143 lines
6.1 KiB
Python
143 lines
6.1 KiB
Python
import re
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def extract_data_from_log(log_file_path, output_file_path):
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# 打开并读取日志文件
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with open(log_file_path, 'r') as file:
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log_data = file.readlines()
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# 用来存储提取的所有数据
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extracted_data = []
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# 标志位，用于记录第一次检测到 "检测到小悠小悠、小悠师傅" 后
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in_detection_section = False
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last_detection_index = -1
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# 临时变量存储累积的文本
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accumulated_text = ""
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# 遍历每一行，查找符合条件的行
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for i in range(len(log_data)):
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# 查找每次 "检测到小悠小悠、小悠师傅" 出现的行
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if "检测到小悠小悠、小悠师傅" in log_data[i]:
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# 如果已经进入了一个检测区段，则提取前一个区段的数据
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if in_detection_section:
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# 提取该段 recognize_time、recognized_text 和 run_time
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recognize_times = []
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recognized_texts = []
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run_times = []
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for j in range(last_detection_index + 1, i):
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# 提取 recognize_time
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match_recognize_time = re.search(r"(recognize_time:\d+\.\d+)", log_data[j])
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if match_recognize_time:
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recognize_times.append(match_recognize_time.group(1))
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# 提取 Recognized text
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match_recognized_text = re.search(r"(Recognized text:.*?)(?=\n|$)", log_data[j])
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if match_recognized_text:
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recognized_texts.append(match_recognized_text.group(1))
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# 提取运行时间
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match_run_time = re.search(r"(运行时间：\d+\.\d+)", log_data[j])
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if match_run_time:
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run_times.append(match_run_time.group(1))
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# 提取 accumulated_text，并进行拼接，去除每个累积文本的 "accumulated_text:" 前缀
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match_accumulated_text = re.search(r"(accumulated_text:.*?)(?=\n|$)", log_data[j])
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if match_accumulated_text:
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# 去除 "accumulated_text:" 前缀并拼接
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text = match_accumulated_text.group(1).replace("accumulated_text:", "").strip()
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accumulated_text += text + " "
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# 将提取的结果添加到列表中
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extracted_data.append({
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"recognize_times": recognize_times,
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"recognized_texts": recognized_texts,
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"run_times": run_times,
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"accumulated_text": accumulated_text.strip() # 移除最后的多余空格
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})
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# 添加分隔符
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extracted_data.append('--------------------------------')
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# 标记为检测到新的 "小悠小悠"
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in_detection_section = True
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last_detection_index = i # 更新上一个检测的位置
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# 清空 accumulated_text 为下一次检测做准备
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accumulated_text = ""
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# 最后一次检查，确保从最后一个检测点到文件结束的时间也被记录
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if in_detection_section:
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recognize_times = []
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recognized_texts = []
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run_times = []
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for j in range(last_detection_index + 1, len(log_data)):
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# 提取 recognize_time
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match_recognize_time = re.search(r"(recognize_time:\d+\.\d+)", log_data[j])
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if match_recognize_time:
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recognize_times.append(match_recognize_time.group(1))
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# 提取 Recognized text
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match_recognized_text = re.search(r"(Recognized text:.*?)(?=\n|$)", log_data[j])
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if match_recognized_text:
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recognized_texts.append(match_recognized_text.group(1))
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# 提取运行时间
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match_run_time = re.search(r"(运行时间：\d+\.\d+)", log_data[j])
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if match_run_time:
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run_times.append(match_run_time.group(1))
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# 提取 accumulated_text，并进行拼接，去除每个累积文本的 "accumulated_text:" 前缀
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match_accumulated_text = re.search(r"(accumulated_text:.*?)(?=\n|$)", log_data[j])
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if match_accumulated_text:
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# 去除 "accumulated_text:" 前缀并拼接
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text = match_accumulated_text.group(1).replace("accumulated_text:", "").strip()
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accumulated_text += text + " "
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# 将提取的结果添加到列表中
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extracted_data.append({
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"recognize_times": recognize_times,
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"recognized_texts": recognized_texts,
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"run_times": run_times,
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"accumulated_text": accumulated_text.strip() # 移除最后的多余空格
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})
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# 添加分隔符
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extracted_data.append('--------------------------------')
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# 将提取的数据保存到输出文件
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with open(output_file_path, 'w') as output_file:
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for section in extracted_data:
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if isinstance(section, dict): # 如果是字典
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output_file.write("Recognize Time:\n")
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for time in section["recognize_times"]:
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output_file.write(time + '\n')
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output_file.write("\nRecognized Text:\n")
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for text in section["recognized_texts"]:
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output_file.write(text + '\n')
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output_file.write("\nModel Time:\n")
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for run_time in section["run_times"]:
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output_file.write(run_time + '\n')
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output_file.write("\nAccumulated Text:\n")
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output_file.write(section["accumulated_text"] + '\n')
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output_file.write("\n")
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elif section == '--------------------------------':
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output_file.write('--------------------------------\n')
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print(f"提取的数据已保存到 {output_file_path}")
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if __name__ == "__main__":
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# 调用函数并指定输出文件路径
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log_file_path = 'Language_2025-01-03_165625.log' # 替换为实际的日志文件路径
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output_file_path = 'extracted_data.txt' # 输出文件路径
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extract_data_from_log(log_file_path, output_file_path)
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