220 lines
6.7 KiB
Python
220 lines
6.7 KiB
Python
#!/usr/bin/env python3
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"""
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微信用户反馈每分钟同步到飞书收集表格
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"""
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import os
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import json
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import pymysql
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import subprocess
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from datetime import datetime
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# 配置
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LOG_FILE = "/var/log/sync_wechat_feedback.log"
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LAST_SYNC_ID_FILE = "/root/.openclaw/workspace-xiaokui/data/last_wechat_sync_id"
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TARGET_SPREADSHEET_TOKEN = "AOxbsifk3hybRZteGowcMxNnnqc"
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TARGET_SHEET_ID = "f17380"
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LARK_CLI_CONFIG = "/root/.openclaw/credentials/xiaoyan"
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# 数据库配置
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DB_CONFIG = {
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"host": "bj-cdb-8frbdwju.sql.tencentcdb.com",
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"port": 25413,
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"user": "read_only",
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"password": "fdsfiidier^$*hjfdijjd232",
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"database": "vala_test",
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"charset": "utf8mb4"
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}
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def log(message):
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"""写日志"""
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timestamp = datetime.now().strftime("%Y-%m-%d %H:%M:%S")
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with open(LOG_FILE, "a", encoding="utf-8") as f:
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f.write(f"[{timestamp}] {message}\n")
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print(f"[{timestamp}] {message}")
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def get_last_sync_id():
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"""获取上次同步的最大ID"""
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if not os.path.exists(LAST_SYNC_ID_FILE):
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return 0
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with open(LAST_SYNC_ID_FILE, "r") as f:
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return int(f.read().strip())
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def save_last_sync_id(last_id):
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"""保存上次同步的最大ID"""
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with open(LAST_SYNC_ID_FILE, "w") as f:
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f.write(str(last_id))
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def fetch_new_wechat_data(last_id):
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"""从MySQL读取新增的微信反馈数据"""
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conn = pymysql.connect(**DB_CONFIG)
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cursor = conn.cursor()
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sql = """
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SELECT id, msg_time, sender_name, msg_type, content
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FROM wechat_group_message
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WHERE id > %s
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ORDER BY msg_time DESC
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"""
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cursor.execute(sql, (last_id,))
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rows = cursor.fetchall()
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cursor.close()
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conn.close()
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return rows
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def convert_to_sheet_format(rows):
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"""转换为飞书表格需要的格式"""
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sheet_rows = []
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max_id = 0
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for row in rows:
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id, msg_time, sender_name, msg_type, content = row
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if id > max_id:
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max_id = id
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# 整理反馈内容
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if msg_type == "text":
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feedback_content = content
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elif msg_type == "image":
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feedback_content = f"[图片] {content}"
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elif msg_type == "video":
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feedback_content = f"[视频] {content}"
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else:
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feedback_content = f"[{msg_type}] {content}"
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# 清理特殊字符
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feedback_content = feedback_content.replace("\n", " ").replace("\r", "").replace('"', '\\"')
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sheet_rows.append([
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"", # A 序号后续统一生成
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"微信-用户火线救火", # B 反馈渠道
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msg_time.strftime("%Y-%m-%d %H:%M:%S"), # C 反馈时间
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sender_name, # D 反馈人
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feedback_content, # E 反馈内容
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"", # F 备注 留空
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"" # G 回复 留空
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])
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return sheet_rows, max_id
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def get_existing_sheet_data():
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"""读取目标表格现有数据"""
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cmd = [
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"lark-cli", "sheets", "+read",
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"--spreadsheet-token", TARGET_SPREADSHEET_TOKEN,
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"--range", f"{TARGET_SHEET_ID}!A2:O",
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"--as", "bot"
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]
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env = os.environ.copy()
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env["LARKSUITE_CLI_CONFIG_DIR"] = LARK_CLI_CONFIG
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env["PATH"] = "/root/.nvm/versions/node/v24.14.0/bin:" + env.get("PATH", "")
