class MarkLumba:
    def __init__(self):
        self.role = "Data & Automation Engineer"
        
        # Programming Languages
        self.languages = {
            "primary": ["Python", "SQL"],
            "scripting": ["Shell", "Bash"]
        }
        
        # Big Data Technologies
        self.big_data = {
            "processing": ["Apache Spark", "Hadoop"],
            "streaming": ["Apache Kafka"],
            "orchestration": ["Apache Airflow"]
        }
        
        # Cloud Platforms
        self.cloud_services = {
            "platforms": ["AWS", "GCP", "Azure"],
            "containers": ["Docker", "Kubernetes"]
        }
        
        # Databases
        self.databases = {
            "sql": ["MySQL", "PostgreSQL", "SQL Server", "DuckDB"],
            "nosql": ["MongoDB", "Cassandra", "Redis"]
        }
        
        # AI/ML Tools
        self.ai_ml = {
            "frameworks": ["LLM", "Hugging Face Transformers"],
            "libraries": ["TensorFlow", "PyTorch", "scikit-learn"]
        }
        
        # Development Tools
        self.dev_tools = {
            "version_control": ["Git", "GitHub"],
            "ci_cd": ["Jenkins", "GitHub Actions"],
            "monitoring": ["Grafana", "Prometheus"]
        }
        
        # Core Competencies
        self.expertise = {
            "data_engineering": ["ETL", "Data Pipelines", "Data Modeling"],
            "automation": ["Process Automation", "Workflow Optimization"],
            "architecture": ["System Design", "Microservices", "Data Architecture"]
        }

    def get_tech_stack(self):
        """
        Returns a formatted version of the complete tech stack
        """
        return {
            "Languages": self.languages,
            "Big Data": self.big_data,
            "Cloud & Infrastructure": self.cloud_services,
            "Databases": self.databases,
            "AI/ML": self.ai_ml,
            "Development Tools": self.dev_tools,
            "Core Expertise": self.expertise
        }

    def __str__(self):
        """
        Returns a string representation of key skills
        """
        return f"Data & Automation Engineer specialized in Python, Big Data, and Cloud Technologies"