Update app.py

app.py

@@ -8,51 +8,179 @@ from collections import Counter
 import plotly.express as px
 import plotly.graph_objects as go
 import networkx as nx
+import io
+from PIL import Image
+
+# 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):
+    try:
+        profile = client.get_profile(actor=did_or_handle)
+        return profile.avatar if profile and profile.avatar else None
+    except Exception:
+        return None
 
 def analyze_and_output(my_id, my_pw, target_id, freq_type, progress=gr.Progress()):
     try:
-        # --- 1. ログイン & データ取得 ---
+        # --- 1. ログイン ---
         client = Client()
-        client.login(my_id.replace('@', '').strip(), my_pw.strip())
+        my_id = my_id.replace('@', '').strip()
         target_handle = target_id.replace('@', '').strip()
+        client.login(my_id, my_pw.strip())
+        
         profile = client.get_profile(actor=target_handle)
         
         posts_data = []
-        interactions = [] # (自分, 相手, 種類)
+        hashtags = []
+        reply_users_list = []    
+        repost_users_list = []    
+        like_users_list = []      
+
+        # ネットワーク図作成のための相互作用リスト
+        interactions_for_network = [] # (source_handle, target_handle, type)
+        user_avatars = {target_handle: getattr(profile, 'avatar', None)} # 顔アイコンURLを保存
+
+        max_limit = 500 
         
+        # --- 2. 投稿フィードの分析 ---
+        progress(0, desc="フィードと相互作用データを取得中...")
         cursor = None
-        for _ in range(10): # 最大1000件
-            response = client.get_author_feed(actor=profile.did, limit=100, cursor=cursor)
+        
+        for _ in range(10): # 最大1000件取得を想定しつつ無限ループ防止
+            try:
+                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:
+                break
+
             for feed_view in response.feed:
+                if not getattr(feed_view, 'post', None): continue
                 post = feed_view.post
-                if post.author.handle == target_handle:
-                    # 投稿データ保存
-                    posts_data.append({
-                        'text': getattr(post.record, 'text', ""),
-                        'created_at': pd.to_datetime(post.record.created_at),
-                    })
+
+                # リポスト分析
+                if feed_view.reason:
+                    if hasattr(post, 'author') and post.author:
+                        orig_author_handle = post.author.handle
+                        if orig_author_handle != target_handle:
+                            repost_users_list.append(orig_author_handle)
+                            interactions_for_network.append((target_handle, orig_author_handle, 'repost'))
+                            if orig_author_handle not in user_avatars:
+                                user_avatars[orig_author_handle] = get_profile_image(client, orig_author_handle)
+                    continue 
+
+                # 本人投稿分析
+                if hasattr(post, 'author') and post.author and post.author.handle == target_handle:
+                    if not hasattr(post, 'record'): continue
                     
-                    # ネットワーク用：リプライ
-                    if feed_view.reply and feed_view.reply.parent:
-                        parent_author = getattr(feed_view.reply.parent.author, 'handle', None)
-                        if parent_author and parent_author != target_handle:
-                            interactions.append((target_handle, parent_author, 'reply'))
-                
-                # ネットワーク用：リポスト
-                if feed_view.reason and post.author.handle != target_handle:
-                    interactions.append((target_handle, post.author.handle, 'repost'))
-            
-            cursor = response.cursor
-            if not cursor: break
+                    rkey = post.uri.split('/')[-1]
+                    post_url = f"https://bsky.app/profile/{target_handle}/post/{rkey}"
+                    
+                    likes = getattr(post, 'like_count', 0) or 0
+                    reposts = getattr(post, 'repost_count', 0) or 0
+                    created_at_raw = getattr(post.record, 'created_at', None)
+                    text = getattr(post.record, 'text', "") or ""
+
+                    if created_at_raw:
+                        posts_data.append({
+                            'text': text,
+                            'created_at': pd.to_datetime(created_at_raw),
+                            'likes': likes,
+                            'reposts': reposts,
+                            'score': likes + reposts,
+                            'url': post_url
+                        })
+                        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') and 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'))
+                                if p_handle not in user_avatars:
+                                    user_avatars[p_handle] = get_profile_image(client, p_handle)
 
