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ai_import_quary/import_keywords.py

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"""
从Excel文件导入关键词到baidu_keyword表
"""
import pandas as pd
import logging
import argparse
import os
import time
import glob
import shutil
from database_config import DatabaseManager
from datetime import datetime
# 配置日志
logging.basicConfig(
level=logging.DEBUG,
format='%(asctime)s - %(levelname)s - %(message)s'
)
logger = logging.getLogger(__name__)
def read_excel_keywords_with_department(excel_path, query_column='query', department_column='科室'):
"""
读取Excel文件中的关键词和部门信息
Args:
excel_path: Excel文件路径
query_column: query列名默认为'query'
department_column: 部门列名默认为'科室'如果为None则不读取部门信息
Returns:
包含(keyword, department)元组的列表如果没有部门列则department为None
"""
try:
# 读取Excel文件
df = pd.read_excel(excel_path)
logger.info(f"成功读取Excel文件: {excel_path}")
logger.info(f"Excel文件包含 {len(df)} 行数据")
logger.info(f"Excel列名: {df.columns.tolist()}")
# 检查query列是否存在
if query_column not in df.columns:
logger.error(f"未找到query列: {query_column}")
return []
# 检查是否有部门列
has_department = department_column and department_column in df.columns
if department_column and not has_department:
logger.warning(f"未找到department列: {department_column},将不使用部门信息")
# 获取query数据
query_data = df[query_column].dropna()
query_list = query_data.tolist()
# 根据是否有部门列,组合数据
keyword_dept_pairs = []
if has_department:
# 有部门列,获取部门数据
department_data = df[department_column].dropna()
# 对齐数据长度,取最短长度
min_length = min(len(query_data), len(department_data))
query_list = query_data.iloc[:min_length].tolist()
department_list = department_data.iloc[:min_length].tolist()
for i in range(min_length):
keyword = str(query_list[i]).strip()
department = str(department_list[i]).strip()
if keyword and department: # 确保关键词和部门都不为空
keyword_dept_pairs.append((keyword, department))
else:
# 没有部门列,只提取关键词
logger.info("没有部门列,将只导入关键词,不指定科室")
for keyword in query_list:
keyword = str(keyword).strip()
if keyword: # 确保关键词不为空
keyword_dept_pairs.append((keyword, None))
# 去除重复项,保留第一个出现的组合
seen = set()
unique_keyword_dept_pairs = []
for keyword, dept in keyword_dept_pairs:
if (keyword, dept) not in seen:
seen.add((keyword, dept))
unique_keyword_dept_pairs.append((keyword, dept))
if has_department:
logger.info(f"提取到 {len(unique_keyword_dept_pairs)} 个唯一的关键词-部门组合")
else:
logger.info(f"提取到 {len(unique_keyword_dept_pairs)} 个唯一的关键词")
return unique_keyword_dept_pairs
except Exception as e:
logger.error(f"读取Excel文件失败: {e}", exc_info=True)
raise
def get_department_id(db_manager, department_name):
"""
根据科室名称从ai_departments表中获取对应的ID
Args:
db_manager: 数据库管理器实例
department_name: 科室名称
Returns:
科室ID如果未找到则抛出异常
"""
try:
# 查询科室ID - 使用正确的字段名
sql = "SELECT id FROM ai_departments WHERE department_name = %s"
result = db_manager.execute_query(sql, (department_name,), fetch_one=True)
if result:
return result[0] # 返回ID
else:
error_msg = f"未找到科室 '{department_name}' 的ID请先在ai_departments表中添加该科室"
logger.error(error_msg)
raise ValueError(error_msg)
except Exception as e:
logger.error(f"查询科室ID失败: {e}", exc_info=True)
raise
def get_author_info_by_department(db_manager, department_id):
"""
根据科室ID从ai_authors表中获取任一符合条件的作者信息
Args:
db_manager: 数据库管理器实例
department_id: 科室ID
Returns:
(author_id, author_name) 元组如果未找到则返回 (None, None)
"""
try:
# 查询符合条件的作者信息
sql = "SELECT id, author_name FROM ai_authors WHERE department_id = %s AND status = 'active' AND daily_post_max > 0 LIMIT 1"
result = db_manager.execute_query(sql, (department_id,), fetch_one=True)
if result:
return result[0], result[1] # 返回 author_id, author_name
else:
logger.warning(f"未找到科室ID {department_id} 下符合条件的活跃作者")
return None, None
except Exception as e:
logger.error(f"查询作者信息失败: {e}", exc_info=True)
return None, None
def import_keywords_to_db(db_manager, keyword_dept_pairs, seed_id=9999, seed_name='手动提交', crawled=1, batch_size=100, sleep_seconds=0.1):
"""
将关键词批量导入到baidu_keyword表
Args:
db_manager: 数据库管理器实例
keyword_dept_pairs: 包含(keyword, department)元组的列表
seed_id: 种子ID默认9999
seed_name: 种子名称默认'手动提交'
crawled: 是否已爬取默认1
batch_size: 日志批次大小每多少条记录输出一次进度
sleep_seconds: 每条记录间隔睡眠时间默认0.1
Returns:
成功导入的数量
"""
if not keyword_dept_pairs:
logger.warning("没有关键词需要导入")
return 0
try:
logger.info(f"开始导入 {len(keyword_dept_pairs)} 个关键词-部门组合到数据库...")
