216 lines
7.8 KiB
Python
216 lines
7.8 KiB
Python
import pandas as pd
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import random
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from openpyxl import load_workbook
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from openpyxl.styles import Font, PatternFill, Alignment
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def calculate_id_check_code(id_17):
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"""
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计算身份证校验码（符合GB 11643-1999标准）
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:param id_17: 前17位身份证号
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:return: 校验码（0-9或X）
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"""
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# 权重因子
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weights = [7, 9, 10, 5, 8, 4, 2, 1, 6, 3, 7, 9, 10, 5, 8, 4, 2]
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# 校验码对应表
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check_codes = ['1', '0', 'X', '9', '8', '7', '6', '5', '4', '3', '2']
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# 计算加权和
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weighted_sum = sum(int(id_17[i]) * weights[i] for i in range(17))
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# 取模得到索引
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mod = weighted_sum % 11
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# 返回对应的校验码
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return check_codes[mod]
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def generate_valid_person_id(id_type):
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"""
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生成符合校验标准的证件号码
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"""
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if id_type == '身份证':
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# 6位地区码 + 4位年份 + 2位月份 + 2位日期 + 3位顺序码
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area_code = f"{random.randint(110000, 659999)}"
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birth_year = random.randint(1960, 2000)
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birth_month = f"{random.randint(1, 12):02d}"
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birth_day = f"{random.randint(1, 28):02d}"
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sequence_code = f"{random.randint(0, 999):03d}"
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# 前17位
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id_17 = f"{area_code}{birth_year}{birth_month}{birth_day}{sequence_code}"
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# 计算校验码
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check_code = calculate_id_check_code(id_17)
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return f"{id_17}{check_code}"
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else:
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# 护照、台胞证、港澳通行证：8位数字
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return str(random.randint(10000000, 99999999))
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# 验证身份证校验码
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def validate_id_check_code(person_id):
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"""
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验证身份证校验码是否正确
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"""
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if len(person_id) != 18:
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return False
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id_17 = person_id[:17]
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check_code = person_id[17]
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return calculate_id_check_code(id_17) == check_code.upper()
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# 定义数据生成规则
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last_names = ['王', '李', '张', '刘', '陈', '杨', '赵', '黄', '周', '吴', '徐', '孙', '胡', '朱', '高', '林', '何', '郭', '马', '罗']
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first_names_male = ['伟', '强', '磊', '洋', '勇', '军', '杰', '涛', '超', '明', '刚', '平', '辉', '鹏', '华', '飞', '鑫', '波', '斌', '宇']
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first_names_female = ['芳', '娜', '敏', '静', '丽', '娟', '燕', '艳', '玲', '婷', '慧', '君', '萍', '颖', '琳', '雪', '梅', '兰', '红', '霞']
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person_types = ['中介']
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person_sub_types = ['本人', '配偶', '子女', '父母', '其他']
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genders = ['M', 'F', 'O']
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id_types = ['身份证', '护照', '台胞证', '港澳通行证']
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companies = ['房屋租赁公司', '房产经纪公司', '投资咨询公司', '置业咨询公司', '不动产咨询公司', '物业管理公司', '资产评估公司', '土地评估公司', '地产代理公司', '房产咨询公司']
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positions = ['区域经理', '店长', '高级经纪人', '房产经纪人', '销售经理', '置业顾问', '物业顾问', '评估师', '业务员', '总监', '主管', None]
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relation_types = ['配偶', '子女', '父母', '兄弟姐妹', None, None]
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provinces = ['北京市', '上海市', '广东省', '江苏省', '浙江省', '四川省', '河南省', '福建省', '湖北省', '湖南省']
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districts = ['海淀区', '朝阳区', '天河区', '浦东新区', '西湖区', '黄浦区', '静安区', '徐汇区', '福田区', '罗湖区']
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streets = ['路', '大街', '大道', '街道', '巷', '广场', '大厦', '花园']
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buildings = ['1号楼', '2号楼', '3号楼', '4号楼', '5号楼', '6号楼', '7号楼', '8号楼', 'A座', 'B座']
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def generate_name(gender):
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first_names = first_names_male if gender == 'M' else first_names_female
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return random.choice(last_names) + random.choice(first_names)
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def generate_mobile():
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return f"1{random.choice([3, 5, 7, 8, 9])}{random.randint(0, 9)}{random.randint(10000000, 99999999)}"
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def generate_wechat():
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return f"wx_{''.join(random.choices('abcdefghijklmnopqrstuvwxyz0123456789', k=8))}"
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def generate_address():
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return f"{random.choice(provinces)}{random.choice(districts)}{random.choice(streets)}{random.randint(1, 100)}号"
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def generate_social_credit_code():
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return f"91{random.randint(0, 9)}{random.randint(10000000000000000, 99999999999999999)}"
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def generate_related_num_id():
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return f"ID{random.randint(10000, 99999)}"
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def generate_row(index):
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gender = random.choice(genders)
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person_sub_type = random.choice(person_sub_types)
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id_type = random.choice(id_types)
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return {
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'姓名*': generate_name(gender),
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'人员类型': '中介',
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'人员子类型': person_sub_type,
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'性别': gender,
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'证件类型': id_type,
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'证件号码*': generate_valid_person_id(id_type),
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'手机号码': generate_mobile(),
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'微信号': random.choice([generate_wechat(), None, None]),
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'联系地址': generate_address(),
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'所在公司': random.choice(companies),
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'企业统一信用码': random.choice([generate_social_credit_code(), None, None]),
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'职位': random.choice(positions),
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'关联人员ID': random.choice([generate_related_num_id(), None, None, None]),
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'关系类型': random.choice(relation_types),
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'备注': None
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}
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# 生成1000条数据
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print("正在生成1000条测试数据...")
