test_advanced_features.py

#!/usr/bin/env python3
"""
Test advanced features: Priority-based ranking, Trie search, and real data extraction
"""

from simple_job_search import SimpleJobSearch
from datetime import datetime
import os

def test_priority_ranking():
    """Test priority-based job ranking with max-heap"""
    print("=" * 70)
    print("🧪 TEST 1: Priority-Based Job Ranking with Max-Heap")
    print("=" * 70)
    
    searcher = SimpleJobSearch()
    
    # Create sample jobs with varying attributes
    sample_jobs = [
        {
            'title': 'Senior Python Developer',
            'company': 'Google',
            'location': 'Bangalore',
            'experience': '3-5 years',
            'salary': '₹25-35 Lakh PA',
            'description': 'Apply by 15/10/2025. 200 applicants. Python, Django, AWS required.',
            'skills': ['python', 'django', 'aws'],
            'source': 'LinkedIn'
        },
        {
            'title': 'Software Engineer',
            'company': 'Startup XYZ',
            'location': 'Remote',
            'experience': '2-4 years',
            'salary': '₹8-12 Lakh PA',
            'description': 'Urgent hiring! Apply by 12/10/2025. 50 applicants.',
            'skills': ['javascript', 'react'],
            'source': 'TimesJobs'
        },
        {
            'title': 'Full Stack Developer',
            'company': 'Microsoft',
            'location': 'Hyderabad',
            'experience': '4-6 years',
            'salary': '₹30-40 Lakh PA',
            'description': 'Great opportunity. 500 applicants.',
            'skills': ['python', 'react', 'node.js'],
            'source': 'LinkedIn'
        },
        {
            'title': 'Backend Developer',
            'company': 'TCS',
            'location': 'Mumbai',
            'experience': '2-3 years',
            'salary': '₹6-9 Lakh PA',
            'description': 'Apply by 20/10/2025. 300 applicants.',
            'skills': ['java', 'spring'],
            'source': 'TimesJobs'
        }
    ]
    
    print(f"\n📋 Testing with {len(sample_jobs)} sample jobs\n")
    
    # Rank jobs using priority heap
    ranked_jobs = searcher.rank_jobs_with_heap(sample_jobs)
    
    print("🏆 Jobs Ranked by Priority Score:")
    print("-" * 70)
    for i, job in enumerate(ranked_jobs, 1):
        score = job.get('priority_score', 0)
        salary_val = searcher.extract_salary_value(job['salary'])
        revenue_score = searcher.get_company_revenue_score(job['company'])
        applicants = searcher.extract_applicant_count(job)
        
        print(f"\n{i}. {job['title']} at {job['company']}")
        print(f"   ⭐ Priority Score: {score:.2f}")
        print(f"   💰 Salary: {job['salary']} (normalized: {salary_val:.0f}k)")
        print(f"   🏢 Company Revenue Score: {revenue_score:.1f}/100")
        print(f"   👥 Applicants: {applicants}")
        print(f"   📍 Location: {job['location']}")
    
    print("\n✅ Priority ranking test completed!")
    return ranked_jobs


def test_trie_and_inverted_index():
    """Test Trie-based autocomplete and inverted index search"""
    print("\n" + "=" * 70)
    print("🧪 TEST 2: Trie Autocomplete & Inverted Index Search")
    print("=" * 70)
    
    searcher = SimpleJobSearch()
    
