Update app-backup.py

app-backup.py

@@ -10,12 +10,10 @@ def create_trend_chart(space_id, daily_ranks_df):
         return None
     
     try:
-        # 특정 space의 데이터만 필터링
         space_data = daily_ranks_df[daily_ranks_df['id'] == space_id].copy()
         if space_data.empty:
             return None
         
-        # 데이터 정렬
         space_data = space_data.sort_values('date')
         
         fig = px.line(
@@ -24,29 +22,29 @@ def create_trend_chart(space_id, daily_ranks_df):
             y='rank',
             title=f'Daily Rank Trend for {space_id}',
             labels={'date': 'Date', 'rank': 'Rank'},
-            markers=True
+            markers=True,
+            height=400  # 차트 높이 설정
         )
         
         fig.update_layout(
             xaxis_title="Date",
             yaxis_title="Rank",
             yaxis=dict(
-                range=[100, 1],   # 100위부터 1위까지 (역순으로 설정)
-                tickmode='linear',  # 선형 간격으로 눈금 표시
-                tick0=1,           # 첫 눈금
-                dtick=10          # 눈금 간격 (10단위로 표시)
+                range=[100, 1],
+                tickmode='linear',
+                tick0=1,
+                dtick=10
             ),
             hovermode='x unified',
             plot_bgcolor='white',
             paper_bgcolor='white',
-            showlegend=False
+            showlegend=False,
+            margin=dict(t=50, r=20, b=40, l=40)
         )
         
-        # 격자 추가
         fig.update_xaxes(showgrid=True, gridwidth=1, gridcolor='lightgray')
         fig.update_yaxes(showgrid=True, gridwidth=1, gridcolor='lightgray')
         
-        # 라인 스타일 수정
         fig.update_traces(
             line_color='#2563eb',
             line_width=2,
@@ -58,119 +56,211 @@ def create_trend_chart(space_id, daily_ranks_df):
         print(f"Error creating chart: {e}")
         return None
 
+def update_display(selection):
+    global daily_ranks_df
+    
+    if not selection:
+        return None, gr.HTML(value="<div style='text-align: center; padding: 20px; color: #666;'>Select a space to view details</div>")
+    
+    try:
+        space_id = selection
+        
+        latest_data = daily_ranks_df[
+            daily_ranks_df['id'] == space_id
+        ].sort_values('date').iloc[-1]
+        
+        info_text = f"""
+        <div style="padding: 16px; background-color: white; border-radius: 8px; box-shadow: 0 1px 3px rgba(0,0,0,0.1);">
+            <h3 style="margin: 0 0 12px 0;">Space Details</h3>
+            <p style="margin: 4px 0;"><strong>ID:</strong> {space_id}</p>
+            <p style="margin: 4px 0;"><strong>Current Rank:</strong> {int(latest_data['rank'])}</p>
+            <p style="margin: 4px 0;"><strong>Trending Score:</strong> {latest_data['trendingScore']:.2f}</p>
+            <p style="margin: 4px 0;"><strong>Created At:</strong> {latest_data['createdAt'].strftime('%Y-%m-%d')}</p>
+            <p style="margin: 12px 0 0 0;">
+                <a href="https://huggingface.co/spaces/{space_id}" 
+                   target="_blank" 
+                   style="color: #2563eb; text-decoration: none;">
+                    View Space ↗
+                </a>
+            </p>
+        </div>
+        """
+        
+        chart = create_trend_chart(space_id, daily_ranks_df)
+        
+        return chart, gr.HTML(value=info_text)
+        
+    except Exception as e:
+        print(f"Error in update_display: {e}")
+        return None, gr.HTML(value=f"<div style='color: red;'>Error processing data: {str(e)}</div>")
+
 def load_and_process_data():
     try:
         url = "https://huggingface.co/datasets/cfahlgren1/hub-stats/resolve/main/spaces.parquet"
         response = requests.get(url)
         df = pd.read_parquet(BytesIO(response.content))
         
-        # 30일치 데이터 준비
         thirty_days_ago = datetime.now() - timedelta(days=30)
         df['createdAt'] = pd.to_datetime(df['createdAt'])
         df = df[df['createdAt'] >= thirty_days_ago].copy()
         
