import json
import logging
import re
from flask import Flask, request, jsonify
from routes import app
logging.basicConfig(level=logging.INFO)
logger = logging.getLogger(__name__)

def parse_markdown_table(table_str):
    """
    Parses a markdown table string and returns a list of lab configurations.
    Each configuration is a dictionary with keys:
        - lab: int
        - cell_counts: list of ints
        - increment: str
        - condition: list of three ints
    """
    lines = table_str.strip().split('\n')
    # Remove header and separator
    data_lines = lines[2:]
    lab_configs = {}
    for line in data_lines:
        # Split by '|' and strip spaces
        parts = [part.strip() for part in line.strip().split('|')]
        if len(parts) < 4:
            continue  # Skip incomplete lines
        lab_str, cell_counts_str, increment_str, condition_str = parts[:4]
        lab = int(lab_str)
        # Extract cell counts
        cell_counts = list(map(int, cell_counts_str.split()))
        # Extract increment expression
        increment = increment_str
        # Extract condition
        # Use regular expression to extract numbers, considering multiple spaces
        condition_numbers = re.findall(r'\d+', condition_str)
        condition = list(map(int, condition_numbers))
        if len(condition) != 3:
            raise ValueError("Condition does not have exactly three numbers.")
        # Store in lab_configs
        lab_configs[lab] = {
            'cell_counts': cell_counts,
            'increment': increment,
            'condition': condition
        }
    return lab_configs

def apply_increment(count, expr):
    """
    Applies the increment expression to the given count.
    """
    tokens = expr.split()
    if len(tokens) != 3:
        raise ValueError(f"Invalid increment expression: {expr}")
    op1, operator, op2 = tokens
    if op1 != 'count':
        raise ValueError(f"Invalid operand: {op1}")
    if op2 == 'count':
        operand = count
    else:
        operand = int(op2)
    if operator == '+':
        return count + operand
    elif operator == '*':
        return count * operand
    else:
        raise ValueError(f"Unknown operator: {operator}")

def evaluate_condition(count, condition):
    """
    Evaluates the condition and returns the target lab.
    Condition is a list of three integers: [divisor, lab_if_true, lab_if_false]
    """
    divisor, lab_if_true, lab_if_false = condition
    if divisor == 0:
        raise ValueError("Divisor in condition cannot be zero.")
    if count % divisor == 0:
        return lab_if_true
    else:
        return lab_if_false

@app.route('/lab_work', methods=['POST'])
def lab_work():
    try:
        data = request.get_json()
        if not isinstance(data, list):
            return jsonify({"error": "Input data should be a list of markdown tables."}), 400
        test_cases = data  # List of markdown table strings
        output = []
        for idx, table_str in enumerate(test_cases):
            logger.info(f"Processing Test Case {idx + 1}")
            # Parse the table
            lab_configs = parse_markdown_table(table_str)
            if not lab_configs:
                return jsonify({"error": f"No lab configurations found in Test Case {idx + 1}."}), 400
            # Determine the number of labs
            lab_numbers = sorted(lab_configs.keys())
            num_labs = len(lab_numbers)
            max_lab_number = max(lab_numbers)
            # Initialize labs data
            labs = {}
            for lab in lab_numbers:
                labs[lab] = {
                    'increment': lab_configs[lab]['increment'],
                    'condition': lab_configs[lab]['condition'],
                    'current_dishes': lab_configs[lab]['cell_counts'][:],  # Make a copy
                    'next_day_dishes': []
                }
            # Initialize analysis counts
            analysis_counts = {lab: 0 for lab in lab_numbers}
            # Initialize records at intervals
            records = {}
            # Simulate 10,000 days
            for day in range(1, 10001):
                # Initialize processing lists for the day
                processing_lists = {lab: labs[lab]['current_dishes'][:] for lab in lab_numbers}
                # Clear current_dishes for receiving new dishes passed to labs already processed
                for lab in lab_numbers:
                    labs[lab]['current_dishes'] = []
                # Process labs in order
                for lab in lab_numbers:
                    dishes_to_process = processing_lists[lab]
                    for dish in dishes_to_process:
                        # Apply increment
                        try:
                            updated_count = apply_increment(dish, labs[lab]['increment'])
                        except ValueError as ve:
                            return jsonify({"error": f"Error in increment expression for lab {lab}: {str(ve)}"}), 400
                        # Evaluate condition
                        try:
                            target_lab = evaluate_condition(updated_count, labs[lab]['condition'])
                        except ValueError as ve:
                            return jsonify({"error": f"Error in condition for lab {lab}: {str(ve)}"}), 400
                        # Increment analysis count
                        analysis_counts[lab] += 1
                        # Assign to target lab
                        if target_lab not in lab_configs:
                            return jsonify({"error": f"Target lab {target_lab} does not exist in Test Case {idx + 1}."}), 400
                        if target_lab > lab:
                            # Target lab has not been processed yet today
                            processing_lists[target_lab].append(updated_count)
                        else:
                            # Target lab has already been processed today
                            labs[target_lab]['next_day_dishes'].append(updated_count)
                # After processing all labs, update current_dishes for next day
                for lab in lab_numbers:
                    # Append dishes passed to labs already processed today
                    labs[lab]['current_dishes'].extend(labs[lab]['next_day_dishes'])
                    # Clear next_day_dishes for the next day
                    labs[lab]['next_day_dishes'] = []
                # Record counts at intervals of 1000 days
                if day % 1000 == 0:
                    # Prepare the counts list ordered by lab numbers
                    counts_list = [analysis_counts[lab] for lab in lab_numbers]
                    records[str(day)] = counts_list
                    logger.info(f"Recorded counts for day {day}: {counts_list}")
            # After simulation, prepare the output for this test case
            output.append(records)
        return jsonify(output), 200
    except Exception as e:
        logger.error(f"An error occurred: {str(e)}")
        return jsonify({"error": f"An error occurred: {str(e)}"}), 500