#!/usr/bin/env python3
# -*- coding: utf-8 -*-
"""
谛听多维报告 PDF 生成器
使用 WeasyPrint 将 HTML 模板转换为 PDF
"""

import json
import re
from pathlib import Path
from typing import Dict, Any, Optional
from jinja2 import Environment, FileSystemLoader, select_autoescape

# 尝试导入 WeasyPrint，提供友好的错误提示
try:
    from weasyprint import HTML, CSS
    from weasyprint.text.fonts import FontConfiguration
    WEASYPRINT_AVAILABLE = True
except OSError as e:
    if 'libgobject' in str(e) or 'gobject' in str(e).lower():
        WEASYPRINT_AVAILABLE = False
        WEASYPRINT_ERROR = "WeasyPrint 需要 GTK+ 运行时库。\n\n" \
                          "Windows 用户推荐使用 Conda 安装（最简单）：\n" \
                          "  conda install -c conda-forge weasyprint\n\n" \
                          "或参考 install_weasyprint_windows.md 文件中的详细安装指南。"
    else:
        WEASYPRINT_AVAILABLE = False
        WEASYPRINT_ERROR = f"WeasyPrint 导入失败: {e}\n\n请参考 install_weasyprint_windows.md 文件。"
except ImportError as e:
    WEASYPRINT_AVAILABLE = False
    WEASYPRINT_ERROR = f"WeasyPrint 未安装: {e}\n\n请运行: pip install weasyprint"


class ReportDataProcessor:
    """报告数据处理器"""
    
    @staticmethod
    def mask_name(name: Optional[str]) -> str:
        """姓名脱敏"""
        if not name:
            return ''
        if len(name) == 1:
            return '*'
        if len(name) == 2:
            return name[0] + '*'
        return name[0] + '*' * (len(name) - 2) + name[-1]
    
    @staticmethod
    def mask_phone(phone: Optional[str]) -> str:
        """手机号脱敏"""
        if not phone:
            return ''
        if len(phone) == 11:
            return phone[:3] + '****' + phone[7:]
        return phone
    
    @staticmethod
    def mask_id_card(id_card: Optional[str]) -> str:
        """身份证号脱敏"""
        if not id_card:
            return ''
        return re.sub(r'^(.{6})(?:\d+)(.{4})$', r'\1****\2', id_card)
    
    @staticmethod
    def format_interval(interval: Optional[str], unit: str = "") -> str:
        """格式化区间表达式"""
        if not interval or interval == "-" or interval == "0":
            return interval or "-"
        
        try:
            # 处理特殊格式，如 "3,6(个月)"
            if "(" in interval and ")" in interval:
                match = re.match(r'^(\d+(?:,\d+)*)\((.+)\)$', interval)
                if match:
                    numbers = [n.strip() for n in match.group(1).split(",")]
                    time_unit = match.group(2)
                    if len(numbers) == 2:
                        return f"{numbers[0]}-{numbers[1]}{time_unit}"
                    return f"{', '.join(numbers)}{time_unit}"
            
            # 处理区间表达式
            pattern = r'^([\[\(])(\d+(?:\.\d+)?),(\d+(?:\.\d+)?|\+)([\]\)])$'
            match = re.match(pattern, interval)
            
            if not match:
                return interval
            
            left_bracket, left_value, right_value, right_bracket = match.groups()
            is_left_inclusive = left_bracket == "["
            is_right_inclusive = right_bracket == "]"
            is_right_infinity = right_value == "+"
            
            if is_right_infinity:
                if is_left_inclusive:
                    return f"≥{left_value}{unit}"
                else:
                    return f">{left_value}{unit}"
            else:
                left_num = float(left_value)
                right_num = float(right_value)
                
                if left_num == right_num:
                    return f"{int(left_num)}{unit}"
                else:
                    if is_left_inclusive and is_right_inclusive:
                        return f"{int(left_num)}-{int(right_num)}{unit}"
                    elif is_left_inclusive and not is_right_inclusive:
                        return f"{int(left_num)}-{int(right_num) - 1}{unit}"
                    elif not is_left_inclusive and is_right_inclusive:
                        return f"{int(left_num) + 1}-{int(right_num)}{unit}"
                    else:
                        return f"{int(left_num) + 1}-{int(right_num) - 1}{unit}"
        except Exception as e:
            print(f"区间格式化失败: {e}, 原数据: {interval}")
            return interval
    
