1. Read Excel File:

    Load all sheets from the Excel file sample_datasets.xlsx using pandas.
    Extract sheet names to determine table names.
    Read the first row for column headers and treat the first column as primary key.

2. Create Tables in PostgreSQL (Using SQLAlchemy Only):

    Use SQLAlchemy ORM or Core to create the schema dynamically.
    Check for column existence and add new columns dynamically if found.
    No hardcoded column names or SQL strings.

3. Auto Schema Evolution:

    When the Excel file is updated with new columns, the script must:
    Detect missing columns in the existing PostgreSQL table.
    Use SQLAlchemy to add those new columns to the existing table schema.

4. CRUD Operations (on one table e.g., Employees):

    Create: Add a new employee.
    Read: Fetch all employees or by ID.
    Update: Modify an employee's department or salary.
    Delete: Remove an employee by ID.