From 6b79f3cc5ae638e56572cb96161eb55415abf6d8 Mon Sep 17 00:00:00 2001
From: pjmw9izve <2308014474@qq.com>
Date: Tue, 17 Sep 2024 12:43:02 +0800
Subject: [PATCH] ADD file via upload

---
 get_danmu_about_AI.py | 32 ++++++++++++++++++++++++++++++++
 1 file changed, 32 insertions(+)
 create mode 100644 get_danmu_about_AI.py

diff --git a/get_danmu_about_AI.py b/get_danmu_about_AI.py
new file mode 100644
index 0000000..df36942
--- /dev/null
+++ b/get_danmu_about_AI.py
@@ -0,0 +1,32 @@
+from get_danmu import get_danmu
+
+def is_related(danmu, keyword_strings):
+#    判断弹幕是否与任意一个关键字相关。
+    return any(keyword in danmu for keyword in keyword_strings)
+
+def danmu_about_AI(urls, keywords):
+    #根据提供的关键字对弹幕进行分类和统计，并返回前八个关键字及其相关弹幕。
+
+    all_danmu = get_danmu(urls)
+
+    # 初始化保存结果的字典
+    keyword_count = {keyword: 0 for keyword in keywords}  # 保存每个关键字的数量
+    keyword_dist = {keyword: [] for keyword in keywords}  # 保存与每个关键字相关的弹幕
+
+    # 遍历每一个弹幕，若与某一个关键字相关则统计
+    for danmu in all_danmu:
+        for keyword, keyword_strings in keywords.items():
+            if is_related(danmu, keyword_strings):
+                keyword_count[keyword] += 1
+                keyword_dist[keyword].append(danmu)
+                break
+
+    # 得到前八个关键字及其对应计数
+    top_8_AI = sorted(keyword_count.items(), key=lambda item: item[1], reverse=True)[:8]
+
+    # 统计得到前八个相关技术的所有弹幕
+    top_8_danmu = []
+    for keyword, _ in top_8_AI:
+        top_8_danmu.extend(keyword_dist[keyword])
+
+    return top_8_danmu, top_8_AI