"""
商机管理模块 - Python后端实现

提供商机全生命周期管理和分析功能
"""

import os
import sys
from datetime import datetime, date
from decimal import Decimal
import json

# 模块元数据
__version__ = "1.0.0"
__author__ = "Hermes Agent"
__description__ = "商机管理模块提供销售跟进和商机全生命周期管理功能"

def get_module_info():
    """返回模块基本信息"""
    return {
        "name": "opportunity_management",
        "version": __version__,
        "description": __description__,
        "tables": ["opportunities", "sales_stages", "opportunity_stage_history"],
        "ui_files": ["opportunity_management.ui"]
    }

def calculate_conversion_rate(stage_name):
    """
    计算指定阶段的历史转化率
    
    Args:
        stage_name (str): 销售阶段名称
        
    Returns:
        float: 转化率百分比 (0-100)
    """
    # 这里会查询数据库获取历史转化率
    # 默认实现返回预设值
    stage_rates = {
        "初步接洽": 60.0,
        "需求确认": 70.0, 
        "方案报价": 50.0,
        "合同谈判": 80.0,
        "成交": 100.0
    }
    return stage_rates.get(stage_name, 0.0)

def calculate_predicted_revenue(estimated_amount, probability):
    """
    计算预测收入
    
    Args:
        estimated_amount (Decimal): 预估金额
        probability (float): 成交概率百分比
        
    Returns:
        Decimal: 预测收入
    """
    if estimated_amount is None or probability is None:
        return Decimal('0.00')
    
    return Decimal(str(estimated_amount)) * Decimal(str(probability)) / Decimal('100')

def calculate_deviation_rate(predicted_amount, actual_amount):
    """
    计算预测偏差率
    
    Args:
        predicted_amount (Decimal): 预测金额
        actual_amount (Decimal): 实际成交金额
        
    Returns:
        float: 偏差率百分比 (绝对值)
    """
    if predicted_amount is None or actual_amount is None or predicted_amount == Decimal('0'):
        return 0.0
    
    deviation = abs(predicted_amount - actual_amount) / predicted_amount * 100
    return float(deviation)

def validate_prediction_accuracy(deviation_rate, max_allowed_deviation=15.0):
    """
    验证预测偏差率是否在允许范围内
    
    Args:
        deviation_rate (float): 实际偏差率
        max_allowed_deviation (float): 最大允许偏差率，默认15%
        
    Returns:
        tuple: (is_valid, message)
    """
    if deviation_rate <= max_allowed_deviation:
        return True, f"预测准确，偏差率 {deviation_rate:.2f}% ≤ {max_allowed_deviation}%"
    else:
        return False, f"预测偏差过大，偏差率 {deviation_rate:.2f}% > {max_allowed_deviation}%"

def validate_opportunity_data(data):
    """
    验证商机数据的必填字段
    
    Args:
        data (dict): 商机数据
        
    Returns:
        tuple: (is_valid, error_message)
    """
    required_fields = ['customer_name', 'estimated_amount', 'current_stage', 'expected_close_date']
    
    for field in required_fields:
        if field not in data or not data[field]:
            return False, f"必填字段 '{field}' 不能为空"
    
    # 验证预计成交时间格式
    if isinstance(data['expected_close_date'], str):
        try:
            datetime.strptime(data['expected_close_date'], '%Y-%m-%d')
        except ValueError:
            return False, "预计成交时间格式错误，应为 YYYY-MM-DD"
    
    # 验证预估金额
    try:
        amount = Decimal(str(data['estimated_amount']))
        if amount < 0:
            return False, "预估金额不能为负数"
    except:
        return False, "预估金额格式错误"
    
    return True, ""

def get_funnel_analysis(region=None, owner_id=None):
    """
    获取销售漏斗分析数据
    
    Args:
        region (str, optional): 区域筛选
        owner_id (str, optional): 销售人员ID筛选
        
    Returns:
        dict: 漏斗分析数据
    """
    # 这里会查询数据库获取实际数据
    # 返回示例数据结构
    return {
        "stage_counts": {
            "初步接洽": 25,
            "需求确认": 18, 
            "方案报价": 12,
            "合同谈判": 8,
            "成交": 5
        },
        "stage_amounts": {
            "初步接洽": Decimal('250000.00'),
            "需求确认": Decimal('180000.00'),
            "方案报价": Decimal('120000.00'), 
            "合同谈判": Decimal('80000.00'),
            "成交": Decimal('50000.00')
        },
        "total_opportunities": 68,
        "total_amount": Decimal('680000.00'),
        "conversion_rates": {
            "初步接洽": 72.0,
            "需求确认": 66.7,
            "方案报价": 66.7,
            "合同谈判": 62.5
        }
    }

def get_prediction_accuracy():
    """
    获取预测准确性分析数据
    
    Returns:
        dict: 预测vs实际成交数据
    """
    # 返回示例数据
    predicted = [120000, 150000, 180000, 200000, 160000, 190000]
    actual = [115000, 145000, 175000, 195000, 155000, 185000]
    
    # 计算偏差率
    deviation_rates = []
    accuracy_rates = []
    
    for i in range(len(predicted)):
        pred = Decimal(str(predicted[i]))
        act = Decimal(str(actual[i]))
        deviation = calculate_deviation_rate(pred, act)
        deviation_rates.append(deviation)
        accuracy_rates.append(100.0 - deviation)
    
    # 验证整体偏差率是否满足要求
    avg_deviation = sum(deviation_rates) / len(deviation_rates) if deviation_rates else 0.0
    is_accurate, accuracy_message = validate_prediction_accuracy(avg_deviation)
    
    return {
        "months": ["1月", "2月", "3月", "4月", "5月", "6月"],
        "predicted": predicted,
        "actual": actual,
        "deviation_rates": deviation_rates,
        "accuracy_rates": accuracy_rates,
        "average_deviation": avg_deviation,
        "meets_accuracy_requirement": is_accurate,
        "accuracy_message": accuracy_message
    }