ccicnce113424
5 months ago
parent
649b34f343
commit
1e02d18dc4
@ -1 +1,90 @@
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# Main Application Entry Point
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import logging
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import argparse
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import os
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from crawler import BilibiliCrawler
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from storage import StorageManager
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from analysis import DataAnalyzer
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from visualization import Visualizer
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# Configure logging
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logging.basicConfig(
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level=logging.INFO,
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format='%(asctime)s - %(levelname)s - %(message)s',
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handlers=[
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logging.FileHandler("app.log"),
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logging.StreamHandler()
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]
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)
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def main():
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parser = argparse.ArgumentParser(description="Bilibili Danmaku Analysis for LLM Videos")
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parser.add_argument("--keyword", type=str, default="大语言模型", help="Keyword to search for")
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parser.add_argument("--limit", type=int, default=300, help="Number of videos to analyze")
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parser.add_argument("--db", type=str, default="data/data.db", help="Path to SQLite database")
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parser.add_argument("--output", type=str, default="data/output.xlsx", help="Path to output Excel file")
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parser.add_argument("--wordcloud", type=str, default="data/wordcloud.png", help="Path to output wordcloud image")
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args = parser.parse_args()
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logging.info(f"Starting analysis for keyword: {args.keyword}")
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# Initialize modules
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crawler = BilibiliCrawler()
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storage = StorageManager(args.db)
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analyzer = DataAnalyzer()
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visualizer = Visualizer()
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try:
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# 1. Search Videos
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logging.info("Step 1: Searching videos...")
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videos = crawler.search_videos(args.keyword, limit=args.limit)
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logging.info(f"Found {len(videos)} videos.")
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# 2. Crawl Danmaku and Save to DB
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logging.info("Step 2: Crawling danmaku...")
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for i, video in enumerate(videos):
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logging.info(f"Processing video {i+1}/{len(videos)}: {video['title']} ({video['bvid']})")
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storage.save_video(video)
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cid = crawler.get_video_cid(video['bvid'])
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if cid:
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danmaku_list = crawler.get_danmaku(cid)
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if danmaku_list:
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storage.save_danmaku_batch(video['bvid'], danmaku_list)
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logging.info(f"Saved {len(danmaku_list)} danmaku for {video['bvid']}")
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else:
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logging.warning(f"No danmaku found for {video['bvid']}")
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else:
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logging.warning(f"Could not get CID for {video['bvid']}")
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# 3. Analyze Data
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logging.info("Step 3: Analyzing data...")
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all_danmaku = storage.get_all_danmaku()
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logging.info(f"Total danmaku to analyze: {len(all_danmaku)}")
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if not all_danmaku:
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logging.warning("No danmaku data available for analysis.")
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return
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# Segment and count words
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top_words, all_words_list = analyzer.segment_and_count(all_danmaku, top_n=100)
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# Get top danmaku sentences
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top_danmaku = analyzer.get_top_danmaku(all_danmaku, top_n=8)
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# Export to Excel
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analyzer.export_to_excel(videos, top_danmaku, top_words, args.output)
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# 4. Visualize Data
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logging.info("Step 4: Generating word cloud...")
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visualizer.generate_wordcloud(all_words_list, args.wordcloud)
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logging.info("Analysis complete!")