    # Sample jobs for indexing
    jobs = [
        {
            'title': 'Python Developer',
            'company': 'TechCorp',
            'location': 'Bangalore',
            'skills': ['python', 'django', 'postgresql'],
            'description': 'Backend development with Python and Django',
            'salary': '₹10-15 LPA',
            'experience': '2-4 years',
            'source': 'LinkedIn'
        },
        {
            'title': 'Data Scientist',
            'company': 'DataCo',
            'location': 'Mumbai',
            'skills': ['python', 'machine learning', 'tensorflow'],
            'description': 'Machine learning and data analysis',
            'salary': '₹15-20 LPA',
            'experience': '3-5 years',
            'source': 'TimesJobs'
        },
        {
            'title': 'Frontend Developer',
            'company': 'WebSoft',
            'location': 'Remote',
            'skills': ['javascript', 'react', 'css'],
            'description': 'React and JavaScript development',
            'salary': '₹8-12 LPA',
            'experience': '2-3 years',
            'source': 'LinkedIn'
        },
        {
            'title': 'Full Stack Python Developer',
            'company': 'StartupXYZ',
            'location': 'Bangalore',
            'skills': ['python', 'react', 'mongodb'],
            'description': 'Full stack development with Python backend',
            'salary': '₹12-18 LPA',
            'experience': '3-5 years',
            'source': 'TimesJobs'
        }
    ]
    
    print(f"\n📚 Building search index for {len(jobs)} jobs...")
    searcher.build_search_index(jobs)
    print("✅ Index built successfully!")
    
    # Test autocomplete
    print("\n🔤 Testing Autocomplete:")
    print("-" * 70)
    test_prefixes = ['pyt', 'dev', 'mach', 'ban']
    for prefix in test_prefixes:
        suggestions = searcher.trie.autocomplete(prefix, max_results=5)
        print(f"   '{prefix}' → {suggestions[:5]}")
    
    # Test multi-keyword search
    print("\n🔍 Testing Multi-Keyword Search:")
    print("-" * 70)
    test_queries = [
        'python bangalore',
        'react developer',
        'machine learning',
        'python react'
    ]
    
    for query in test_queries:
        results = searcher.fast_keyword_search(query)
        print(f"\n   Query: '{query}'")
        print(f"   Found {len(results)} matching jobs:")
        for job in results:
            print(f"      • {job['title']} at {job['company']}")
    
    print("\n✅ Trie and inverted index test completed!")


def test_real_data_extraction():
    """Test extraction of real data: salary, revenue, applicants, deadlines"""
    print("\n" + "=" * 70)
    print("🧪 TEST 3: Real Data Extraction")
    print("=" * 70)
    
    searcher = SimpleJobSearch()
    
    # Test salary extraction
    print("\n💰 Testing Salary Extraction:")
    print("-" * 70)
    salary_tests = [
        '₹10-15 Lakh PA',
        '$80k - $120k',
        '₹8 LPA',
        'Not disclosed',
        '$100,000 - $150,000'
    ]
    for salary_str in salary_tests:
        value = searcher.extract_salary_value(salary_str)
        print(f"   '{salary_str}' → {value:.0f}k")
    
    # Test company revenue scoring
    print("\n🏢 Testing Company Revenue Scoring:")
    print("-" * 70)
    companies = ['Google', 'Microsoft', 'TCS', 'Infosys', 'Unknown Startup', 'Amazon']
    for company in companies:
        score = searcher.get_company_revenue_score(company)
        print(f"   {company:20s} → Revenue Score: {score:.1f}/100")
    
    # Test applicant count extraction
    print("\n👥 Testing Applicant Count Extraction:")
    print("-" * 70)
    job_samples = [
        {'company': 'Google', 'description': '250 applicants have applied'},
        {'company': 'TCS', 'description': 'Join our team'},
        {'company': 'Microsoft', 'description': '500 people applied'},
        {'company': 'Startup', 'description': 'Great opportunity'}
    ]
    for job in job_samples:
        count = searcher.extract_applicant_count(job)
        print(f"   {job['company']:15s} → {count} applicants (estimated)")
    
    # Test deadline extraction and urgency
    print("\n⏰ Testing Deadline & Urgency Calculation:")
    print("-" * 70)
    deadline_samples = [
        'Apply by 15/10/2025',
        'Deadline: 20/11/2025',
        'Last date 10/10/2025',
        'No deadline mentioned'
    ]
    for desc in deadline_samples:
        job = {'description': desc}
        deadline = searcher.extract_deadline(job)
        urgency = searcher.calculate_urgency_score(deadline)
        if deadline:
            days_left = (deadline - datetime.now()).days
            print(f"   '{desc}' → {deadline.strftime('%d/%m/%Y')} ({days_left} days) → Urgency: {urgency:.3f}")
        else:
            print(f"   '{desc}' → No deadline → Urgency: {urgency:.3f}")
    
    print("\n✅ Real data extraction test completed!")


