Update app.py

app.py

@@ -10,10 +10,13 @@ import plotly.graph_objects as go
 import networkx as nx
 
 # プロフィール画像を取得するヘルパー関数
-def get_profile_image(client, did_or_handle):
+def get_profile_info(client, did_or_handle):
     try:
         profile = client.get_profile(actor=did_or_handle)
-        return profile.avatar if profile and profile.avatar else None
+        return {
+            "avatar": profile.avatar if profile.avatar else "https://abs.twimg.com/sticky/default_profile_images/default_profile_normal.png",
+            "handle": profile.handle
+        }
     except Exception:
         return None
 
@@ -30,16 +33,14 @@ def analyze_and_output(my_id, my_pw, target_id, freq_type, progress=gr.Progress(
         posts_data = []
         hashtags = []
         reply_users_list = []    
-        repost_users_list = []    
-        like_users_list = []      
-
+        repost_users_list = []   
+        like_users_list = []     
         interactions_for_network = [] 
-        user_avatars = {target_handle: getattr(profile, 'avatar', None)} 
 
         max_limit = 500 
         
         # --- 2. 投稿フィードの分析 ---
-        progress(0, desc="データを取得中...")
+        progress(0, desc="フィードを取得中...")
         cursor = None
         
         for _ in range(10): 
@@ -47,22 +48,23 @@ def analyze_and_output(my_id, my_pw, target_id, freq_type, progress=gr.Progress(
                 response = client.get_author_feed(actor=profile.did, limit=100, cursor=cursor)
             except Exception:
                 break
-            if not response or not hasattr(response, 'feed') or not response.feed:
+            if not response or not response.feed:
                 break
 
             for feed_view in response.feed:
-                if not getattr(feed_view, 'post', None): continue
                 post = feed_view.post
 
+                # リポスト分析
                 if feed_view.reason:
-                    if hasattr(post, 'author') and post.author:
+                    if hasattr(post, 'author'):
                         orig_author = post.author.handle
                         if orig_author != target_handle:
                             repost_users_list.append(orig_author)
-                            interactions_for_network.append((target_handle, orig_author, 'repost'))
+                            interactions_for_network.append((target_handle, orig_author))
                     continue 
 
-                if hasattr(post, 'author') and post.author.handle == target_handle:
+                # 本人投稿分析
+                if post.author.handle == target_handle:
                     rkey = post.uri.split('/')[-1]
                     post_url = f"https://bsky.app/profile/{target_handle}/post/{rkey}"
                     likes = getattr(post, 'like_count', 0) or 0
@@ -82,80 +84,145 @@ def analyze_and_output(my_id, my_pw, target_id, freq_type, progress=gr.Progress(
                         if text:
                             hashtags.extend(re.findall(r'#(\w+)', text))
                     
+                    # リプライ相手
                     if getattr(feed_view, 'reply', None) and feed_view.reply.parent:
                         parent = feed_view.reply.parent
                         if hasattr(parent, 'author'):
                             p_handle = parent.author.handle
                             if p_handle != target_handle:
                                 reply_users_list.append(p_handle)
-                                interactions_for_network.append((target_handle, p_handle, 'reply'))
+                                interactions_for_network.append((target_handle, p_handle))
 
-            cursor = getattr(response, 'cursor', None)
+            cursor = response.cursor
             if not cursor or len(posts_data) >= max_limit: break
-
-        # --- 3. 解析結果の作成 ---
+            progress(0.4, desc=f"{len(posts_data)}件取得済み...")
+
+        # --- 3. いいねの取得 ---
+        try:
+            likes_resp = client.get_actor_likes(actor=profile.did, limit=40)
+            for like_item in likes_resp.feed:
+                l_handle = like_item.post.author.handle
+                if l_handle != target_handle:
+                    like_users_list.append(l_handle)
+        except: pass
+
+        # --- 4. 解析とHTML作成 ---
         if not posts_data:
-            return "データが見つかりませんでした。", "", "", None, None, "完了（データ不足）"
+            return "データ不足", "", "", None, None, "失敗"
 
