engagement_timing': 'morning',
            'template_personalization': 'basic',
            'productivity_score': contact.engagement_score
        }
        
        # Tracking strategy optimization
        if contact.tracking_optimization:
            open_likelihood = contact.tracking_optimization.get('open_likelihood', 0)
            click_likelihood = contact.tracking_optimization.get('click_likelihood', 0)
            
            if open_likelihood > 80 and click_likelihood > 60:
                optimization['tracking_strategy'] = 'aggressive'
                optimization['template_personalization'] = 'high'
            elif open_likelihood > 60:
                optimization['tracking_strategy'] = 'moderate'
                optimization['template_personalization'] = 'medium'
        
        # Multi-channel follow-up recommendations
        channels = ['email']
        if contact.phone_validation and contact.phone_validation.get('valid'):
            channels.append('phone')
        if contact.linkedin_url:
            channels.append('linkedin')
        optimization['follow_up_channels'] = channels
        
        # Engagement timing optimization
        if contact.engagement_intelligence and contact.best_engagement_time:
            optimization['engagement_timing'] = contact.best_engagement_time
        
        return optimization
    
    async def _generate_tracking_strategies(self, contacts: List[SmartMixmaxContact]) -> Dict:
        """Generate comprehensive tracking strategies for different contact segments"""
        strategies = {
            'high_engagement': {'contacts': [], 'strategy': {}},
            'medium_engagement': {'contacts': [], 'strategy': {}},
            'low_engagement': {'contacts': [], 'strategy': {}}
        }
        
        # Segment contacts by engagement score
        for contact in contacts:
            if contact.engagement_score >= 80:
                strategies['high_engagement']['contacts'].append(contact)
            elif contact.engagement_score >= 60:
                strategies['medium_engagement']['contacts'].append(contact)
            else:
                strategies['low_engagement']['contacts'].append(contact)
        
        # Generate strategies for each segment
        strategies['high_engagement']['strategy'] = {
            'tracking_frequency': 'aggressive',
            'personalization_level': 'high',
            'follow_up_timing': 'immediate',
            'multi_channel': True
        }
        
        strategies['medium_engagement']['strategy'] = {
            'tracking_frequency': 'moderate',
            'personalization_level': 'medium',
            'follow_up_timing': 'standard',
            'multi_channel': True
        }
        
        strategies['low_engagement']['strategy'] = {
            'tracking_frequency': 'conservative',
            'personalization_level': 'basic',
            'follow_up_timing': 'delayed',
            'multi_channel': False
        }
        
        return strategies
    
    def _generate_smart_follow_ups(self, contacts: List[SmartMixmaxContact]) -> Dict:
        """Generate intelligent follow-up recommendations for Mixmax"""
        recommendations = {}
        
        for contact in contacts:
            contact_key = contact.email
            recommendations[contact_key] = {
                'priority': contact.follow_up_priority,
                'channels': contact.mixmax_optimization.get('follow_up_channels', ['email']),
                'timing': contact.mixmax_optimization.get('engagement_timing', 'morning'),
                'personalization': contact.mixmax_optimization.get('template_personalization', 'basic'),
                'tracking_strategy': contact.mixmax_optimization.get('tracking_strategy', 'standard')
            }
        
        return recommendations
    
    def _calculate_productivity_stats(self, contacts: List[SmartMixmaxContact]) -> Dict:
        """Calculate comprehensive productivity statistics"""
        total = len(contacts)
        if total == 0:
            return {}
        
        high_engagement = sum(1 for c in contacts if c.engagement_score >= 80)
        multi_channel = sum(1 for c in contacts if len(c.mixmax_optimization.get('follow_up_channels', ['email'])) > 1)
        trackable = sum(1 for c in contacts if c.tracking_optimization and c.tracking_optimization.get('open_likelihood', 0) > 60)
        
        return {
            'total_contacts': total,
            'high_engagement_rate': (high_engagement / total) * 100,
            'multi_channel_capability': (multi_channel / total) * 100,
            'trackable_contacts': (trackable / total) * 100,
            'average_engagement_score': sum(c.engagement_score for c in contacts) / total,
            'productivity_ready': sum(1 for c in contacts if c.productivity_readiness in ['excellent', 'good'])
        }

# Example usage for Mixmax productivity optimization
async def main():
    integration = Mixmax1lookupIntegration(
        mixmax_api_key="your_mixmax_api_key",
        lookup_api_key="your_1lookup_api_key"
    )
    
    # Sample contacts for productivity optimization
    sample_contacts = [
        {
            'email': 'john@example.com',
            'firstName': 'John',
            'lastName': 'Smith',
            'position': 'Sales Director',
            'company': 'Example Corp'
        },
        # Add more contacts...
    ]
    
    # Optimize email tracking
    tracking_result = await integration.optimize_email_tracking(sample_contacts)
    
    print("Mixmax Tracking Optimization Results:")
    print(f"Total Contacts: {tracking_result.get('total_contacts')}")
    print(f"Enhanced Contacts: {tracking_result.get('enhanced_contacts')}")
    
    productivity_stats = tracking_result.get('productivity_stats', {})
    print(f"
Productivity Statistics:")
    print(f"High Engagement Rate: {productivity_stats.get('high_engagement_rate', 0):.1f}%")
    print(f"Multi-Channel Capability: {productivity_stats.get('multi_channel_capability', 0):.1f}%")
    print(f"Trackable Contacts: {productivity_stats.get('trackable_contacts', 0):.1f}%")
    print(f"Average Engagement Score: {productivity_stats.get('average_engagement_score', 0):.1f}")

# Run the integration
if __name__ == "__main__":
    import aiohttp
    asyncio.run(main())