logger.info("采用逐条查询+插入模式,避免重复")
# 准备SQL语句
check_sql = "SELECT COUNT(*) FROM baidu_keyword WHERE keyword = %s"
insert_sql = """
INSERT INTO baidu_keyword (keyword, seed_id, seed_name, crawled, parents_id, created_at, department, department_id, query_status, author_id, author_name)
VALUES (%s, %s, %s, %s, 0, NOW(), %s, %s, %s, %s, %s)
"""
success_count = 0
skip_count = 0
failed_count = 0
# 逐条处理
for idx, (keyword, department) in enumerate(keyword_dept_pairs, 1):
try:
if department:
logger.debug(f'[调试] 处理第 {idx}/{len(keyword_dept_pairs)} 条: {keyword}, 部门: {department}')
else:
logger.debug(f'[调试] 处理第 {idx}/{len(keyword_dept_pairs)} 条: {keyword}, 无部门信息')
# 1. 如果有部门信息获取科室ID和作者信息
if department:
dept_id = get_department_id(db_manager, department)
author_id, author_name = get_author_info_by_department(db_manager, dept_id)
else:
# 没有部门信息使用默认值空字符串而不是None避免数据库NOT NULL约束
department = ''
dept_id = 0
author_id = 0
author_name = ''
# 2. 查询关键词是否存在
result = db_manager.execute_query(check_sql, (keyword,), fetch_one=True)
exists = result[0] > 0 if result else False
if exists:
skip_count += 1
logger.debug(f'[调试] 关键词已存在,跳过: {keyword}')
else:
# 3. 不存在则插入
if department:
logger.debug(f'[调试] 准备插入: {keyword}, 部门: {department}, 部门ID: {dept_id}, 作者ID: {author_id}, 作者名: {author_name}, query_status: manual_review')
else:
logger.debug(f'[调试] 准备插入: {keyword}, 无部门信息, query_status: manual_review')
affected = db_manager.execute_update(
insert_sql,
(keyword, seed_id, seed_name, crawled, department, dept_id, 'manual_review', author_id, author_name),
autocommit=True
)
if affected > 0:
success_count += 1
if department:
logger.debug(f'[调试] 插入成功: {keyword}, 部门: {department}, 部门ID: {dept_id}, 作者ID: {author_id}, 作者名: {author_name}, query_status: manual_review')
else:
logger.debug(f'[调试] 插入成功: {keyword}, 无部门信息, query_status: manual_review')
# 5. 输出进度
if idx % batch_size == 0 or idx == len(keyword_dept_pairs):
progress = (idx / len(keyword_dept_pairs)) * 100
logger.info(f'[插入进度] {idx}/{len(keyword_dept_pairs)} ({progress:.1f}%) | 成功: {success_count} | 跳过: {skip_count} | 失败: {failed_count}')
# 6. 每次执行完sleep
time.sleep(sleep_seconds)
except ValueError as ve:
# 遇到科室不存在的错误,停止整个导入过程
logger.error(f'[错误] 第 {idx} 条记录遇到错误: {ve}')
raise ve
except Exception as e:
failed_count += 1
logger.warning(f'[调试] 处理失败 [{idx}/{len(keyword_dept_pairs)}]: keyword={keyword}, 部门={department},错误:{e}')
logger.info(f"导入完成!成功插入: {success_count} | 跳过已存在: {skip_count} | 失败: {failed_count}")
return success_count
except Exception as e:
logger.error(f"导入关键词失败: {e}", exc_info=True)
raise
def main():
"""主函数"""
# 检查query_upload文件夹是否存在
upload_folder = 'query_upload'
if not os.path.exists(upload_folder):
logger.error(f'未找到 {upload_folder} 文件夹')
return
# 查找Excel文件
excel_patterns = ['*.xlsx', '*.xls']
excel_files = []
for pattern in excel_patterns:
excel_files.extend(glob.glob(os.path.join(upload_folder, pattern)))
excel_files.extend(glob.glob(os.path.join(upload_folder, pattern.upper())))
if not excel_files:
logger.error(f'{upload_folder} 文件夹中未找到Excel文件 (.xlsx 或 .xls)')
return
logger.info(f'{upload_folder} 文件夹中找到 {len(excel_files)} 个Excel文件:')
for i, file_path in enumerate(excel_files, 1):
logger.info(f' {i}. {os.path.basename(file_path)}')
# 如果只有一个文件,直接使用;如果有多个文件,让用户选择
if len(excel_files) == 1:
excel_path = excel_files[0]
logger.info(f'自动选择文件: {os.path.basename(excel_path)}')
else:
print('\n找到多个Excel文件请选择要使用的文件:')
for i, file_path in enumerate(excel_files, 1):
print(f' {i}. {os.path.basename(file_path)}')
while True:
try:
choice = int(input(f'请选择文件 (1-{len(excel_files)}): '))
if 1 <= choice <= len(excel_files):
excel_path = excel_files[choice - 1]
break
else:
print(f'请输入1到{len(excel_files)}之间的数字')
except ValueError:
