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62 lines
2.2 KiB
62 lines
2.2 KiB
2 months ago
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"""
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profiler.py - 性能分析
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"""
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import time
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import cProfile
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import pstats
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import io
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from main import search_videos, get_cid, get_danmaku, parse_danmaku
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from analyse import filter_danmakus, count_danmakus, get_top_danmakus
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from visualization import (filter_relevant_danmakus, preprocess_danmakus,
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extract_words, remove_stopwords,
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calculate_word_frequency, generate_wordcloud)
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def run_performance_analysis():
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"""运行性能分析并记录结果。"""
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profiler = cProfile.Profile()
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profiler.enable() # 开始性能分析
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# 固定参数
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keyword = "python"
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max_results = 5
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stopwords = ['的', '是', '在', '有', '和', '这', '了', '与']
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# 获取视频列表
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video_list = search_videos(keyword, max_results)
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for video_id in video_list:
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cid = get_cid(video_id)
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danmakus = get_danmaku(video_id, cid)
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xml_content = parse_danmaku(danmakus) # 假设 get_danmaku 返回 XML
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time.sleep(2)
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# 处理弹幕
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filtered_danmakus = filter_danmakus(xml_content, keyword)
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counted_danmakus = count_danmakus(filtered_danmakus)
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get_top_danmakus(counted_danmakus)
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# 进一步分析
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relevant_danmakus = filter_relevant_danmakus(xml_content, keyword)
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preprocessed_danmakus = preprocess_danmakus(relevant_danmakus)
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words = extract_words(preprocessed_danmakus)
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words_no_stopwords = remove_stopwords(words, stopwords)
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word_freq = calculate_word_frequency(words_no_stopwords)
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generate_wordcloud(word_freq)
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profiler.disable() # 停止性能分析
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# 将性能分析结果输出到一个字符串流中
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output_stream = io.StringIO()
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sortby = pstats.SortKey.CUMULATIVE # 按照累计时间排序
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stats = pstats.Stats(profiler, stream=output_stream).sort_stats(sortby)
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stats.print_stats() # 打印结果
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# 输出性能分析结果
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with open("profiler.txt", "w", encoding='utf-8') as output_file:
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output_file.write(output_stream.getvalue())
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# 保存性能分析数据以便使用 SnakeViz 可视化
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profiler.dump_stats("output.prof")
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if __name__ == "__main__":
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run_performance_analysis()
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