         df = pd.DataFrame(posts_data)
-        df['created_at'] = df['created_at'].dt.tz_localize(None)
-        df = df.sort_values('created_at', ascending=True)
-        
-        first_post_time = df.iloc[0]['created_at']
-        days_active = max((datetime.now() - first_post_time).days, 1)
-
-        stats_html = f"<b>総ポスト数:</b> {getattr(profile, 'posts_count', 0)} / <b>継続:</b> {days_active}日"
-
-        # 棒グラフ
+        df['created_at_dt'] = df['created_at'].dt.tz_localize(None)
+        days_active = max((datetime.now() - df['created_at_dt'].min()).days, 1)
+
+        stats_html = f"""
+        <div style='display: grid; grid-template-columns: repeat(3, 1fr); gap: 10px;'>
+            <div style='background: #e3f2fd; padding: 10px; border-radius: 8px; text-align: center;'>
+                <small>総ポスト</small><br><b>{getattr(profile, 'posts_count', 0)}</b>
+            </div>
+            <div style='background: #f1f8e9; padding: 10px; border-radius: 8px; text-align: center;'>
+                <small>継続日数</small><br><b>{days_active}日</b>
+            </div>
+            <div style='background: #fff3e0; padding: 10px; border-radius: 8px; text-align: center;'>
+                <small>1日平均</small><br><b>{len(df)/days_active:.2f}</b>
+            </div>
+        </div>
+        """
+
+        # ランキングHTML
+        def rank_box(title, items):
+            top = Counter(items).most_common(3)
+            res = f"<b>{title}</b><br>"
+            res += "<br>".join([f"@{n} ({c}回)" for n, c in top]) if top else "なし"
+            return res
+
+        rank_html = f"""
+        <div style='background: #f9f9f9; padding: 15px; border-radius: 10px; font-size: 0.9em;'>
+            {rank_box("💬 リプライ", reply_users_list)}<hr>
+            {rank_box("🔄 リポスト", repost_users_list)}<hr>
+            {rank_box("❤️ いいね", like_users_list)}
+        </div>
+        """
+
+        # ベスト投稿
+        top_posts = df.sort_values('score', ascending=False).head(3)
+        posts_html = "<b>🏆 ベストポスト</b><br>"
+        for _, row in top_posts.iterrows():
+            posts_html += f"<div style='margin-bottom:8px; font-size:0.85em; border-left:3px solid #0085ff; padding-left:5px;'>{row['text'][:60]}... (❤️{row['likes']})</div>"
+
+        # --- 5. グラフ作成 ---
         freq_map = {"日ごと": "D", "週ごと": "W", "月ごと": "M"}
-        df_counts = df.set_index('created_at').resample(freq_map[freq_type]).size().reset_index(name='count')
-        fig_bar = px.bar(df_counts, x='created_at', y='count', title="投稿推移")
+        df_counts = df.set_index('created_at_dt').resample(freq_map[freq_type]).size().reset_index(name='count')
+        fig_bar = px.bar(df_counts, x='created_at_dt', y='count', title="アクティビティ推移")
 
-        # ネットワーク図 (簡易版)
+        # --- 6. アイコン付きネットワーク図 ---
+        progress(0.8, desc="ネットワーク図を生成中...")
         G = nx.Graph()
-        all_inter = [item[1] for item in interactions_for_network]
-        top_nodes = [target_handle] + [u for u, c in Counter(all_inter).most_common(9)]
+        top_interactors = [u for u, c in Counter(reply_users_list + repost_users_list).most_common(9)]
+        nodes = [target_handle] + top_interactors
         
-        for s, t, _ in interactions_for_network:
-            if s in top_nodes and t in top_nodes:
-                G.add_edge(s, t)
+        # 相互作用の重み付け
+        for s, t in interactions_for_network:
+            if s in nodes and t in nodes:
+                if G.has_edge(s, t): G[s][t]['weight'] += 1
+                else: G.add_edge(s, t, weight=1)
+
+        pos = nx.spring_layout(G, k=0.5)
+        
+        # アイコンURLの取得
+        node_images = []
+        for node in G.nodes():
+            info = get_profile_info(client, node)
+            img_url = info['avatar'] if info else ""
+            node_images.append(dict(
+                source=img_url, xref="x", yref="y", x=pos[node][0], y=pos[node][1],
+                sizex=0.15, sizey=0.15, xanchor="center", yanchor="middle", layer="above"
+            ))
 