-        # 날짜별 데이터 처리
         dates = pd.date_range(start=thirty_days_ago, end=datetime.now(), freq='D')
         daily_ranks = []
         
         for date in dates:
-            # 해당 날짜의 데이터 추출
             date_data = df[df['createdAt'].dt.date <= date.date()].copy()
-            
-            # trendingScore가 같은 경우 id로 정렬하여 유니크한 순위 보장
             date_data = date_data.sort_values(['trendingScore', 'id'], ascending=[False, True])
-            
-            # 순위 계산
             date_data['rank'] = range(1, len(date_data) + 1)
             date_data['date'] = date.date()
-            
-            # 필요한 컬럼만 선택
             daily_ranks.append(
                 date_data[['id', 'date', 'rank', 'trendingScore', 'createdAt']]
             )
         
-        # 전체 데이터 병합
         daily_ranks_df = pd.concat(daily_ranks, ignore_index=True)
         
-        # 최신 날짜의 top 100 추출
         latest_date = daily_ranks_df['date'].max()
         top_100_spaces = daily_ranks_df[
-            daily_ranks_df['date'] == latest_date
-        ].sort_values('rank').head(100).copy()
+            (daily_ranks_df['date'] == latest_date) &
+            (daily_ranks_df['rank'] <= 100)
+        ].sort_values('rank').copy()
         
         return daily_ranks_df, top_100_spaces
     except Exception as e:
         print(f"Error loading data: {e}")
         return pd.DataFrame(), pd.DataFrame()
 
-def update_display(selection):
-    global daily_ranks_df
-    
-    if not selection:
-        return None, "Please select a space"
-    
-    try:
-        # 선택된 항목에서 space ID 추출
-        space_id = selection.split(': ')[1].split(' (Score')[0]
-        
-        # 최신 데이터 가져오기
-        latest_data = daily_ranks_df[
-            daily_ranks_df['id'] == space_id
-        ].sort_values('date').iloc[-1]
-        
-        info_text = f"""ID: {space_id}
-Current Rank: {int(latest_data['rank'])}
-Trending Score: {latest_data['trendingScore']:.2f}
-Created At: {latest_data['createdAt'].strftime('%Y-%m-%d')}"""
-        
-        chart = create_trend_chart(space_id, daily_ranks_df)
-        
-        return chart, info_text
-        
-    except Exception as e:
-        print(f"Error in update_display: {e}")
-        return None, f"Error processing data: {str(e)}"
-
 # 데이터 로드
 print("Loading initial data...")
 daily_ranks_df, top_100_spaces = load_and_process_data()
-print("Data loaded.")
+print("Data loaded successfully!")
 
 # Gradio 인터페이스 생성
 with gr.Blocks(theme=gr.themes.Soft()) as demo:
-    gr.Markdown("# Trending Spaces Dashboard")
+    gr.Markdown("""
+    # HF Space Ranking Tracker
     
-    with gr.Row():
-        with gr.Column(scale=1):
-            # 순위가 포함된 리스트로 표시
-            space_choices = [
-                f"Rank {row['rank']}: {row['id']} (Score: {row['trendingScore']:.2f})"
-                for _, row in top_100_spaces.iterrows()
-            ]
+    Track, analyze, and discover trending AI applications in the Hugging Face ecosystem. Our service continuously monitors and ranks all Spaces over a 30-day period, providing detailed analytics and daily ranking changes for the top 100 performers.
+    """)
+    
+    with gr.Tabs():
+        with gr.Tab("Dashboard"):
+            with gr.Row(variant="panel"):
+                trend_plot = gr.Plot(
+                    label="Daily Rank Trend",
+                    container=True,
+                )
             
-            space_list = gr.Radio(
-                choices=space_choices,
-                label="Top 100 Trending Spaces",
-                info="Select a space to view its rank trend",
-                value=space_choices[0] if space_choices else None
-            )
+            with gr.Row():
+                info_box = gr.HTML(
+                    value="<div style='text-align: center; padding: 20px; color: #666;'>Select a space to view details</div>"
+                )
             