    @staticmethod
    def format_amount_interval(interval: Optional[str]) -> str:
        """格式化金额区间"""
        return ReportDataProcessor.format_interval(interval, "元")
    
    @staticmethod
    def format_institution_interval(interval: Optional[str]) -> str:
        """格式化机构数量区间"""
        return ReportDataProcessor.format_interval(interval, "家")
    
    @staticmethod
    def get_check_suggest_class(check_suggest: Optional[str]) -> str:
        """获取审核建议样式类"""
        suggest = check_suggest or '建议拒绝'
        if '拒绝' in suggest:
            return 'pdf-value-danger'
        elif '通过' in suggest:
            return 'pdf-value-success'
        else:
            return 'pdf-value-warning'
    
    @staticmethod
    def get_fraud_risk_level(score: int) -> str:
        """获取反欺诈风险等级"""
        if score == -1:
            return '未评估'
        if score >= 80:
            return '高风险'
        if score >= 60:
            return '中风险'
        return '低风险'
    
    @staticmethod
    def get_credit_level(score: int) -> str:
        """获取信用等级"""
        if score == -1:
            return '未评估'
        if score >= 800:
            return '信用较好'
        if score >= 500:
            return '信用良好'
        return '信用一般'
    
    @staticmethod
    def get_fraud_score_bg_class(score: int) -> str:
        """获取反欺诈评分背景样式类"""
        if score == -1:
            return 'pdf-score-default'
        if score >= 80:
            return 'pdf-score-high'
        if score >= 60:
            return 'pdf-score-medium'
        return 'pdf-score-low'
    
    @staticmethod
    def get_credit_score_bg_class(score: int) -> str:
        """获取信用评分背景样式类"""
        if score == -1:
            return 'pdf-score-default'
        if score >= 800:
            return 'pdf-score-low'
        if score >= 500:
            return 'pdf-score-info'
        return 'pdf-score-medium'
    
    @staticmethod
    def get_risk_tag_class(level: str) -> str:
        """获取风险标签样式类"""
        if level == '高风险':
            return 'pdf-tag-danger'
        if level == '中风险':
            return 'pdf-tag-warning'
        if level == '低风险':
            return 'pdf-tag-success'
        if level == '信用较好':
            return 'pdf-tag-success'
        if level == '信用良好':
            return 'pdf-tag-info'
        if level == '信用一般':
            return 'pdf-tag-warning'
        return 'pdf-tag-default'
    
    @staticmethod
    def get_risk_level_class(level: str) -> str:
        """获取风险等级样式类"""
        if level == '高风险':
            return 'pdf-score-high'
        if level == '中风险':
            return 'pdf-score-medium'
        if level == '低风险':
            return 'pdf-score-low'
        return 'pdf-score-default'
    
    @staticmethod
    def get_risk_flag_text(flag: int) -> str:
        """获取风险标识文本"""
        if flag == 1:
            return '高风险'
        if flag == 2:
            return '低风险'
        return '未查得'
    
    @staticmethod
    def get_risk_flag_tag_class(flag: int) -> str:
        """获取风险标识标签样式类"""
        if flag == 1:
            return 'pdf-tag-danger'
        if flag == 2:
            return 'pdf-tag-success'
        return 'pdf-tag-default'
    
    @staticmethod
    def get_result_text(result: Optional[str]) -> str:
        """获取验证结果文本"""
        if result == '一致':
            return '核验一致'
        if result == '不一致':
            return '核验不一致'
        return result or '未查得'
    
    @staticmethod
    def get_verification_result_class(result: Optional[str]) -> str:
        """获取验证结果样式类"""
        if result == '一致':
            return 'pdf-result-success'
        if result == '不一致':
            return 'pdf-result-danger'
        return 'pdf-result-default'
    
    @staticmethod
    def get_high_risk_count(risk_warning: Dict[str, Any]) -> int:
        """获取高风险数量"""
        high_risk_fields = [
            'idCardTwoElementMismatch', 'phoneThreeElementMismatch',
            'shortPhoneDuration', 'noPhoneDuration',
            'hasCriminalRecord', 'isEconomyFront', 'isDisrupSocial', 'isKeyPerson', 'isTrafficRelated',
            'hitHighRiskBankLastTwoYears', 'hitHighRiskNonBankLastTwoYears',
            'hitCivilCase', 'hitCriminalRisk', 'hitAdministrativeCase', 'hitPreservationReview',
            'hitExecutionCase', 'hitBankruptcyAndLiquidation', 'hitDirectlyUnderCase', 'hitCompensationCase',
            'frequentApplicationRecent', 'frequentNonBankApplications', 'highDebtPressure', 'frequentBankApplications',
            'frequentRentalApplications', 'veryFrequentRentalApplications'
        ]
        return sum(risk_warning.get(field, 0) for field in high_risk_fields)
    