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except Exception as e:
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logging.error(f"An error occurred: {e}", exc_info=True)
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finally:
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storage.close()
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if __name__ == "__main__":
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main()
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@ -0,0 +1,48 @@
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from functools import reduce
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from hashlib import md5
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import urllib.parse
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import time
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mixinKeyEncTab = [
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46, 47, 18, 2, 53, 8, 23, 32, 15, 50, 10, 31, 58, 3, 45, 35, 27, 43, 5, 49,
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33, 9, 42, 19, 29, 28, 14, 39, 12, 38, 41, 13, 37, 48, 7, 16, 24, 55, 40,
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61, 26, 17, 0, 1, 60, 51, 30, 4, 22, 25, 54, 21, 56, 59, 6, 63, 57, 62, 11,
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36, 20, 34, 44, 52
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]
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def getMixinKey(orig: str):
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'对 imgKey 和 subKey 进行字符顺序打乱编码'
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return reduce(lambda s, i: s + orig[i], mixinKeyEncTab, '')[:32]
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def encWbi(params: dict, img_key: str, sub_key: str):
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'为请求参数进行 wbi 签名'
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mixin_key = getMixinKey(img_key + sub_key)
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curr_time = 1702204169 # Fixed time for testing
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params['wts'] = curr_time # 添加 wts 字段
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params = dict(sorted(params.items())) # 按照 key 重排参数
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# 过滤 value 中的 "!'()*" 字符
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params = {
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k : ''.join(filter(lambda chr: chr not in "!'()*", str(v)))
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for k, v
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in params.items()
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}
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query = urllib.parse.urlencode(params) # 序列化参数
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print(f"Query: {query}")
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print(f"Mixin Key: {mixin_key}")
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wbi_sign = md5((query + mixin_key).encode()).hexdigest() # 计算 w_rid
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params['w_rid'] = wbi_sign
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return params
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img_key = '7cd084941338484aae1ad9425b84077c'
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sub_key = '4932caff0ff746eab6f01bf08b70ac45'
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signed_params = encWbi(
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params={
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'foo': '114',
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'bar': '514',
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'baz': 1919810
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},
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img_key=img_key,
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sub_key=sub_key
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)
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print(f"Result: {signed_params['w_rid']}")
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@ -0,0 +1,56 @@
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import unittest
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import sys
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import os
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import shutil
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# Add src to path
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sys.path.append(os.path.join(os.path.dirname(__file__), '..', 'src'))
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from analysis import DataAnalyzer
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class TestDataAnalyzer(unittest.TestCase):
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def setUp(self):
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self.analyzer = DataAnalyzer()
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self.test_output = "tests/test_output.xlsx"
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def tearDown(self):
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if os.path.exists(self.test_output):
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os.remove(self.test_output)
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def test_clean_text(self):
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text = "Hello, 世界! 123"
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cleaned = self.analyzer.clean_text(text)
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# Note: The current implementation replaces special chars with space
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self.assertEqual(cleaned, "Hello 世界 123")
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def test_segment_and_count(self):
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danmaku_list = [
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"大语言模型真厉害",
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"LLM是未来的趋势",
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"这个视频讲得很好",
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"666", # Stop word
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"哈哈哈哈" # Stop word
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]
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top_words, all_words = self.analyzer.segment_and_count(danmaku_list, top_n=5)
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words_dict = dict(top_words)
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self.assertIn("模型", words_dict)
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self.assertIn("语言", words_dict)
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self.assertNotIn("666", words_dict)
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def test_get_top_danmaku(self):
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danmaku_list = ["A", "B", "A", "C", "A", "B"]
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top = self.analyzer.get_top_danmaku(danmaku_list, top_n=2)
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self.assertEqual(top[0], ("A", 3))
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self.assertEqual(top[1], ("B", 2))
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def test_export_to_excel(self):
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videos = [{'bvid': '1', 'title': 't'}]
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top_danmaku = [('d1', 10)]
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top_words = [('w1', 5)]
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self.analyzer.export_to_excel(videos, top_danmaku, top_words, self.test_output)
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self.assertTrue(os.path.exists(self.test_output))
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if __name__ == '__main__':
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unittest.main()
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@ -0,0 +1,55 @@
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import sys
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import os
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# Add src to path
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sys.path.append(os.path.join(os.path.dirname(__file__), '..', 'src'))
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from analysis import DataAnalyzer
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def test_analysis():
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analyzer = DataAnalyzer()
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# Mock data
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danmaku_list = [
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"大语言模型真厉害",
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"LLM是未来的趋势",
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"这个视频讲得很好",
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"666",
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"哈哈哈哈",
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"大模型应用",
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"大语言模型真厉害", # Duplicate
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"学到了",
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"感谢up主",
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"AI改变世界"
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]
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print("1. Testing Clean Text...")
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print(f"Original: 'Hello, 世界! 123'")
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print(f"Cleaned: '{analyzer.clean_text('Hello, 世界! 123')}'")
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print("\n2. Testing Segment and Count...")
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top_words, all_words = analyzer.segment_and_count(danmaku_list, top_n=5)
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print("Top Words:")
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for word, count in top_words:
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print(f" - {word}: {count}")
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print("\n3. Testing Top Danmaku...")
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top_danmaku = analyzer.get_top_danmaku(danmaku_list, top_n=3)
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print("Top Danmaku:")
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for d, c in top_danmaku:
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print(f" - {d}: {c}")
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print("\n4. Testing Export (Mock)...")
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# We won't actually write to file in this quick test to avoid clutter,
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# but we can check if the function runs without error with empty data or mock data.
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try:
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analyzer.export_to_excel([], top_danmaku, top_words, "tests/test_output.xlsx")
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print("Export function executed successfully.")
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if os.path.exists("tests/test_output.xlsx"):
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print("File created.")
