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

import logging
from typing import Any, Dict, Optional
from ortools.linear_solver import pywraplp

logger = logging.getLogger(__name__)


class HiGHSViaORToolsSolver:
    """HiGHS solver using OR-Tools linear solver wrapper"""

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

    def solve_model(self, model_data: Dict[str, Any]) -> Dict[str, Any]:
        """Solve a model using HiGHS via OR-Tools"""
        
        try:
            # Create HiGHS solver via OR-Tools
            self.solver = pywraplp.Solver.CreateSolver('HIGHS')
            
            if not self.solver:
                return {
                    'status': 'error',
                    'error': 'HiGHS solver not available',
                    'message': 'Could not create HiGHS solver via OR-Tools'
                }
            
            logger.info("✅ HiGHS solver created via OR-Tools")
            
            # Clear any existing variables/constraints
            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)
                    
                    # Create variable based on type
                    if var_type == 'binary':
                        var = self.solver.BoolVar(name)
                        logger.info(f"Added binary variable: {name}")
                    elif var_type == 'integer':
                        var = self.solver.IntVar(lower_bound, upper_bound, name)
                        logger.info(f"Added integer variable: {name} [{lower_bound}, {upper_bound}]")
                    else:  # continuous
                        var = self.solver.NumVar(lower_bound, upper_bound, name)
                        logger.info(f"Added continuous variable: {name} [{lower_bound}, {upper_bound}]")
                    
                    self.variables[name] = var
            
            # 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_terms = self._parse_objective_expression(obj_expression)
                
                # Build objective
                objective = self.solver.Objective()
                for coeff, var_name in obj_terms:
                    if var_name in self.variables:
                        objective.SetCoefficient(self.variables[var_name], coeff)
                
                if obj_type == 'maximize':
                    objective.SetMaximization()
                else:
                    objective.SetMinimization()
                
                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
                    constraint = self._parse_constraint_expression(expression)
                    
                    if constraint:
                        self.constraints.append(constraint)
                        logger.info(f"Added constraint: {expression}")
            
            # Solve the model
            logger.info("Solving HiGHS model via OR-Tools...")
            status = self.solver.Solve()
            
            # Process results
            if status == pywraplp.Solver.OPTIMAL:
                # Extract solution
                optimal_values = {}
                for name, var in self.variables.items():
                    optimal_values[name] = var.solution_value()
                
                objective_value = self.solver.Objective().Value()
                
                return {
                    'status': 'optimal',
                    'objective_value': objective_value,
                    'optimal_values': optimal_values,
                    'solve_time': self.solver.WallTime() / 1000.0,  # Convert to seconds
                    'solver': 'HiGHS-via-OR-Tools',
                    'message': 'Solved successfully with HiGHS via OR-Tools'
                }
            elif status == pywraplp.Solver.INFEASIBLE:
                return {
                    'status': 'infeasible',
                    'error': 'Model is infeasible',
                    'message': 'No feasible solution exists'
                }
            elif status == pywraplp.Solver.UNBOUNDED:
                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 -float('inf')
                upper = float(parts[1]) if parts[1] != 'inf' else float('inf')
                return (lower, upper)
            else:
                # Try to parse as single number
                val = float(bounds_str)
                return (val, val)
        except:
            return (0, float('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 and variables
            terms = expression.replace(' ', '').split('+')
            obj_terms = []
            
            for term in terms:
                if '*' in term:
                    coeff_str, var_name = term.split('*')
                    coeff = float(coeff_str)
                    obj_terms.append((coeff, var_name))
                else:
                    # Assume coefficient is 1
                    obj_terms.append((1.0, term))
            
            return obj_terms
        except:
            return [(1.0, 'x')]  # Default term
    
    def _parse_constraint_expression(self, expression: str) -> Optional[object]:
        """Parse constraint expression like 'x_ijt <= 200*y_ijt'"""
        try:
            # For now, implement simple constraint parsing
            # This is a simplified version - in practice, you'd need more sophisticated parsing
            
            if '<=' in expression:
                lhs, rhs = expression.split('<=')
                rhs_val = float(rhs.strip())
                
                # Create constraint: lhs <= rhs_val
                constraint = self.solver.Constraint(0, rhs_val)
                
                # Parse LHS to add coefficients
                # For now, handle simple cases like "x_ijt" or "18*x_ijt"
                lhs_terms = self._parse_expression_terms(lhs.strip())
                for coeff, var_name in lhs_terms:
                    if var_name in self.variables:
                        constraint.SetCoefficient(self.variables[var_name], coeff)
                
                return constraint
                
            elif '>=' in expression:
                lhs, rhs = expression.split('>=')
                rhs_val = float(rhs.strip())
                
                # Create constraint: lhs >= rhs_val
                constraint = self.solver.Constraint(rhs_val, float('inf'))
                
                # Parse LHS to add coefficients
                lhs_terms = self._parse_expression_terms(lhs.strip())
                for coeff, var_name in lhs_terms:
                    if var_name in self.variables:
                        constraint.SetCoefficient(self.variables[var_name], coeff)
                
                return constraint
                
            elif '=' in expression:
                lhs, rhs = expression.split('=')
                rhs_val = float(rhs.strip())
                
                # Create constraint: lhs = rhs_val
                constraint = self.solver.Constraint(rhs_val, rhs_val)
                
                # Parse LHS to add coefficients
                lhs_terms = self._parse_expression_terms(lhs.strip())
                for coeff, var_name in lhs_terms:
                    if var_name in self.variables:
                        constraint.SetCoefficient(self.variables[var_name], coeff)
                
                return constraint
            else:
                return None
        except Exception as e:
            logger.warning(f"Failed to parse constraint '{expression}': {e}")
            return None
    
    def _parse_expression_terms(self, expression: str) -> list:
        """Parse expression terms like '18*x_ijt' or 'x_ijt'"""
        try:
            terms = []
            
            # Handle simple cases first
            if '*' in expression:
                # Format: "coeff*var"
                coeff_str, var_name = expression.split('*')
                coeff = float(coeff_str.strip())
                terms.append((coeff, var_name.strip()))
            else:
                # Format: "var" (coefficient is 1)
                terms.append((1.0, expression.strip()))
            
            return terms
        except Exception as e:
            logger.warning(f"Failed to parse expression terms '{expression}': {e}")
            return [(1.0, expression)]
