Create app.py

app.py

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+import requests
+import pandas as pd
+import matplotlib.pyplot as plt
+import seaborn as sns
+from datetime import datetime, timedelta
+import numpy as np
+import streamlit as st
+import plotly.graph_objects as go
+import plotly.express as px
+from PIL import Image
+import io
+import base64
+
+# 페이지 설정
+st.set_page_config(layout="wide", page_title="HuggingFace Spaces Trending Analysis")
+
+# 스타일 적용
+st.markdown("""
+    <style>
+    .main {
+        background-color: #f5f5f5;
+    }
+    .stButton>button {
+        background-color: #ff4b4b;
+        color: white;
+        border-radius: 5px;
+    }
+    .trending-card {
+        padding: 20px;
+        border-radius: 10px;
+        background-color: white;
+        box-shadow: 0 4px 6px rgba(0, 0, 0, 0.1);
+        margin: 10px 0;
+    }
+    </style>
+    """, unsafe_allow_html=True)
+
+# 타이틀
+st.title("🤗 HuggingFace Spaces Trending Analysis")
+
+# 관심 스페이스 URL 리스트와 정보
+target_spaces = {
+    "ginipick/FLUXllama": "https://huggingface.co/spaces/ginipick/FLUXllama",
+    "ginipick/SORA-3D": "https://huggingface.co/spaces/ginipick/SORA-3D",
+    "fantaxy/Sound-AI-SFX": "https://huggingface.co/spaces/fantaxy/Sound-AI-SFX",
+    # ... [나머지 스페이스들도 동일한 형식으로 추가]
+    "NCSOFT/VARCO_Arena": "https://huggingface.co/spaces/NCSOFT/VARCO_Arena"
+}
+
+def get_trending_spaces(date):
+    url = f"https://huggingface.co/api/spaces/trending?date={date}&limit=300"
+    response = requests.get(url)
+    if response.status_code == 200:
+        return response.json()
+    return None
+
+def get_space_rank(spaces, space_id):
+    for idx, space in enumerate(spaces, 1):
+        if space.get('id', '') == space_id:
+            return idx
+    return None
+
+# 데이터 수집
+@st.cache_data
+def fetch_trending_data():
+    start_date = datetime(2023, 12, 1)
+    end_date = datetime(2023, 12, 31)
+    dates = [(start_date + timedelta(days=x)).strftime('%Y-%m-%d') 
+             for x in range((end_date - start_date).days + 1)]
+    
+    trending_data = {}
+    target_space_ranks = {space: [] for space in target_spaces.keys()}
+    
+    with st.spinner('데이터를 불러오는 중...'):
+        for date in dates:
+            spaces = get_trending_spaces(date)
+            if spaces:
+                trending_data[date] = spaces
+                for space_id in target_spaces.keys():
+                    rank = get_space_rank(spaces, space_id)
+                    target_space_ranks[space_id].append(rank)
+    
+    return trending_data, target_space_ranks, dates
+
+trending_data, target_space_ranks, dates = fetch_trending_data()
+
+# 시각화
+st.header("📈 Trending Rank Changes")
+
+# Plotly를 사용한 인터랙티브 그래프
+fig = go.Figure()
+
+for space_id, ranks in target_space_ranks.items():
+    fig.add_trace(go.Scatter(
+        x=dates,
+        y=ranks,
+        name=space_id,
+        mode='lines+markers',
+        hovertemplate=
+        '<b>Date</b>: %{x}<br>' +
+        '<b>Rank</b>: %{y}<br>' +
+        '<b>Space</b>: ' + space_id
+    ))
+
+fig.update_layout(
+    title='Trending Ranks Over Time',
+    xaxis_title='Date',
+    yaxis_title='Rank',
+    yaxis_autorange='reversed',
+    height=800,
+    template='plotly_white',
+    hovermode='x unified'
+)
+
+st.plotly_chart(fig, use_container_width=True)
+
+# 최신 순위 정보 출력
+st.header("🏆 Latest Rankings")
+
+latest_date = max(trending_data.keys())
+latest_spaces = trending_data[latest_date]
+
+cols = st.columns(3)
+col_idx = 0
+
+for space_id, url in target_spaces.items():
+    rank = get_space_rank(latest_spaces, space_id)
+    if rank:
+        space_info = next((s for s in latest_spaces if s['id'] == space_id), None)
+        if space_info:
+            with cols[col_idx % 3]:
+                with st.container():
+                    st.markdown(f"""
+                    <div class="trending-card">
+                        <h3>#{rank} - {space_id}</h3>
+                        <p>👍 Likes: {space_info.get('likes', 'N/A')}</p>
+                        <p>📝 {space_info.get('title', 'N/A')}</p>
+                        <p>{space_info.get('description', 'N/A')[:100]}...</p>
+                        <a href="{url}" target="_blank">Visit Space 🔗</a>
+                    </div>
+                    """, unsafe_allow_html=True)
+            col_idx += 1
+
+# 다운로드 기능
+st.header("📊 Download Data")
+
+# DataFrame 생성
+df_data = []
+for date in dates:
+    spaces = trending_data.get(date, [])
+    for space_id in target_spaces.keys():
+        rank = get_space_rank(spaces, space_id)
+        if rank:
+            space_info = next((s for s in spaces if s['id'] == space_id), None)
+            if space_info:
+                df_data.append({
+                    'Date': date,
+                    'Space ID': space_id,
+                    'Rank': rank,
+                    'Likes': space_info.get('likes', 'N/A'),
+                    'Title': space_info.get('title', 'N/A'),
+                    'URL': target_spaces[space_id]
+                })
+
+df = pd.DataFrame(df_data)
+
+# CSV 다운로드 버튼
+csv = df.to_csv(index=False)
+b64 = base64.b64encode(csv.encode()).decode()
+href = f'<a href="data:file/csv;base64,{b64}" download="trending_data.csv">Download CSV File</a>'
+st.markdown(href, unsafe_allow_html=True)
+
+# 푸터
+st.markdown("""
+---
+Made with ❤️ using Streamlit and HuggingFace API
+""")