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result = subprocess.run(cmd, env=env, capture_output=True, text=True)
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if result.returncode != 0:
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log(f"读取表格失败: {result.stderr}")
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return []
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try:
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data = json.loads(result.stdout)
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values = data.get("data", {}).get("valueRange", {}).get("values", [])
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# 过滤空行
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valid_values = [row for row in values if row and len(row) >= 1 and row[0] and row[0].strip()]
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return valid_values
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except Exception as e:
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log(f"解析表格数据失败: {str(e)}")
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return []
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def merge_and_sort_data(new_rows, existing_rows):
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"""合并新老数据，按时间倒序排列，重新生成序号，去重"""
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seen = set()
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all_rows = []
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# 合并新老数据
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for row in new_rows + existing_rows:
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if not row or len(row) < 5:
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continue
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# 去重：时间+反馈人+内容
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key = f'{row[2]}_{row[3]}_{row[4]}'
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if key in seen:
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continue
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seen.add(key)
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all_rows.append(row)
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# 按反馈时间倒序排列
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all_rows.sort(key=lambda x: x[2], reverse=True)
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# 重新生成序号
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for i, row in enumerate(all_rows):
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row[0] = str(i + 1)
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return all_rows
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def write_to_sheet(all_rows):
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"""写入数据到飞书表格"""
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if not all_rows:
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log("无数据需要写入")
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return
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# 清空原有数据
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empty_data = [["" for _ in range(15)] for _ in range(200)]
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cmd_clear = [
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"lark-cli", "sheets", "+write",
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"--spreadsheet-token", TARGET_SPREADSHEET_TOKEN,
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"--range", f"{TARGET_SHEET_ID}!A2:O201",
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"--values", json.dumps(empty_data, ensure_ascii=False),
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"--as", "bot"
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]
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env = os.environ.copy()
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env["LARKSUITE_CLI_CONFIG_DIR"] = LARK_CLI_CONFIG
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env["PATH"] = "/root/.nvm/versions/node/v24.14.0/bin:" + env.get("PATH", "")
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subprocess.run(cmd_clear, env=env, capture_output=True)
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# 写入新数据
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end_row = len(all_rows) + 1
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cmd_write = [
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"lark-cli", "sheets", "+write",
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"--spreadsheet-token", TARGET_SPREADSHEET_TOKEN,
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"--range", f"{TARGET_SHEET_ID}!A2:O{end_row}",
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"--values", json.dumps(all_rows, ensure_ascii=False),
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"--as", "bot"
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]
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result = subprocess.run(cmd_write, env=env, capture_output=True, text=True)
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if result.returncode != 0:
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log(f"写入表格失败: {result.stderr}")
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return False
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return True
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def main():
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log("=== 微信反馈同步任务开始 ===")
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last_sync_id = get_last_sync_id()
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log(f"上次同步最大ID: {last_sync_id}")
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# 获取新数据
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new_rows = fetch_new_wechat_data(last_sync_id)
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if not new_rows:
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log("无新增微信反馈数据，退出")
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return
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new_count = len(new_rows)
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log(f"发现 {new_count} 条新增微信反馈数据")
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# 转换格式
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sheet_rows, new_max_id = convert_to_sheet_format(new_rows)
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# 获取现有数据
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existing_rows = get_existing_sheet_data()
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log(f"现有表格数据量: {len(existing_rows)} 条")
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# 合并排序
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all_rows = merge_and_sort_data(sheet_rows, existing_rows)
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log(f"合并后总数据量: {len(all_rows)} 条")
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# 写入表格
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success = write_to_sheet(all_rows)
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if success:
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save_last_sync_id(new_max_id)
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log(f"✅ 同步完成，新增 {new_count} 条，总 {len(all_rows)} 条，已按时间倒序排列")
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else:
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log("❌ 同步失败")
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log("=== 同步任务完成 ===")
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if __name__ == "__main__":
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main()
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