+            cursor = getattr(response, 'cursor', None)
+            if not cursor or len(posts_data) >= max_limit: break
+            progress(min(len(posts_data)/max_limit * 0.5, 0.5), desc=f"{len(posts_data)}件取得中...")
+
+        # --- 3. いいね一覧の分析 ---
+        progress(0.6, desc="いいねを分析中...")
+        try:
+            likes_resp = client.get_actor_likes(actor=profile.did, limit=50) # いいねの取得は少し少なめに
+            if likes_resp and hasattr(likes_resp, 'feed'):
+                for like_item in likes_resp.feed:
+                    if like_item.post and hasattr(like_item.post, 'author') and like_item.post.author:
+                        l_handle = like_item.post.author.handle
+                        if l_handle != target_handle:
+                            like_users_list.append(l_handle)
+                            # ネットワーク図には追加しないが、ユーザー情報を取得するならここで
+                            if l_handle not in user_avatars:
+                                user_avatars[l_handle] = get_profile_image(client, l_handle)
+        except Exception:
+            pass # いいね取得でエラーが出ても続行
+
+        # --- 4. 解析結果のHTML作成 ---
         if not posts_data:
-            return None, None, "データが見つかりませんでした"
+            return "有効な投稿データが見つかりませんでした。", "", "", None, None, "完了（データ不足）"
 
         df = pd.DataFrame(posts_data)
-        df['created_at'] = df['created_at'].dt.tz_localize(None)
+        df['created_at'] = df['created_at'].dt.tz_localize(None) # タイムゾーンを削除
+        df = df.sort_values('created_at', ascending=True)
+        
+        first_post_time = df.iloc[0]['created_at'].replace(tzinfo=None)
+        days_active = max((datetime.now().replace(tzinfo=None) - first_post_time).days, 1)
+
+        stats_html = f"""
+        <div style='display: grid; grid-template-columns: repeat(3, 1fr); gap: 10px; margin-bottom: 20px;'>
+            <div style='background: #e3f2fd; padding: 15px; border-radius: 10px; text-align: center; border: 1px solid #90caf9;'>
+                <div style='color: #1565c0; font-size: 0.8em;'>総ポスト</div><div style='font-size: 1.5em; font-weight: bold;'>{getattr(profile, 'posts_count', 0)}</div>
+            </div>
+            <div style='background: #f1f8e9; padding: 15px; border-radius: 10px; text-align: center; border: 1px solid #c5e1a5;'>
+                <div style='color: #33691e; font-size: 0.8em;'>継続日数</div><div style='font-size: 1.5em; font-weight: bold;'>{days_active}日</div>
+            </div>
+            <div style='background: #fff3e0; padding: 15px; border-radius: 10px; text-align: center; border: 1px solid #ffcc80;'>
+                <div style='color: #e65100; font-size: 0.8em;'>1日平均</div><div style='font-size: 1.5em; font-weight: bold;'>{len(df)/days_active:.2f}</div>
+            </div>
+        </div>
+        """
 
-        # --- 2. 投稿数の棒グラフ (Plotly) ---
-        # freq_type: "日ごと" -> "D", "週ごと" -> "W", "月ごと" -> "M"
+        def make_rank_list(title, icon, counter_list):
+            html = f"<b>{icon} {title}</b><div style='font-size: 0.85em; color: #444; margin: 5px 0 12px 0;'>"
+            if not counter_list: return html + "データなし</div>"
+            items = Counter(counter_list).most_common(3)
+            for name, count in items:
+                html += f"<div>@{name} ({count}回)</div>"
+            return html + "</div>"
+
+        rank_html = f"""
+        <div style='background: #fafafa; padding: 15px; border-radius: 10px; border: 1px solid #eee;'>
+            {make_rank_list("よくリプライする相手", "💬", reply_users_list)}
+            {make_rank_list("よくリポストする相手", "🔄", repost_users_list)}
+            {make_rank_list("よくいいねする相手", "❤️", like_users_list)}
+            <b>#️⃣ よく使うタグ</b><div style='display: flex; flex-wrap: wrap; gap: 5px; margin-top: 8px;'>
+            {"".join([f"<span style='background: #eee; padding: 3px 8px; border-radius: 10px; font-size: 0.75em;'>#{t}</span>" for t, _ in Counter(hashtags).most_common(3)]) or "なし"}
+            </div>
+        </div>
+        """
+
+        top_3 = df.sort_values('score', ascending=False).head(3)
+        posts_html = f"<h4>🌱 初投稿 ({df.iloc[0]['created_at'].strftime('%Y/%m/%d')})</h4><p style='font-size: 0.9em; background:#f9f9f9; padding:10px; border-radius:5px;'>{df.iloc[0]['text']}</p><h4>🏆 ベストポスト Top 3</h4>"
+        
+        for i, (_, row) in enumerate(top_3.iterrows(), 1):
+            posts_html += f"""
+            <div style='border: 1px solid #eee; padding: 10px; margin-bottom: 8px; border-radius: 8px; background: white;'>
+                <b>第{i}位</b> (❤️{row['likes']} 🔄{row['reposts']})<br>
+                <p style='margin:5px 0;'>{row['text'][:80]}...</p>
+                <a href='{row['url']}' target='_blank' style='color:#d81b60; font-size:0.8em;'>表示</a>
+            </div>
+            """
+
+        # --- 5. 投稿数の棒グラフ (Plotly) ---
         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')
         