-        pos = nx.spring_layout(G)
         edge_x, edge_y = [], []
-        for e in G.edges():
-            x0, y0 = pos[e[0]]
-            x1, y1 = pos[e[1]]
-            edge_x.extend([x0, x1, None])
-            edge_y.extend([y0, y1, None])
-
-        fig_network = go.Figure(data=[go.Scatter(x=edge_x, y=edge_y, mode='lines', line=dict(color='#888')),
-                                     go.Scatter(x=[pos[n][0] for n in G.nodes()], 
-                                               y=[pos[n][1] for n in G.nodes()], 
-                                               mode='markers+text', 
-                                               text=list(G.nodes()), 
-                                               marker=dict(size=20, color='#0085ff'))])
+        for edge in G.edges():
+            edge_x += [pos[edge[0]][0], pos[edge[1]][0], None]
+            edge_y += [pos[edge[0]][1], pos[edge[1]][1], None]
+
+        fig_net = go.Figure()
+        fig_net.add_trace(go.Scatter(x=edge_x, y=edge_y, mode='lines', line=dict(color='#ccc', width=1), hoverinfo='none'))
+        fig_net.add_trace(go.Scatter(x=[pos[n][0] for n in G.nodes()], y=[pos[n][1] for n in G.nodes()],
+                                     mode='markers+text', text=list(G.nodes()), textposition="bottom center",
+                                     marker=dict(size=30, color='rgba(0,0,0,0)')))
         
-        return stats_html, "Ranking Data", "Top Posts Data", fig_bar, fig_network, "解析完了"
+        fig_net.update_layout(images=node_images, showlegend=False, 
+                              xaxis=dict(showgrid=False, zeroline=False, showticklabels=False),
+                              yaxis=dict(showgrid=False, zeroline=False, showticklabels=False),
+                              plot_bgcolor='white', margin=dict(t=40, b=0, l=0, r=0))
+
+        return stats_html, rank_html, posts_html, fig_bar, fig_net, "解析完了！"
 
     except Exception as e:
         return f"エラー: {str(e)}", "", "", None, None, "失敗"
 
-with gr.Blocks() as demo:
-    gr.Markdown("# 🦋 Bluesky 分析")
+# --- UI定義 ---
+with gr.Blocks(title="Bluesky Dashboard") as demo:
+    gr.Markdown("# 🦋 Bluesky 全機能統合ダッシュボード")
+    
     with gr.Row():
-        with gr.Column():
-            in_id = gr.Textbox(label="自分のID")
-            in_pw = gr.Textbox(label="パスワード", type="password")
-            in_target = gr.Textbox(label="対象のID")
-            in_freq = gr.Radio(["日ごと", "週ごと", "月ごと"], label="集計単位", value="日ごと")
-            btn = gr.Button("開始")
-            status = gr.Textbox(label="状態")
-        with gr.Column():
+        with gr.Column(scale=1):
+            my_id = gr.Textbox(label="自分のハンドル", placeholder="me.bsky.social")
+            my_pw = gr.Textbox(label="アプリパスワード", type="password")
+            target_id = gr.Textbox(label="解析対象", placeholder="target.bsky.social")
+            freq = gr.Radio(["日ごと", "週ごと", "月ごと"], label="グラフ単位", value="日ごと")
+            btn = gr.Button("分析開始", variant="primary")
+            status = gr.Textbox(label="ステータス", interactive=False)
+        
+        with gr.Column(scale=2):
             out_stats = gr.HTML()
-            out_bar = gr.Plot()
-            out_net = gr.Plot()
+            with gr.Row():
+                out_rank = gr.HTML()
+                out_posts = gr.HTML()
+
+    with gr.Row():
+        out_bar = gr.Plot(label="投稿頻度")
+        out_net = gr.Plot(label="ユーザーネットワーク（アイコン付）")
 
-    btn.click(analyze_and_output, inputs=[in_id, in_pw, in_target, in_freq], 
-              outputs=[out_stats, gr.HTML(), gr.HTML(), out_bar, out_net, status])
+    btn.click(analyze_and_output, inputs=[my_id, my_pw, target_id, freq], 
+              outputs=[out_stats, out_rank, out_posts, out_bar, out_net, status])
 
 demo.launch()