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import requests
import pandas as pd
import gradio as gr
# Assuming we have an API endpoint that provides the required data
API_ENDPOINT = "https://api.example.com/crypto/top-volume/12h"
def fetch_top_cryptos():
# Placeholder for API call and data processing
# In a real scenario, replace this with a call to the actual API
response = requests.get(API_ENDPOINT)
if response.status_code == 200:
data = response.json()
# Assuming the API returns data in a format that can be directly converted to a DataFrame
df = pd.DataFrame(data)
# Selecting and formatting the relevant columns
df = df[['name', 'volume_invested']]
return df
else:
return "Error fetching data"
# Gradio interface
iface = gr.Interface(
fn=fetch_top_cryptos,
inputs=None,
outputs="dataframe",
title="Top Cryptocurrencies by Volume",
description="Shows the top cryptocurrencies by volume invested in the past 12 hours."
)
# The API key for deploying on Hugging Face Spaces
api_key = "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"
# Launch the app locally for testing
if __name__ == "__main__":
iface.launch()
# To deploy on Hugging Face Spaces, use the `launch` method with `share=True` and the `api_key` parameter
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