resume_analyzer.py

from models import Resume, JobDescription
from typing import Dict, Any

class ResumeAnalyzer:
    """
    Renew System for Judging and Analyzing Resumes Sounak
    Deep heuristic-based analysis comparing candidate skills with JD requirements.
    """
    
    @staticmethod
    def analyze(resume: Resume, jd: JobDescription) -> Dict[str, Any]:
        match_skills = set([s.lower() for s in resume.skills]).intersection(set([s.lower() for s in jd.required_skills]))
        missing_skills = set([s.lower() for s in jd.required_skills]) - set([s.lower() for s in resume.skills])
        bonus_skills = set([s.lower() for s in resume.skills]).intersection(set([s.lower() for s in jd.preferred_skills]))
        
        # Experience Check
        exp_verdict = "Adequate"
        if resume.experience_years < jd.min_experience:
            exp_verdict = f"Missing {jd.min_experience - resume.experience_years} years"
        elif jd.max_experience and resume.experience_years > jd.max_experience:
            exp_verdict = "Over-qualified"
        else:
            exp_verdict = "Strong Fit"
            
        # Pros & Cons
        pros = []
        cons = []
        
        if match_skills:
            pros.append(f"Matches {len(match_skills)} core skills.")
        if bonus_skills:
            pros.append(f"Brings {len(bonus_skills)} bonus skills to the role.")
        if exp_verdict == "Strong Fit":
            pros.append("Experience aligns perfectly with requirements.")
            
        if missing_skills:
            cons.append(f"Missing critical tech stack: {', '.join(missing_skills)}.")
        if exp_verdict.startswith("Missing"):
            cons.append(f"Lacks requisite years of experience ({exp_verdict}).")
            
        return {
            "match_skills": list(match_skills),
            "missing_skills": list(missing_skills),
            "bonus_skills": list(bonus_skills),
            "experience_verdict": exp_verdict,
            "pros": pros,
            "cons": cons,
            "overall_judgment": "Recommended for Interview" if (len(match_skills) >= len(jd.required_skills)//2 and not exp_verdict.startswith("Missing")) else "Caution/Reject"
        }

resume_analyzer = ResumeAnalyzer()