-            info_box = gr.Textbox(
-                label="Space Details",
-                value="",
-                interactive=False,
-                lines=4
+            # 라디오 버튼을 먼저 정의
+            space_selection = gr.Radio(
+                choices=[row['id'] for _, row in top_100_spaces.iterrows()],
+                value=None,
+                visible=False
             )
+            
+            # HTML에서 JavaScript 이벤트를 직접 처리
+            html_content = """
+            <div style='display: flex; flex-wrap: wrap; gap: 16px; justify-content: center;'>
+            """ + "".join([
+                f"""
+                <div class="space-card" 
+                     data-space-id="{row['id']}"
+                     style="
+                    border: 1px solid #e5e7eb;
+                    border-radius: 8px;
+                    padding: 16px;
+                    margin: 8px;
+                    background-color: hsl(210, {max(30, 90 - (row['rank'] / 100 * 60))}%, {min(97, 85 + (row['rank'] / 100 * 10))}%);
+                    box-shadow: 0 1px 3px rgba(0,0,0,0.1);
+                    display: inline-block;
+                    width: 250px;
+                    vertical-align: top;
+                    cursor: pointer;
+                    transition: all 0.2s;
+                "
+                onmouseover="this.style.transform='translateY(-2px)';this.style.boxShadow='0 4px 6px rgba(0,0,0,0.1)';"
+                onmouseout="this.style.transform='none';this.style.boxShadow='0 1px 3px rgba(0,0,0,0.1)';"
+                >
+                    <div style="font-size: 1.2em; font-weight: bold; margin-bottom: 8px;">
+                        #{int(row['rank'])}
+                    </div>
+                    <div style="margin-bottom: 8px;">
+                        {row['id']}
+                    </div>
+                    <div style="color: #666; margin-bottom: 12px;">
+                        Score: {row['trendingScore']:.2f}
+                    </div>
+                    <div style="display: flex; gap: 8px;">
+                        <a href="https://huggingface.co/spaces/{row['id']}" 
+                           target="_blank" 
+                           style="padding: 6px 12px; background-color: white; color: #2563eb; text-decoration: none; border-radius: 4px; font-size: 0.9em; border: 1px solid #2563eb;"
+                           onclick="event.stopPropagation();">
+                            View Space ↗
+                        </a>
+                        <button onclick="event.preventDefault(); gradioEvent('{row['id']}');"
+                                style="padding: 6px 12px; background-color: #2563eb; color: white; border: none; border-radius: 4px; cursor: pointer; font-size: 0.9em;">
+                            View Trend
+                        </button>
+                    </div>
+                </div>
+                """
+                for _, row in top_100_spaces.iterrows()
+            ]) + """
+            </div>
+            <script>
+            function gradioEvent(spaceId) {
+                const radio = document.querySelector(`input[type="radio"][value="${spaceId}"]`);
+                if (radio) {
+                    radio.checked = true;
+                    const event = new Event('change');
+                    radio.dispatchEvent(event);
+                }
+            }
+            </script>
+            """
+            
+            with gr.Row():
+                space_grid = gr.HTML(value=html_content)
         
-        with gr.Column(scale=2):
-            trend_plot = gr.Plot(
-                label="Daily Rank Trend"
-            )
+        with gr.Tab("About"):
+            gr.Markdown("""
+            ### Our Tracking System
+            
+            #### What We Track
+            - Daily ranking changes for all Hugging Face Spaces
+            - Comprehensive trending scores based on 30-day activity
+            - Detailed performance metrics for top 100 Spaces
+            - Historical ranking data with daily granularity
+            
+            #### Key Features
+            - **Real-time Rankings**: Stay updated with daily rank changes
+            - **Interactive Visualizations**: Track ranking trajectories over time
+            - **Trend Analysis**: Identify emerging popular AI applications
+            - **Direct Access**: Quick links to explore trending Spaces
+            - **Performance Metrics**: Detailed trending scores and statistics
+            
+            ### Why Use HF Space Ranking Tracker?
+            - Discover trending AI demos and applications
+            - Monitor your Space's performance and popularity
+            - Identify emerging trends in the AI community
+            - Make data-driven decisions about your AI projects
+            - Stay ahead of the curve in AI application development
+            
+            Our dashboard provides a comprehensive view of the Hugging Face Spaces ecosystem, helping developers, researchers, and enthusiasts track and understand the dynamics of popular AI applications. Whether you're monitoring your own Space's performance or discovering new trending applications, HF Space Ranking Tracker offers the insights you need.
+            
+            Experience the pulse of the AI community through our daily updated rankings and discover what's making waves in the world of practical AI applications.
+            """)
     
-    space_list.change(
+    # 라디오 버튼 변경 이벤트 연결
+    space_selection.change(
         fn=update_display,
-        inputs=[space_list],
-        outputs=[trend_plot, info_box]
+        inputs=[space_selection],
+        outputs=[trend_plot, info_box],
+        api_name="update_display"
     )
 
 if __name__ == "__main__":