164 lines
7.4 KiB
Python
164 lines
7.4 KiB
Python
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#!/usr/bin/env python
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# -*- coding: utf-8 -*-
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'''
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# @Time : 2025/9/28 13:36
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# @Author : reenrr
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# @File : plc_data_reader.py
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# @Description : 通用PLC数据读取线程：按配置动态处理read/read_write类型的区域
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# 支持结构化数据解析（real/int/bool等）
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'''
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import threading
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import time
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import logging
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from datetime import datetime
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from snap7.util import get_real, get_int, get_bool, get_word, get_dint # 导入snap7解析工具
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class PLCDataReaderThread(threading.Thread):
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def __init__(self, plc_client, area_config, update_interval=0.03, output_file_prefix="plc_area_"):
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"""
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初始化PLC数据读取线程（配置驱动，支持多区域）
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参数:
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plc_client: 已连接的Snap7Client实例（来自PLCManager）
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area_config: 单个区域的配置（来自config.json的plcs[].areas）
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示例：{"name":"DB100_Read", "type":"read", "db_number":100, "offset":0, "size":6000, "structure":[...]}
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update_interval: 读取间隔（秒），默认30ms
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output_file_prefix: 输出文件前缀，最终文件名为“前缀+区域名.log”
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"""
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# 线程名包含区域名，便于日志区分（如"PLCDataReader_DB100_Read"）
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thread_name = f"PLCDataReader_{area_config['name']}"
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super().__init__(name=thread_name, daemon=True)
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# 1. 核心依赖（PLC客户端+区域配置）
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self.plc_client = plc_client
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self.area_config = area_config # 动态区域配置，不再硬编码DB100
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self.area_name = area_config["name"]
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self.db_number = area_config["db_number"]
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self.offset = area_config["offset"]
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self.size = area_config["size"]
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self.area_type = area_config["type"] # 区分read/read_write/write
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# 2. 线程与输出配置
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self.update_interval = update_interval
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self.output_file = f"{output_file_prefix}DB{self.db_number}.log" # 每个区域独立文件
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# 3. 数据缓存（新增结构化数据存储）
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self.running = False
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self._latest_data = None # 格式：(timestamp, data_info, raw_bytes, parsed_data)
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self._data_lock = threading.Lock() # 线程安全锁
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# 4. 日志
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self.logger = logging.getLogger(f"PLCDataReader.{self.area_name}")
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def start(self):
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"""启动线程（验证PLC连接+读写类型适配）"""
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# 仅处理需要读的区域（read/read_write），write类型不启动
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if self.area_type not in ["read", "read_write"]:
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self.logger.warning(f"跳过启动：区域类型为{self.area_type}（无需循环读取）")
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return
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self.running = True
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super().start()
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self.logger.info(f"✅ 线程启动成功（DB{self.db_number}，{self.area_type}）")
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self.logger.info(f"🔧 配置：间隔{self.update_interval * 1000}ms，读取{self.size}字节，输出{self.output_file}")
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def stop(self):
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"""停止线程（优雅清理）"""
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self.running = False
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if self.is_alive():
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self.join(timeout=2.0)
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if self.is_alive():
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self.logger.warning("⚠️ 线程未正常退出，强制终止")
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self.logger.info(f"🛑 线程已停止（DB{self.db_number}）")
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def get_latest_data(self):
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"""
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线程安全获取最新数据（返回原始字节+解析后的结构化数据）
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返回示例：
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{
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"timestamp": "2025-09-28 10:00:00.123",
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"data_info": {"area_name":"DB100_Read", "db_number":100, "offset_range":"0-5999", "actual_length":6000},
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"raw_bytes": bytearray(b'\x00\x10...'),
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"parsed_data": {"temperature":25.5, "pressure":100, "status":True} # 解析后的字段
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}
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"""
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with self._data_lock:
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if self._latest_data is None:
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self.logger.debug("⚠️ 无最新数据缓存")
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return None
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timestamp, data_info, raw_bytes, parsed_data = self._latest_data
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return {
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"timestamp": timestamp,
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"data_info": data_info.copy(),
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"raw_bytes": raw_bytes.copy()
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}
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def run(self):
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"""线程主循环：读PLC→解析数据→更新缓存→写文件"""
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self.logger.debug(f"📌 主循环启动（DB{self.db_number}）")
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while self.running:
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cycle_start = time.time()
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try:
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# 步骤1：读取PLC区域数据（调用Snap7Client的缓存方法）
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cache_success = self.plc_client.cache_large_data_block(
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db_number=self.db_number,
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offset=self.offset,
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size=self.size
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)
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# 步骤2：处理读取结果（缓存+解析+写文件）
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if cache_success and self.plc_client.data_cache is not None:
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raw_data = self.plc_client.data_cache # 原始字节
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data_len = len(raw_data)
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timestamp = datetime.now().strftime("%Y-%m-%d %H:%M:%S.%f")[:-3]
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# 构造数据基本信息
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data_info = {
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"area_name": self.area_name,
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"db_number": self.db_number,
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"offset_range": f"0-{self.size - 1}",
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"actual_length": data_len,
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"area_type": self.area_type
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}
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# 步骤3：线程安全更新内存缓存
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with self._data_lock:
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self._latest_data = (timestamp, data_info, raw_data.copy())
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# 步骤4：写入文件（含原始字节+解析后数据）
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self._write_latest_data_to_file(timestamp, data_info, raw_data)
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else:
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self.logger.warning(f"⚠️ 数据读取失败（DB{self.db_number}），跳过本次更新")
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# 步骤6：精确控制读取间隔
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cycle_elapsed = time.time() - cycle_start
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sleep_time = max(0, self.update_interval - cycle_elapsed)
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if sleep_time > 0:
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time.sleep(sleep_time)
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except Exception as e:
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self.logger.error(f"🔴 循环读取出错: {str(e)}", exc_info=True)
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time.sleep(self.update_interval)
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def _write_latest_data_to_file(self, timestamp, data_info, raw_data):
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"""
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写入文件：含原始字节+解析后的结构化数据（每个区域独立文件）
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"""
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try:
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# 处理原始字节为列表（便于查看）
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data_list = list(raw_data) # 只显示前50字节，避免文件过大
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data_str = f"{data_list} (共{len(raw_data)}字节)"
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# 覆盖写入文件
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with open(self.output_file, "w", encoding="utf-8") as f:
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f.write(f"[{timestamp}] 📝 {self.area_name} 最新数据\n")
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f.write(
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f" - 区域信息：DB{data_info['db_number']}（{data_info['offset_range']}），类型{data_info['area_type']}\n")
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f.write(f" - 原始字节数据：{data_str}\n")
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f.write("=" * 120 + "\n")
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self.logger.debug(f"📤 最新DB{self.db_number}数据已覆盖写入文件：{self.output_file}")
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except Exception as e:
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self.logger.error(f"🔴 写入DB{self.db_number}数据到文件出错: {str(e)}", exc_info=True)
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