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