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profiler.py

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