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import yfinance as yf
import pandas as pd
import time
from datasets import Dataset
import os
# Hugging Face Credentials
HF_USERNAME = "KavinduHansaka"
HF_DATASET_REPO = f"{HF_USERNAME}/btc-minute-data"
HF_TOKEN = os.getenv("Token")
# Function to Fetch BTC Prices from Yahoo Finance (Last 24h, 1-min interval)
def fetch_btc_price():
try:
btc = yf.Ticker("BTC-USD")
df = btc.history(period="1d", interval="1m") # Fetch last 24 hours with 1-min intervals
df = df.tail(240) # Keep only the last 4 hours (240 minutes)
df.reset_index(inplace=True)
df = df[["Datetime", "Close"]].rename(columns={"Datetime": "timestamp", "Close": "price"})
df["timestamp"] = df["timestamp"].astype(str)
return df
except Exception as e:
print(f"❌ Failed to fetch BTC price: {e}")
return None
# Convert & Upload Dataset
def create_hf_dataset(df):
return Dataset.from_pandas(df)
def upload_to_huggingface(dataset):
dataset.push_to_hub(HF_DATASET_REPO, token=HF_TOKEN)
print(f"✅ Dataset updated at: https://huggingface.co/datasets/{HF_USERNAME}/btc-minute-data")
def update_dataset():
print("Fetching latest BTC minute data...")
df = fetch_btc_price()
if df is None or df.empty:
print("❌ Failed to fetch BTC price.")
return
print("Uploading BTC dataset to Hugging Face...")
dataset = create_hf_dataset(df)
upload_to_huggingface(dataset)
print("✅ BTC Dataset updated successfully!")
if __name__ == "__main__":
while True:
update_dataset()
time.sleep(3600) # Update dataset every hour
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