    @staticmethod
    def get_middle_risk_count(risk_warning: Dict[str, Any]) -> int:
        """获取中风险数量"""
        middle_risk_fields = [
            'idCardPhoneProvinceMismatch', 'isAntiFraudInfo',
            'hitCurrentOverdue',
            'moreFrequentNonBankApplications', 'highFraudGangLevel', 'moreFrequentBankApplications'
        ]
        return sum(risk_warning.get(field, 0) for field in middle_risk_fields)
    
    @staticmethod
    def get_all_risks(risk_warning: Dict[str, Any]) -> list:
        """获取所有风险列表"""
        risks = []
        
        risk_mapping = {
            'idCardTwoElementMismatch': {
                'description': '身份证二要素信息对比结果不一致',
                'detail': '身份证号与姓名信息不匹配',
                'level': '高风险'
            },
            'phoneThreeElementMismatch': {
                'description': '手机三要素简版不一致',
                'detail': '手机号与身份证号、姓名信息不匹配',
                'level': '高风险'
            },
            'shortPhoneDuration': {
                'description': '手机在网时长极短',
                'detail': '手机号在网时间过短，存在风险',
                'level': '高风险'
            },
            'idCardPhoneProvinceMismatch': {
                'description': '身份证号手机号归属省不一致',
                'detail': '身份证归属地与手机号归属地不匹配',
                'level': '中风险'
            },
            'hasCriminalRecord': {
                'description': '该用户有前科',
                'detail': '用户存在犯罪前科记录',
                'level': '高风险'
            },
            'isKeyPerson': {
                'description': '该用户为重点人员',
                'detail': '用户被列为重点监管人员',
                'level': '高风险'
            },
            'hitHighRiskBankLastTwoYears': {
                'description': '近两年命中银行高风险',
                'detail': '近两年在银行机构存在高风险记录',
                'level': '高风险'
            },
            'hitCurrentOverdue': {
                'description': '该用户命中当前逾期',
                'detail': '用户当前存在逾期记录',
                'level': '中风险'
            },
            'frequentApplicationRecent': {
                'description': '近期申请机构极为频繁',
                'detail': '近期在多个机构频繁申请贷款',
                'level': '高风险'
            }
        }
        
        for key, info in risk_mapping.items():
            if risk_warning.get(key, 0):
                badge_class = 'pdf-tag-danger' if info['level'] == '高风险' else 'pdf-tag-warning'
                risks.append({
                    'key': key,
                    'description': info['description'],
                    'detail': info['detail'],
                    'level': info['level'],
                    'badge_class': badge_class
                })
        
        return risks
    
    @staticmethod
    def get_overdue_status_text(status: Optional[str]) -> str:
        """获取逾期状态文本"""
        if status == '逾期':
            return '逾期'
        if status == '未逾期':
            return '未逾期'
        return '未知'
    
    @staticmethod
    def get_overdue_status_tag_class(status: Optional[str]) -> str:
        """获取逾期状态标签样式类"""
        if status == '逾期':
            return 'pdf-tag-danger'
        if status == '未逾期':
            return 'pdf-tag-success'
        return 'pdf-tag-default'
    
    @staticmethod
    def get_overdue_time_text(status: Optional[str]) -> str:
        """获取逾期时间文本"""
        if status == '逾期':
            return '逾期'
        if status == '未逾期':
            return '正常'
        return '未知'
    
    @staticmethod
    def get_overdue_time_class(status: Optional[str]) -> str:
        """获取逾期时间样式类"""
        if status == '逾期':
            return 'pdf-time-danger'
        if status == '未逾期':
            return 'pdf-time-success'
        return 'pdf-time-default'


def process_judicial_data(judicial_data: Dict[str, Any]) -> Dict[str, Any]:
    """处理司法涉诉数据"""
    processor = ReportDataProcessor()
    