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data = []
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for i in range(1000):
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row = generate_row(i)
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data.append(row)
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if (i + 1) % 100 == 0:
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print(f"已生成 {i + 1} 条...")
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# 创建DataFrame
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df = pd.DataFrame(data)
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# 输出文件
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output_file = 'doc/test-data/intermediary/intermediary_test_data_1000_valid.xlsx'
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# 保存到Excel
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df.to_excel(output_file, index=False, engine='openpyxl')
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# 格式化Excel文件
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wb = load_workbook(output_file)
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ws = wb.active
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# 设置列宽
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ws.column_dimensions['A'].width = 15
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ws.column_dimensions['B'].width = 12
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ws.column_dimensions['C'].width = 12
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ws.column_dimensions['D'].width = 8
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ws.column_dimensions['E'].width = 12
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ws.column_dimensions['F'].width = 20
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ws.column_dimensions['G'].width = 15
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ws.column_dimensions['H'].width = 15
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ws.column_dimensions['I'].width = 30
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ws.column_dimensions['J'].width = 20
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ws.column_dimensions['K'].width = 20
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ws.column_dimensions['L'].width = 12
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ws.column_dimensions['M'].width = 15
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ws.column_dimensions['N'].width = 12
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ws.column_dimensions['O'].width = 20
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# 设置表头样式
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header_fill = PatternFill(start_color='D3D3D3', end_color='D3D3D3', fill_type='solid')
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header_font = Font(bold=True)
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for cell in ws[1]:
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cell.fill = header_fill
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cell.font = header_font
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cell.alignment = Alignment(horizontal='center', vertical='center')
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# 冻结首行
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ws.freeze_panes = 'A2'
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wb.save(output_file)
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# 验证身份证校验码
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print("\n正在验证身份证校验码...")
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df_read = pd.read_excel(output_file)
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id_cards = df_read[df_read['证件类型'] == '身份证']['证件号码*']
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valid_count = 0
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invalid_count = 0
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invalid_ids = []
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for idx, person_id in id_cards.items():
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if validate_id_check_code(str(person_id)):
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valid_count += 1
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else:
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invalid_count += 1
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invalid_ids.append(person_id)
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print(f"\n✅ 成功生成1000条测试数据到: {output_file}")
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print(f"\n=== 身份证校验码验证 ===")
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print(f"身份证总数: {len(id_cards)}条")
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print(f"校验正确: {valid_count}条 ✅")
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print(f"校验错误: {invalid_count}条")
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if invalid_count > 0:
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print(f"\n错误的身份证号:")
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for pid in invalid_ids[:10]:
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print(f" {pid}")
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print(f"\n=== 数据统计 ===")
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print(f"人员类型: {df_read['人员类型'].unique()}")
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print(f"性别分布: {dict(df_read['性别'].value_counts())}")
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print(f"证件类型分布: {dict(df_read['证件类型'].value_counts())}")
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print(f"人员子类型分布: {dict(df_read['人员子类型'].value_counts())}")
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print(f"\n=== 身份证号码样本（已验证校验码）===")
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valid_id_samples = id_cards.head(5).tolist()
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for sample in valid_id_samples:
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is_valid = "✅" if validate_id_check_code(str(sample)) else "❌"
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print(f"{sample} {is_valid}")
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