#!/usr/bin/env python3
"""
HiGHS Solver - Proof of Concept Implementation
"""

import logging
from typing import Any, Dict, Optional
import numpy as np

logger = logging.getLogger(__name__)

# Try to import HiGHS
try:
    import highspy
    HAS_HIGHS = True
    logger.info("HiGHS solver available for optimization")
except ImportError as e:
    HAS_HIGHS = False
    logger.warning(f"HiGHS solver not available: {e}")


class HiGHSSolver:
    """HiGHS solver using highspy Python bindings"""

    def __init__(self):
        self.model = None
        self.variables = {}
        self.constraints = []
        self.objective = None

    def solve_model(self, model_data: Dict[str, Any]) -> Dict[str, Any]:
        """Solve a model using HiGHS"""
        if not HAS_HIGHS:
            return {
                'status': 'error',
                'error': 'HiGHS not available',
                'message': 'HiGHS library not installed'
            }

        try:
            # Create a new HiGHS model
            self.model = highspy.Highs()
            self.variables = {}
            self.constraints = []
            
            # Add variables
            variables_data = model_data.get('variables', [])
            for var_data in variables_data:
                if isinstance(var_data, dict):
                    name = var_data.get('name', f'var_{len(self.variables)}')
                    var_type = var_data.get('type', 'continuous')
                    bounds = var_data.get('bounds', '0 to inf')
                    
                    # Parse bounds
                    lower_bound, upper_bound = self._parse_bounds(bounds)
                    
                    # Add variable to HiGHS
                    if var_type == 'binary':
                        self.model.addVar(lower_bound, upper_bound, highspy.HighsVarType.kInteger)
                        self.variables[name] = len(self.variables)
                        logger.info(f"Added binary variable: {name} [{lower_bound}, {upper_bound}]")
                    elif var_type == 'integer':
                        self.model.addVar(lower_bound, upper_bound, highspy.HighsVarType.kInteger)
                        self.variables[name] = len(self.variables)
                        logger.info(f"Added integer variable: {name} [{lower_bound}, {upper_bound}]")
                    else:  # continuous
                        self.model.addVar(lower_bound, upper_bound, highspy.HighsVarType.kContinuous)
                        self.variables[name] = len(self.variables)
                        logger.info(f"Added continuous variable: {name} [{lower_bound}, {upper_bound}]")
            
            # Set objective
            objective_data = model_data.get('objective', {})
            if objective_data:
                obj_type = objective_data.get('type', 'minimize')
                obj_expression = objective_data.get('expression', '')
                
                # Parse objective expression
                obj_coeffs = self._parse_objective_expression(obj_expression)
                
                if obj_type == 'maximize':
                    # Negate coefficients for maximization
                    obj_coeffs = [-coeff for coeff in obj_coeffs]
                
                # Set objective in HiGHS
                self.model.changeObjectiveSense(highspy.ObjSense.kMinimize)
                self.model.changeColsCost(len(obj_coeffs), list(range(len(obj_coeffs))), obj_coeffs)
                
                logger.info(f"Set objective: {obj_type} {obj_expression}")
            
            # Add constraints
            constraints_data = model_data.get('constraints', [])
            for i, constraint_data in enumerate(constraints_data):
                if isinstance(constraint_data, dict):
                    expression = constraint_data.get('expression', '')
                    description = constraint_data.get('description', f'constraint_{i}')
                    
                    # Parse constraint expression
                    coeffs, rhs, sense = self._parse_constraint_expression(expression)
                    
                    if coeffs is not None:
                        # Add constraint to HiGHS
                        self.model.addRow(rhs, rhs, len(coeffs), 
                                        list(range(len(coeffs))), coeffs)
                        logger.info(f"Added constraint: {expression}")
            
            # Solve the model
            logger.info("Solving HiGHS model...")
            self.model.run()
            
            # Get solution status
            status = self.model.getModelStatus()
            
            if status == highspy.HighsModelStatus.kOptimal:
                # Extract solution
                solution = self.model.getSolution()
                optimal_values = {}
                
                for name, var_idx in self.variables.items():
                    optimal_values[name] = solution.col_value[var_idx]
                
                objective_value = solution.objective_value
                
                return {
                    'status': 'optimal',
                    'objective_value': objective_value,
                    'optimal_values': optimal_values,
                    'solve_time': 0.0,  # HiGHS doesn't expose solve time easily
                    'solver': 'HiGHS',
                    'message': 'Solved successfully with HiGHS'
                }
            elif status == highspy.HighsModelStatus.kInfeasible:
                return {
                    'status': 'infeasible',
                    'error': 'Model is infeasible',
                    'message': 'No feasible solution exists'
                }
            elif status == highspy.HighsModelStatus.kUnbounded:
                return {
                    'status': 'unbounded',
                    'error': 'Model is unbounded',
                    'message': 'Objective can be improved indefinitely'
                }
            else:
                return {
                    'status': 'error',
                    'error': f'HiGHS solver status: {status}',
                    'message': 'Solver failed to find solution'
                }
                
        except Exception as e:
            logger.error(f"HiGHS solving failed: {e}")
            return {
                'status': 'error',
                'error': str(e),
                'message': 'HiGHS solver encountered an error'
            }
    
    def _parse_bounds(self, bounds_str: str) -> tuple:
        """Parse bounds string like '0 to 200' or '0 or 1'"""
        try:
            if ' or ' in bounds_str:  # Binary: '0 or 1'
                return (0, 1)
            elif ' to ' in bounds_str:  # Range: '0 to 200'
                parts = bounds_str.split(' to ')
                lower = float(parts[0]) if parts[0] != '-inf' else -np.inf
                upper = float(parts[1]) if parts[1] != 'inf' else np.inf
                return (lower, upper)
            else:
                # Try to parse as single number
                val = float(bounds_str)
                return (val, val)
        except:
            return (0, np.inf)  # Default bounds
    
    def _parse_objective_expression(self, expression: str) -> list:
        """Parse objective expression like '77.34*y_ijt + 44.70*I_it'"""
        try:
            # Simple parsing - split by + and extract coefficients
            terms = expression.replace(' ', '').split('+')
            coeffs = []
            
            for term in terms:
                if '*' in term:
                    coeff, var = term.split('*')
                    coeffs.append(float(coeff))
                else:
                    # Assume coefficient is 1
                    coeffs.append(1.0)
            
            return coeffs
        except:
            return [1.0]  # Default coefficient
    
    def _parse_constraint_expression(self, expression: str) -> tuple:
        """Parse constraint expression like 'x_ijt <= 200*y_ijt'"""
        try:
            # Simple parsing for basic constraints
            if '<=' in expression:
                lhs, rhs = expression.split('<=')
                # For now, return simple coefficients
                return [1.0], float(rhs.strip()), highspy.HighsBasisStatus.kLower
            elif '>=' in expression:
                lhs, rhs = expression.split('>=')
                return [1.0], float(rhs.strip()), highspy.HighsBasisStatus.kUpper
            elif '=' in expression:
                lhs, rhs = expression.split('=')
                return [1.0], float(rhs.strip()), highspy.HighsBasisStatus.kEqual
            else:
                return None, 0.0, highspy.HighsBasisStatus.kLower
        except:
            return None, 0.0, highspy.HighsBasisStatus.kLower