    # 处理不同的数据结构
    lawsuit_stat = None
    breach_case_list = []
    consumption_restriction_list = []
    
    # 如果数据在 judicial_data 下
    if 'lawsuitStat' in judicial_data:
        lawsuit_stat = judicial_data.get('lawsuitStat', {})
        breach_case_list = judicial_data.get('breachCaseList', [])
        consumption_restriction_list = judicial_data.get('consumptionRestrictionList', [])
    # 如果数据在 entout.data 下
    elif 'entout' in judicial_data:
        entout_data = judicial_data.get('entout', {}).get('data', {})
        lawsuit_stat = entout_data
        breach_case_list = judicial_data.get('breachCaseList', [])
        consumption_restriction_list = judicial_data.get('consumptionRestrictionList', [])
    # 如果直接就是 lawsuitStat 结构
    elif 'count' in judicial_data or 'civil' in judicial_data:
        lawsuit_stat = judicial_data
    
    if not lawsuit_stat:
        lawsuit_stat = {}
    
    # 处理案件统计
    count = lawsuit_stat.get('count', {})
    
    # 处理各类案件
    civil = lawsuit_stat.get('civil', {})
    criminal = lawsuit_stat.get('criminal', {})
    administrative = lawsuit_stat.get('administrative', {})
    implement = lawsuit_stat.get('implement', {})
    preservation = lawsuit_stat.get('preservation', {})
    bankrupt = lawsuit_stat.get('bankrupt', {})
    
    # 法院曝光台数据（用于替代谛听报告的法院曝光台）
    # 从 multCourtInfo 或司法涉诉数据中提取
    court_exposure = {
        'legal_cases': [],
        'execution_cases': [],
        'disin_cases': breach_case_list,
        'limit_cases': consumption_restriction_list
    }
    
    # 如果有执行案件，添加到法院曝光台
    if implement and implement.get('cases'):
        court_exposure['execution_cases'] = implement.get('cases', [])
    
    # 如果有民事案件，添加到法院曝光台
    if civil and civil.get('cases'):
        court_exposure['legal_cases'].extend(civil.get('cases', []))
    
    # 如果有刑事案件，添加到法院曝光台
    if criminal and criminal.get('cases'):
        court_exposure['legal_cases'].extend(criminal.get('cases', []))
    
    return {
        'has_data': bool(count or civil or criminal or administrative or implement or preservation or bankrupt or breach_case_list or consumption_restriction_list),
        'count': count,
        'civil': civil,
        'criminal': criminal,
        'administrative': administrative,
        'implement': implement,
        'preservation': preservation,
        'bankrupt': bankrupt,
        'breach_case_list': breach_case_list,
        'consumption_restriction_list': consumption_restriction_list,
        'court_exposure': court_exposure
    }


def process_report_data(data: Dict[str, Any], judicial_data: Optional[Dict[str, Any]] = None) -> Dict[str, Any]:
    """处理报告数据，准备模板变量"""
    processor = ReportDataProcessor()
    
    base_info = data.get('baseInfo', {})
    check_suggest = data.get('checkSuggest', '')
    fraud_score = data.get('fraudScore', -1)
    credit_score = data.get('creditScore', -1)
    verify_rule = data.get('verifyRule', '')
    fraud_rule = data.get('fraudRule', '')
    
    element_verification_detail = data.get('elementVerificationDetail', {})
    risk_warning = data.get('riskWarning', {})
    overdue_risk_product = data.get('overdueRiskProduct', {})
    loan_evaluation_verification_detail = data.get('loanEvaluationVerificationDetail', {})
    leasing_risk_assessment = data.get('leasingRiskAssessment', {})
    risk_supervision = data.get('riskSupervision', {})
    
    # 处理基本信息
    base_info_processed = {
        'name_masked': processor.mask_name(base_info.get('name')),
        'age': base_info.get('age', ''),
        'sex': base_info.get('sex', ''),
        'phone_masked': processor.mask_phone(base_info.get('phone')),
        'id_card_masked': processor.mask_id_card(base_info.get('idCard')),
        'location': base_info.get('location', ''),
        'phone_area': base_info.get('phoneArea', '')
    }
    
