app.py

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
""")