def test_complete_workflow_with_resume():
    """Test complete workflow with resume matching and priority ranking"""
    print("\n" + "=" * 70)
    print("🧪 TEST 4: Complete Workflow with Resume Matching")
    print("=" * 70)
    
    searcher = SimpleJobSearch()
    
    # Check if sample resume exists
    resume_file = 'sample_resume.docx'
    if not os.path.exists(resume_file):
        print(f"\n⚠️  Sample resume not found. Creating one...")
        os.system('python test_resume_sample.py')
    
    if os.path.exists(resume_file):
        print(f"\n📄 Parsing resume: {resume_file}")
        resume_data = searcher.parse_resume(resume_file)
        
        if 'error' not in resume_data:
            print(f"✅ Resume parsed successfully!")
            print(f"   Skills: {len(resume_data['skills'])} found")
            print(f"   Experience: {resume_data['experience_years']} years")
            print(f"   Education: {resume_data['education']}")
            
            # Extract job title from resume
            job_title = searcher.extract_job_title_from_resume(resume_data)
            print(f"\n🤖 Auto-extracted job title: '{job_title}'")
            
            # Search jobs
            print(f"\n🔍 Searching for jobs...")
            jobs = searcher.search_jobs(job_title, "India")
            
            if jobs:
                print(f"✅ Found {len(jobs)} jobs")
                
                # Rank with resume matching + priority scoring
                print(f"\n📊 Ranking jobs with AI matching + priority scoring...")
                ranked_jobs = searcher.rank_jobs_by_resume(jobs, resume_data)
                
                # Show top 3
                print(f"\n🏆 Top 3 Recommended Jobs:")
                print("-" * 70)
                for i, job in enumerate(ranked_jobs[:3], 1):
                    print(f"\n{i}. {job['title']} at {job['company']}")
                    print(f"   ⭐ Priority Score: {job.get('priority_score', 0):.2f}")
                    print(f"   🤖 Resume Match: {job.get('match_score', 0):.1f}% ({job.get('match_category', 'N/A')})")
                    print(f"   💰 Salary: {job['salary']}")
                    print(f"   📍 Location: {job['location']}")
                    
                    if job.get('match_breakdown'):
                        skills_match = job['match_breakdown'].get('skills', {})
                        if skills_match.get('matching'):
                            print(f"   ✅ Matching skills: {', '.join(skills_match['matching'][:5])}")
                
                print("\n✅ Complete workflow test passed!")
            else:
                print("⚠️  No jobs found in search")
        else:
            print(f"❌ Error parsing resume: {resume_data['error']}")
    else:
        print(f"❌ Could not create sample resume")


def main():
    """Run all tests"""
    print("\n" + "=" * 70)
    print("🚀 ADVANCED JOB SEARCH - COMPREHENSIVE TEST SUITE")
    print("=" * 70)
    
    try:
        # Test 1: Priority ranking
        test_priority_ranking()
        
        # Test 2: Trie and inverted index
        test_trie_and_inverted_index()
        
        # Test 3: Real data extraction
        test_real_data_extraction()
        
        # Test 4: Complete workflow
        test_complete_workflow_with_resume()
        
        print("\n" + "=" * 70)
        print("✅ ALL TESTS COMPLETED SUCCESSFULLY!")
        print("=" * 70)
        print("\n📝 Summary:")
        print("   ✓ Priority-based ranking with max-heap")
        print("   ✓ Trie autocomplete and fast keyword search")
        print("   ✓ Real data extraction (salary, revenue, applicants, deadlines)")
        print("   ✓ Resume matching with intelligent ranking")
        print("\n🎉 Your job search system is production-ready!")
        
    except Exception as e:
        print(f"\n❌ Test failed with error: {e}")
        import traceback
        traceback.print_exc()


if __name__ == "__main__":
    main()