    # 处理要素核查
    element_verification = None
    if element_verification_detail:
        sfzeys_flag = element_verification_detail.get('sfzeysFlag', 0)
        sjsys_flag = element_verification_detail.get('sjsysFlag', 0)
        person_check_details = element_verification_detail.get('personCheckDetails', {})
        phone_check_details = element_verification_detail.get('phoneCheckDetails', {})
        
        if person_check_details or phone_check_details:
            element_verification = {
                'sfzeys_flag': sfzeys_flag,
                'sfzeys_flag_text': processor.get_risk_flag_text(sfzeys_flag),
                'sfzeys_flag_tag_class': processor.get_risk_flag_tag_class(sfzeys_flag),
                'sjsys_flag': sjsys_flag,
                'sjsys_flag_text': processor.get_risk_flag_text(sjsys_flag),
                'sjsys_flag_tag_class': processor.get_risk_flag_tag_class(sjsys_flag),
                'person_check_details': person_check_details,
                'phone_check_details': phone_check_details,
                'person_result_text': processor.get_result_text(person_check_details.get('result')),
                'person_result_class': processor.get_verification_result_class(person_check_details.get('result')),
                'phone_result_text': processor.get_result_text(phone_check_details.get('result')),
                'phone_result_class': processor.get_verification_result_class(phone_check_details.get('result'))
            }
    
    # 处理风险预警
    risk_warning_processed = None
    if risk_warning:
        risks = processor.get_all_risks(risk_warning)
        if risks or risk_warning.get('totalRiskCounts'):
            risk_warning_processed = {
                'has_data': True,
                'total_risk_counts': risk_warning.get('totalRiskCounts', 0),
                'high_risk_count': processor.get_high_risk_count(risk_warning),
                'middle_risk_count': processor.get_middle_risk_count(risk_warning),
                'level': risk_warning.get('level', '-'),
                'risks': risks
            }
    
    # 处理逾期风险
    overdue_risk_processed = None
    if overdue_risk_product:
        has_unsettled_overdue = overdue_risk_product.get('hasUnsettledOverdue')
        overdue_risk_processed = {
            'has_data': True,
            'status_text': processor.get_overdue_status_text(has_unsettled_overdue),
            'status_tag_class': processor.get_overdue_status_tag_class(has_unsettled_overdue),
            'current_overdue_institution_count': processor.format_institution_interval(
                overdue_risk_product.get('currentOverdueInstitutionCount')
            ),
            'current_overdue_amount': processor.format_amount_interval(
                overdue_risk_product.get('currentOverdueAmount')
            ),
            'settled_institution_count': processor.format_institution_interval(
                overdue_risk_product.get('settledInstitutionCount')
            ),
            'total_loan_institutions': processor.format_institution_interval(
                overdue_risk_product.get('totalLoanInstitutions')
            ),
            'time_1day_text': processor.get_overdue_time_text(overdue_risk_product.get('overdueLast1Day')),
            'time_1day_class': processor.get_overdue_time_class(overdue_risk_product.get('overdueLast1Day')),
            'time_7days_text': processor.get_overdue_time_text(overdue_risk_product.get('overdueLast7Days')),
            'time_7days_class': processor.get_overdue_time_class(overdue_risk_product.get('overdueLast7Days')),
            'time_14days_text': processor.get_overdue_time_text(overdue_risk_product.get('overdueLast14Days')),
            'time_14days_class': processor.get_overdue_time_class(overdue_risk_product.get('overdueLast14Days')),
            'time_30days_text': processor.get_overdue_time_text(overdue_risk_product.get('overdueLast30Days')),
            'time_30days_class': processor.get_overdue_time_class(overdue_risk_product.get('overdueLast30Days'))
        }
    
    # 处理借贷评估
    loan_evaluation_processed = None
    if loan_evaluation_verification_detail:
        risk_flag = loan_evaluation_verification_detail.get('riskFlag', 0)
        organ_loan_performances = loan_evaluation_verification_detail.get('organLoanPerformances', [])
        
        if organ_loan_performances:
            processed_performances = []
            for item in organ_loan_performances:
                apply_count = item.get('applyCount', '')
                type_name = '银行机构' if apply_count == '银行' else '非银机构'
                processed_performances.append({
                    'type_name': type_name,
                    'last7Day': item.get('last7Day', '0/0'),
                    'last15Day': item.get('last15Day', '0/0'),
                    'last1Month': item.get('last1Month', '0/0')
                })
            
            loan_evaluation_processed = {
                'has_data': True,
                'risk_flag': risk_flag,
                'risk_flag_text': processor.get_risk_flag_text(risk_flag),
                'risk_flag_tag_class': processor.get_risk_flag_tag_class(risk_flag),
                'organ_loan_performances': processed_performances
            }
    