print('请输入有效的数字')
# 从database_config.py读取默认配置
from database_config import DB_CONFIG
# 解析命令行参数
parser = argparse.ArgumentParser(description='导入Excel关键词到baidu_keyword表')
parser.add_argument('--host', default=DB_CONFIG['host'], help='数据库主机')
parser.add_argument('--port', type=int, default=3306, help='数据库端口')
parser.add_argument('--user', default=DB_CONFIG['user'], help='数据库用户名')
parser.add_argument('--password', default=DB_CONFIG['password'], help='数据库密码')
parser.add_argument('--database', default=DB_CONFIG['database'], help='数据库名')
parser.add_argument('--batch-size', type=int, default=1, help='日志批次大小')
parser.add_argument('--sleep', type=float, default=0.1, help='每条记录间隔时间(秒)')
parser.add_argument('--query-column', default='query', help='Excel中的query列名默认为query')
parser.add_argument('--dept-column', default='科室', help='Excel中的部门列名默认为科室')
parser.add_argument('--seed-id', type=int, default=9999, help='种子ID')
parser.add_argument('--seed-name', default='手动提交', help='种子名称')
# 移除了命令行参数,改为交互式询问
args = parser.parse_args()
# Excel文件路径已经在上面确定了
# excel_path 已经被赋值
# 创建数据库连接配置
db_config = {
'host': args.host,
'port': args.port,
'user': args.user,
'password': args.password,
'database': args.database,
'charset': DB_CONFIG['charset'] # 使用database_config.py中的字符集配置
}
logger.info("=" * 60)
logger.info("开始导入关键词到baidu_keyword表")
logger.info(f"数据库配置: {args.user}@{args.host}:{args.port}/{args.database}")
logger.info(f"Excel文件: {os.path.basename(excel_path)}")
logger.info("=" * 60)
# 创建数据库管理器
db_manager = DatabaseManager(db_config)
try:
# 1. 读取Excel文件
keyword_dept_pairs = read_excel_keywords_with_department(excel_path, args.query_column, args.dept_column)
# 询问用户是要导入全部数据还是部分测试
print(f"\nExcel中共有 {len(keyword_dept_pairs)} 条数据")
while True:
choice = input("请选择导入方式: A) 全部导入 B) 测试模式(输入前N条数据): ").strip().upper()
if choice == 'A':
# 全部导入
break
elif choice == 'B':
try:
test_count = int(input(f"请输入要测试的条数 (1-{len(keyword_dept_pairs)}): "))
if 1 <= test_count <= len(keyword_dept_pairs):
keyword_dept_pairs = keyword_dept_pairs[:test_count]
print(f"已选择导入前 {test_count} 条数据进行测试")
break
else:
print(f"输入超出范围请输入1到{len(keyword_dept_pairs)}之间的数字")
except ValueError:
print("请输入有效的数字")
else:
print("请输入 A 或 B")
if not keyword_dept_pairs:
logger.warning("没有可导入的关键词,程序退出")
return
# 打印前10个关键词-部门组合作为预览
logger.info(f"\n关键词-部门预览前10个:")
for i, (keyword, department) in enumerate(keyword_dept_pairs[:10], 1):
logger.info(f" {i}. {keyword} (部门: {department})")
if len(keyword_dept_pairs) > 10:
logger.info(f" ... 还有 {len(keyword_dept_pairs) - 10} 个关键词-部门组合")
# 2. 确认导入
print("\n" + "=" * 60)
print(f"即将导入 {len(keyword_dept_pairs)} 个关键词-部门组合到 baidu_keyword 表")
print(f"配置: seed_id={args.seed_id}, seed_name='{args.seed_name}', crawled=1")
confirm = input("确认导入? (y/n): ").strip().lower()
if confirm != 'y':
logger.info("用户取消导入")
return
# 3. 执行导入
success_count = import_keywords_to_db(
db_manager=db_manager,
keyword_dept_pairs=keyword_dept_pairs,
seed_id=args.seed_id,
seed_name=args.seed_name,
crawled=1,
batch_size=args.batch_size,
sleep_seconds=args.sleep
)
logger.info("=" * 60)
logger.info(f"✓ 导入完成!共成功导入 {success_count} 个关键词")
logger.info("=" * 60)
# 运行完成后自动删除 query_upload 文件夹中的所有文件(仅在成功时)
try:
upload_folder = 'query_upload'
for filename in os.listdir(upload_folder):
file_path = os.path.join(upload_folder, filename)
if os.path.isfile(file_path):
os.remove(file_path)
logger.info(f'已删除文件: {filename}')
logger.info('已清理 query_upload 文件夹中的所有文件')
except Exception as e:
logger.error(f'清理 query_upload 文件夹时出错: {e}')
except Exception as e:
logger.error(f"✗ 导入过程出错: {e}", exc_info=True)
logger.info("=" * 60)
logger.info("✗ 导入失败")
logger.info("=" * 60)
# 导入失败时不删除源文件,以便排查问题
if __name__ == '__main__':
main()