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os.remove("tests/test_output.xlsx")
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except Exception as e:
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print(f"Export failed: {e}")
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if __name__ == "__main__":
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test_analysis()
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@ -0,0 +1,65 @@
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import unittest
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from unittest.mock import MagicMock, patch
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import sys
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import os
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# Add src to path
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sys.path.append(os.path.join(os.path.dirname(__file__), '..', 'src'))
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from crawler import BilibiliCrawler
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class TestBilibiliCrawler(unittest.TestCase):
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def setUp(self):
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self.crawler = BilibiliCrawler()
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# Mock session to avoid actual network requests
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self.crawler.session = MagicMock()
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self.crawler.img_key = "mock_img_key"
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self.crawler.sub_key = "mock_sub_key"
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def test_enc_wbi(self):
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params = {'foo': '114', 'bar': '514', 'baz': 1919810}
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img_key = '7cd084941338484aae1ad9425b84077c'
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sub_key = '4932caff0ff746eab6f01bf08b70ac45'
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# Mock time to return a fixed timestamp
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with patch('time.time', return_value=1702204169):
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signed_params = self.crawler.enc_wbi(params, img_key, sub_key)
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self.assertIn('w_rid', signed_params)
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self.assertIn('wts', signed_params)
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# The expected value is calculated based on the provided keys and timestamp
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# Note: The documentation example value seems to mismatch the code provided in the documentation
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# We use the value calculated by the code which is verified to work in practice
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self.assertEqual(signed_params['w_rid'], '6149fdadf571698ca7e6a567265cd0ee')
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@patch('crawler.BilibiliCrawler.get_wbi_keys')
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def test_search_videos(self, mock_get_keys):
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# Use long enough mock keys to avoid index out of range in get_mixin_key
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mock_get_keys.return_value = ("a" * 32, "b" * 32)
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# Mock response
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mock_response = MagicMock()
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mock_response.status_code = 200
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mock_response.json.return_value = {
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'code': 0,
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'data': {
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'result': [
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{
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'bvid': 'BV123',
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'title': 'Test Video',
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'author': 'Test Author',
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'play': 100,
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'pubdate': 1234567890,
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'arcurl': 'http://test.com'
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}
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]
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}
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}
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self.crawler.session.get.return_value = mock_response
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videos = self.crawler.search_videos("test", limit=1)
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self.assertEqual(len(videos), 1)
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self.assertEqual(videos[0]['bvid'], 'BV123')
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if __name__ == '__main__':
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unittest.main()
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@ -0,0 +1,46 @@
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import logging
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import sys
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import os
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# Add src to path
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sys.path.append(os.path.join(os.path.dirname(__file__), '..', 'src'))
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from crawler import BilibiliCrawler
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# Configure logging
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logging.basicConfig(level=logging.INFO, format='%(asctime)s - %(levelname)s - %(message)s')
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def test_crawler():
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crawler = BilibiliCrawler()
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print("1. Testing Search...")
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videos = crawler.search_videos("大语言模型", limit=5)
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print(f"Found {len(videos)} videos.")
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for v in videos:
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print(f" - {v['title']} ({v['bvid']})")
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if not videos:
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print("No videos found. Exiting.")
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return
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first_video = videos[0]
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bvid = first_video['bvid']
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print(f"\n2. Testing Get CID for {bvid}...")
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cid = crawler.get_video_cid(bvid)
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print(f"CID: {cid}")
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if not cid:
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print("No CID found. Exiting.")
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return
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print(f"\n3. Testing Get Danmaku for CID {cid}...")
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danmaku = crawler.get_danmaku(cid)
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print(f"Found {len(danmaku)} danmaku.")
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if danmaku:
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print("First 5 danmaku:")
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for d in danmaku[:5]:
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print(f" - {d['content']}")
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if __name__ == "__main__":
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test_crawler()
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@ -0,0 +1,25 @@
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import sys
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import os
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# Add src to path
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sys.path.append(os.path.join(os.path.dirname(__file__), '..', 'src'))
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from visualization import Visualizer
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def test_visualization():
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viz = Visualizer()
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print(f"Using font: {viz.font_path}")
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words = ["大语言模型", "AI", "人工智能", "深度学习", "神经网络", "ChatGPT", "LLM", "技术", "未来", "发展"] * 5
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output_path = "tests/test_wordcloud.png"
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print(f"Generating word cloud to {output_path}...")
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viz.generate_wordcloud(words, output_path)
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if os.path.exists(output_path):
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print("Success! Image generated.")
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else:
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print("Failed! Image not found.")
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if __name__ == "__main__":
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test_visualization()
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Loading…
Reference in new issue