    # 处理租赁风险评估
    leasing_risk_processed = None
    if leasing_risk_assessment:
        risk_flag = leasing_risk_assessment.get('riskFlag', 0)
        leasing_risk_processed = {
            'has_data': True,
            'risk_flag': risk_flag,
            'risk_flag_text': processor.get_risk_flag_text(risk_flag),
            'risk_flag_tag_class': processor.get_risk_flag_tag_class(risk_flag),
            'institution_total': leasing_risk_assessment.get('threeCInstitutionApplicationCountLast3Days', '0/0'),
            'institution_weekend': leasing_risk_assessment.get('threeCInstitutionApplicationCountLast3DaysWeekend', '0/0'),
            'institution_night': leasing_risk_assessment.get('threeCInstitutionApplicationCountLast3DaysNight', '0/0'),
            'platform_total': leasing_risk_assessment.get('threeCPlatformApplicationCountLast3Days', '0/0'),
            'platform_weekend': leasing_risk_assessment.get('threeCPlatformApplicationCountLast3DaysWeekend', '0/0'),
            'platform_night': leasing_risk_assessment.get('threeCPlatformApplicationCountLast3DaysNight', '0/0')
        }
    
    # 处理运营商核验
    operator_verification = None
    if element_verification_detail:
        online_risk_flag = element_verification_detail.get('onlineRiskFlag', 0)
        online_risk_list = element_verification_detail.get('onlineRiskList', {})
        phone_vail_risk_flag = element_verification_detail.get('phoneVailRiskFlag', 0)
        phone_vail_risks = element_verification_detail.get('phoneVailRisks', {})
        belong_risk_flag = element_verification_detail.get('belongRiskFlag', 0)
        belong_risks = element_verification_detail.get('belongRisks', {})
        
        if online_risk_list or phone_vail_risks or belong_risks:
            operator_verification = {
                'has_data': True,
                'online_risk_flag': online_risk_flag,
                'online_risk_flag_text': processor.get_risk_flag_text(online_risk_flag),
                'online_risk_flag_tag_class': processor.get_risk_flag_tag_class(online_risk_flag),
                'online_risk_list': online_risk_list,
                'phone_vail_risk_flag': phone_vail_risk_flag,
                'phone_vail_risk_flag_text': processor.get_risk_flag_text(phone_vail_risk_flag),
                'phone_vail_risk_flag_tag_class': processor.get_risk_flag_tag_class(phone_vail_risk_flag),
                'phone_vail_risks': phone_vail_risks,
                'belong_risk_flag': belong_risk_flag,
                'belong_risk_flag_text': processor.get_risk_flag_text(belong_risk_flag),
                'belong_risk_flag_tag_class': processor.get_risk_flag_tag_class(belong_risk_flag),
                'belong_risks': belong_risks
            }
    
    # 处理公安重点人员核验
    key_person_verification = None
    if element_verification_detail:
        high_risk_flag = element_verification_detail.get('highRiskFlag', 0)
        key_person_check_list = element_verification_detail.get('keyPersonCheckList', {})
        anti_fraud_info = element_verification_detail.get('antiFraudInfo', {})
        
        if key_person_check_list or anti_fraud_info:
            key_person_verification = {
                'has_data': True,
                'high_risk_flag': high_risk_flag,
                'high_risk_flag_text': processor.get_risk_flag_text(high_risk_flag),
                'high_risk_flag_tag_class': processor.get_risk_flag_tag_class(high_risk_flag),
                'key_person_check_list': key_person_check_list,
                'anti_fraud_info': anti_fraud_info
            }
    
    # 处理法院曝光台（使用司法涉诉数据）
    court_exposure_processed = None
    if judicial_data:
        judicial_processed = process_judicial_data(judicial_data)
        if judicial_processed.get('has_data'):
            court_exposure_processed = judicial_processed.get('court_exposure', {})
    
    # 处理司法涉诉数据
    judicial_processed = None
    if judicial_data:
        judicial_processed = process_judicial_data(judicial_data)
    
