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import gradio as gr
import pandas as pd
import plotly.express as px
from datetime import datetime, timedelta
import requests
from io import BytesIO
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))
# 30์ผ์น ๋ฐ์ดํฐ ์ค๋น
thirty_days_ago = datetime.now() - timedelta(days=30)
df['createdAt'] = pd.to_datetime(df['createdAt'])
df = df[df['createdAt'] >= thirty_days_ago].copy()
# ๋ ์ง๋ณ ๋ฐ์ดํฐ ์ฒ๋ฆฌ
dates = pd.date_range(start=thirty_days_ago, end=datetime.now(), freq='D')
daily_ranks = []
for date in dates:
# ํด๋น ๋ ์ง์ ๋ฐ์ดํฐ ์ถ์ถ
date_data = df[df['createdAt'].dt.date <= date.date()].copy()
# trendingScore๊ฐ ๊ฐ์ ๊ฒฝ์ฐ id๋ก ์ ๋ ฌํ์ฌ ์ ๋ํฌํ ์์ ๋ณด์ฅ
date_data = date_data.sort_values(['trendingScore', 'id'], ascending=[False, True])
# ์์ ๊ณ์ฐ
date_data['rank'] = range(1, len(date_data) + 1)
date_data['date'] = date.date()
# ํ์ํ ์ปฌ๋ผ๋ง ์ ํ
daily_ranks.append(
date_data[['id', 'date', 'rank', 'trendingScore', 'createdAt']]
)
# ์ ์ฒด ๋ฐ์ดํฐ ๋ณํฉ
daily_ranks_df = pd.concat(daily_ranks, ignore_index=True)
# ์ต์ ๋ ์ง์ top 100 ์ถ์ถ
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()
print(f"Total records: {len(daily_ranks_df)}")
print(f"Unique spaces: {len(daily_ranks_df['id'].unique())}")
print(f"Date range: {daily_ranks_df['date'].min()} to {daily_ranks_df['date'].max()}")
return daily_ranks_df, top_100_spaces
except Exception as e:
print(f"Error loading data: {e}")
return pd.DataFrame(), pd.DataFrame()
def create_trend_chart(space_id, daily_ranks_df):
if space_id is None or daily_ranks_df.empty:
return None
try:
# ํน์ space์ ๋ฐ์ดํฐ๋ง ํํฐ๋ง
space_data = daily_ranks_df[daily_ranks_df['id'] == space_id].copy()
if space_data.empty:
return None
# ๋ฐ์ดํฐ ์ ๋ ฌ
space_data = space_data.sort_values('date')
fig = px.line(
space_data,
x='date',
y='rank',
title=f'Daily Rank Trend for {space_id}',
labels={'date': 'Date', 'rank': 'Rank'},
markers=True
)
fig.update_layout(
xaxis_title="Date",
yaxis_title="Rank",
yaxis_autorange="reversed", # ์์ 1์ด ์์ชฝ์ ์ค๋๋ก
hovermode='x unified',
plot_bgcolor='white',
paper_bgcolor='white'
)
return fig
except Exception as e:
print(f"Error creating chart: {e}")
return None
def update_display(selection):
global daily_ranks_df
if not selection:
return None, "Please select a space"
try:
# ์ ํ๋ ํญ๋ชฉ์์ space ID ์ถ์ถ
space_id = selection.split(': ')[1].split(' (Score')[0]
# ์ต์ ๋ฐ์ดํฐ ๊ฐ์ ธ์ค๊ธฐ
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)}"
# ๋ฐ์ดํฐ ๋ก๋
print("Loading initial data...")
daily_ranks_df, top_100_spaces = load_and_process_data()
print("Data loaded.")
# Gradio ์ธํฐํ์ด์ค ์์ฑ
with gr.Blocks(theme=gr.themes.Soft()) as demo:
gr.Markdown("# Trending Spaces Dashboard")
with gr.Row():
with gr.Column(scale=1):
# ์์๊ฐ ํฌํจ๋ ๋ฆฌ์คํธ๋ก ํ์
space_choices = [
f"Rank {row['rank']}: {row['id']} (Score: {row['trendingScore']:.2f})"
for _, row in top_100_spaces.iterrows()
]
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
)
info_box = gr.Textbox(
label="Space Details",
value="",
interactive=False,
lines=4
)
with gr.Column(scale=2):
trend_plot = gr.Plot(
label="Daily Rank Trend"
)
space_list.change(
fn=update_display,
inputs=[space_list],
outputs=[trend_plot, info_box]
)
if __name__ == "__main__":
demo.launch(share=True) |