@@ -62,72 +190,123 @@ def analyze_and_output(my_id, my_pw, target_id, freq_type, progress=gr.Progress(
                          template="plotly_white")
         fig_bar.update_traces(marker_color='#0085ff')
 
-        # --- 3. ユーザーネットワーク図 (NetworkX + Plotly) ---
+        # --- 6. ユーザーネットワーク図 (NetworkX + Plotly + 顔アイコン) ---
         G = nx.Graph()
-        # 出現回数をカウントしてエッジの太さに反映
-        edge_counts = Counter([(u, v) for u, v, t in interactions])
-        for (u, v), weight in edge_counts.items():
-            G.add_edge(u, v, weight=weight)
+        # 相互作用の多い順に上位10ユーザーを抽出
+        all_interactions_nodes = [item[1] for item in interactions_for_network] # 相手側のユーザー
+        top_10_users_counter = Counter(all_interactions_nodes).most_common(9) # 本人を除いた9人
+        top_10_handles = [target_handle] + [user for user, _ in top_10_users_counter]
+
+        for source, target, _type in interactions_for_network:
+            if source in top_10_handles and target in top_10_handles:
+                if not G.has_edge(source, target):
+                    G.add_edge(source, target, weight=1) # 初回
+                else:
+                    G[source][target]['weight'] += 1 # 相互作用回数を重み付け
 
-        pos = nx.spring_layout(G, k=0.5, iterations=50)
+        # ノードが1つ以下ならネットワーク図は作らない
+        if G.number_of_nodes() < 2:
+            fig_network = go.Figure().update_layout(title="ネットワーク図：相互作用が不足しています")
+        else:
+            pos = nx.spring_layout(G, k=0.5, iterations=50) # レイアウト計算
+
+            edge_x, edge_y, edge_weights = [], [], []
+            for u, v, data in G.edges(data=True):
+                x0, y0 = pos[u]
+                x1, y1 = pos[v]
+                edge_x.extend([x0, x1, None])
+                edge_y.extend([y0, y1, None])
+                edge_weights.append(data['weight'])
+
+            edge_trace = go.Scatter(x=edge_x, y=edge_y, line=dict(width=[w*0.5 for w in edge_weights], color='#888'),
+                                    hoverinfo='none', mode='lines', opacity=0.7)
+
+            node_x, node_y, node_text, node_images = [], [], [], []
+            for node in G.nodes():
+                x, y = pos[node]
+                node_x.append(x)
+                node_y.append(y)
+                node_text.append(f"@{node}<br>つながり: {len(list(G.neighbors(node)))}")
+                
+                avatar_url = user_avatars.get(node, None)
+                node_images.append(avatar_url if avatar_url else 'https://img.icons8.com/ios-filled/50/000000/user--v1.png') # デフォルトアイコン
+
+            node_trace = go.Scatter(
+                x=node_x, y=node_y, mode='markers', hoverinfo='text', text=node_text,
+                marker=dict(
+                    symbol='circle', # ダミー
+                    size=30, 
+                    color='rgba(0,0,0,0)', # 透明にして画像を表示
+                    line_width=0,
+                    opacity=0 # 透明
+                )
+            )
+
+            # アイコンを追加するためのアノテーション
+            annotations = []
+            for i, (x, y) in enumerate(zip(node_x, node_y)):
+                annotations.append(
+                    go.layout.Annotation(
+                        x=x, y=y,
+                        xref="x", yref="y",
+                        text="",
+                        showarrow=False,
+                        images=[dict(
+                            source=node_images[i],
+                            xref="x", yref="y",
+                            x=x, y=y,
+                            sizex=0.08, sizey=0.08, # アイコンのサイズ調��
+                            xanchor="center", yanchor="middle"
+                        )]
+                    )
+                )
+
+            fig_network = go.Figure(data=[edge_trace, node_trace],
+                                 layout=go.Layout(title=f'{target_handle}の関連ユーザーネットワーク (Top {len(top_10_handles)} users)',
+                                                showlegend=False, hovermode='closest',
+                                                margin=dict(b=0,l=0,r=0,t=40),
+                                                xaxis=dict(showgrid=False, zeroline=False, showticklabels=False),
+                                                yaxis=dict(showgrid=False, zeroline=False, showticklabels=False),
+                                                annotations=annotations # アイコンをアノテーションとして追加
+                                                ))
         