    # 计算风险评分相关
    fraud_risk_level = processor.get_fraud_risk_level(fraud_score)
    credit_level = processor.get_credit_level(credit_score)
    
    return {
        'base_info': base_info_processed,
        'check_suggest': check_suggest,
        'check_suggest_class': processor.get_check_suggest_class(check_suggest),
        'fraud_score': fraud_score,
        'fraud_score_display': '未命中' if fraud_score == -1 else str(fraud_score),
        'fraud_risk_level': fraud_risk_level,
        'fraud_score_bg_class': processor.get_fraud_score_bg_class(fraud_score),
        'fraud_risk_tag_class': processor.get_risk_tag_class(fraud_risk_level),
        'credit_score': credit_score,
        'credit_score_display': '未命中' if credit_score == -1 else str(credit_score),
        'credit_level': credit_level,
        'credit_score_bg_class': processor.get_credit_score_bg_class(credit_score),
        'credit_risk_tag_class': processor.get_risk_tag_class(credit_level),
        'verify_rule': verify_rule,
        'verify_rule_class': processor.get_risk_level_class(verify_rule),
        'verify_rule_tag_class': processor.get_risk_tag_class(verify_rule),
        'fraud_rule': fraud_rule,
        'fraud_rule_class': processor.get_risk_level_class(fraud_rule),
        'fraud_rule_tag_class': processor.get_risk_tag_class(fraud_rule),
        'element_verification': element_verification,
        'operator_verification': operator_verification,
        'key_person_verification': key_person_verification,
        'overdue_risk': overdue_risk_processed,
        'court_exposure': court_exposure_processed,
        'loan_evaluation': loan_evaluation_processed,
        'judicial_data': judicial_processed
    }


def generate_pdf(data_file: str, output_file: str, template_dir: str = 'templates'):
    """生成 PDF 文件"""
    # 检查 WeasyPrint 是否可用
    if not WEASYPRINT_AVAILABLE:
        print("=" * 60)
        print("错误：WeasyPrint 不可用")
        print("=" * 60)
        print(WEASYPRINT_ERROR)
        print("=" * 60)
        raise RuntimeError("WeasyPrint 未正确安装，请参考错误信息进行安装")
    
    # 读取数据文件
    with open(data_file, 'r', encoding='utf-8') as f:
        if data_file.endswith('.json'):
            json_data = json.load(f)
        else:
            raise ValueError("不支持的文件格式，请使用 JSON 文件")
    
    # 如果是数组，查找 DWBG8B4D 和司法涉诉数据
    report_data = None
    judicial_data = None
    
    if isinstance(json_data, list):
        for item in json_data:
            api_id = item.get('data', {}).get('apiID', '')
            if api_id in ['DWBG8B4D', 'CDWBG8B4D']:
                report_data = item.get('data', {}).get('data', {})
            elif api_id in ['FLXG7E8F', 'FLXG0V4B', 'CFLXG0V4B']:
                # 司法涉诉数据可能在 data.data.judicial_data 或 data.data.entout
                data_content = item.get('data', {}).get('data', {})
                if 'judicial_data' in data_content:
                    judicial_data = data_content.get('judicial_data', {})
                elif 'entout' in data_content:
                    judicial_data = data_content
                else:
                    judicial_data = data_content
    else:
        report_data = json_data
    
    if not report_data:
        raise ValueError("未找到 DWBG8B4D 数据")
    
    # 处理数据
    template_vars = process_report_data(report_data, judicial_data)
    
    # 加载模板
    env = Environment(
        loader=FileSystemLoader(template_dir),
        autoescape=select_autoescape(['html', 'xml'])
    )
    template = env.get_template('report_template.html')
    
    # 渲染 HTML
    html_content = template.render(**template_vars)
    
    # 生成 PDF
    font_config = FontConfiguration()
    html_doc = HTML(string=html_content)
    html_doc.write_pdf(output_file, font_config=font_config)
    
    print(f"PDF 已生成: {output_file}")


if __name__ == '__main__':
    import sys
    
    if len(sys.argv) < 2:
        print("用法: python generate_pdf.py <数据文件> [输出文件]")
        print("示例: python generate_pdf.py public/example.json output.pdf")
        sys.exit(1)
    
    data_file = sys.argv[1]
    output_file = sys.argv[2] if len(sys.argv) > 2 else 'report.pdf'
    
    # 确保模板目录存在
    template_dir = Path('templates')
    if not template_dir.exists():
        template_dir.mkdir()
        print(f"已创建模板目录: {template_dir}")
    
    try:
        generate_pdf(data_file, output_file)
    except Exception as e:
        print(f"生成 PDF 失败: {e}")
        import traceback
        traceback.print_exc()
        sys.exit(1)