-        edge_x, edge_y = [], []
-        for edge in G.edges():
-            x0, y0 = pos[edge[0]]
-            x1, y1 = pos[edge[1]]
-            edge_x.extend([x0, x1, None])
-            edge_y.extend([y0, y1, None])
-
-        edge_trace = go.Scatter(x=edge_x, y=edge_y, line=dict(width=0.5, color='#888'), hoverinfo='none', mode='lines')
-
-        node_x, node_y, node_text, node_size = [], [], [], []
-        for node in G.nodes():
-            x, y = pos[node]
-            node_x.append(x)
-            node_y.append(y)
-            node_text.append(f"@{node}<br>接続数: {len(list(G.neighbors(node)))}")
-            # 中心ユーザー（本人）を大きく表示
-            node_size.append(30 if node == target_handle else 15)
-
-        node_trace = go.Scatter(
-            x=node_x, y=node_y, mode='markers', hoverinfo='text', text=node_text,
-            marker=dict(showscale=True, colorscale='YlGnBu', size=node_size, 
-                        colorbar=dict(thickness=15, title='Node Connections'),
-                        line_width=2))
-
-        fig_network = go.Figure(data=[edge_trace, node_trace],
-                     layout=go.Layout(title='関連ユーザーネットワーク (Reply & Repost)',
-                                    showlegend=False, hovermode='closest',
-                                    margin=dict(b=0,l=0,r=0,t=40),
-                                    xaxis=dict(showgrid=False, zeroline=False, showticklabels=False),
-                                    yaxis=dict(showgrid=False, zeroline=False, showticklabels=False)))
-
-        return fig_bar, fig_network, "解析完了"
+        return stats_html, rank_html, posts_html, fig_bar, fig_network, "解析が完了しました！"
 
     except Exception as e:
-        return None, None, f"エラー: {str(e)}"
+        import traceback
+        return f"エラーが発生しました: {str(e)}", "", "", None, None, "失敗"
 
 # --- Gradio UI ---
-with gr.Blocks() as demo:
-    gr.Markdown("# 🦋 Bluesky Advanced Visualizer")
+with gr.Blocks(title="Bluesky Analysis") as demo:
+    gr.Markdown("# 🦋 Bluesky アクティビティ＆ネットワーク分析")
     
     with gr.Row():
         with gr.Column(scale=1):
-            in_id = gr.Textbox(label="自分のID")
-            in_pw = gr.Textbox(label="アプリパスワード", type="password")
-            in_target = gr.Textbox(label="解析対象のID")
-            in_freq = gr.Radio(["日ごと", "週ごと", "月ごと"], label="グラフの単位", value="日ごと")
-            btn = gr.Button("分析実行", variant="primary")
-            status = gr.Textbox(label="ステータス")
-
+            in_id = gr.Textbox(label="自分のBluesky ID (例: example.bsky.social)")
+            in_pw = gr.Textbox(label="Bluesky アプリパスワード", type="password")
+            in_target = gr.Textbox(label="解析したいユーザーのBluesky ID (例: target.bsky.social)")
+            in_freq = gr.Radio(["日ごと", "週ごと", "月ごと"], label="投稿数グラフの単位", 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(label="概要統計")
+            out_rank = gr.HTML(label="関連ユーザーとハッシュタグ")
+            out_posts = gr.HTML(label="ベスト投稿 Top 3")
+    
+    gr.Markdown("## グラフで見るアクティビティ")
     with gr.Row():
         out_bar = gr.Plot(label="投稿数推移")
-    
+
+    gr.Markdown("## 関連ユーザーネットワーク")
     with gr.Row():
-        out_net = gr.Plot(label="関連ユーザーネットワーク")
+        out_net = gr.Plot(label="主要関連ユーザーネットワーク")
 
-    btn.click(analyze_and_output, 
-              inputs=[in_id, in_pw, in_target, in_freq], 
-              outputs=[out_bar, out_net, status])
+    btn.click(
+        fn=analyze_and_output, 
+        inputs=[in_id, in_pw, in_target, in_freq], 
+        outputs=[out_stats, out_rank, out_posts, out_bar, out_net, status]
+    )
 
-demo.launch()
+demo.launch()
+```http://googleusercontent.com/image_generation_content/1