import streamlit as st
import requests
import pandas as pd
from datetime import datetime
import time
import csv
import threading
from huggingface_hub import HfApi
import os

# Hugging Face Info
HF_USERNAME = "abolfazle80"
REPO_NAME = "crypto_data"
CSV_FILENAME = "USDT.csv"
HF_CSV_URL = f"https://huggingface.co/datasets/{HF_USERNAME}/{REPO_NAME}/resolve/main/{CSV_FILENAME}"

# Define the markets (cryptocurrencies to monitor)
markets = ['DOTUSDT', 'BTCUSDT', 'ADAUSDT', 'BNBUSDT', 'SUIUSDT', 'XRPUSDT']

# Initialize Hugging Face API
api = HfApi()

# 🔹 Initialize loop control variable (Fixed Global Issue)
loop_running = False  

# Function to fetch data from CoinEx
def get_crypto_price_from_coinex(symbol):
    url = 'https://api.coinex.com/v1/market/ticker'
    params = {'market': symbol}

    try:
        response = requests.get(url, params=params)
        response.raise_for_status()
        data = response.json()

        if 'data' in data:
            price = data['data']['ticker']['last']
            volume = data['data']['ticker']['vol']
            return [price, volume]
        else:
            return ["Symbol not found", "Symbol not found"]
    except Exception as e:
        st.error(f"Error fetching data: {e}")
        return ["Error", "Error"]

# Function to download CSV from Hugging Face and save it locally
def download_existing_csv():
    try:
        response = requests.get(HF_CSV_URL)
        response.raise_for_status()
        
        with open(CSV_FILENAME, "wb") as file:
            file.write(response.content)

        df = pd.read_csv(CSV_FILENAME)
        return df
    except requests.exceptions.RequestException:
        return pd.DataFrame()  # Return empty DataFrame if file doesn't exist

# Function to upload the CSV back to Hugging Face
def upload_to_huggingface():
    try:
        api.upload_file(
            path_or_fileobj=CSV_FILENAME,
            path_in_repo=CSV_FILENAME,
            repo_id=f"{HF_USERNAME}/{REPO_NAME}",
            repo_type="dataset",
        )
        print("✅ CSV successfully uploaded to Hugging Face.")
    except Exception as e:
        print(f"❌ Upload failed: {e}")

# Function to fetch, append & update the CSV
def fetch_data():
    global loop_running  # ✅ Fixed Scope Issue
    while loop_running:
        try:
            all_data = []
            for market in markets:
                crypto_data = get_crypto_price_from_coinex(market)
                all_data += crypto_data

            timestamp = datetime.now().strftime('%Y-%m-%d %H:%M:%S')
            all_data.append(timestamp)

            # Check if CSV exists locally; if not, download it
            if not os.path.exists(CSV_FILENAME):
                df_existing = download_existing_csv()
            else:
                df_existing = pd.read_csv(CSV_FILENAME)

            # Convert new data to DataFrame
            df_new = pd.DataFrame([all_data], columns=[f"{m} Price" for m in markets] + 
                                                        [f"{m} Volume" for m in markets] + 
                                                        ["Timestamp"])

            # Append new data to existing data
            df_combined = pd.concat([df_existing, df_new], ignore_index=True)

            # Save updated data to CSV
            df_combined.to_csv(CSV_FILENAME, index=False)

            print(f"✅ {all_data} added to CSV and uploaded.")

            # Upload to Hugging Face
            upload_to_huggingface()

            time.sleep(1)  # Fetch new data every second
        except Exception as e:
            st.error(f"An error occurred: {e}")
            loop_running = False

# Streamlit UI
st.title("🔄 Live Cryptocurrency Data Fetching")

# Start Fetching Button
if st.button("Start Fetching Data"):
    if not loop_running:  # ✅ Fixed issue by ensuring variable scope
        loop_running = True
        threading.Thread(target=fetch_data, daemon=True).start()
        st.success("✅ Started fetching and saving data.")
    else:
        st.warning("⚠️ Fetching is already running.")

# Stop Fetching Button
if st.button("Stop Fetching Data"):
    loop_running = False
    st.success("🛑 Stopped fetching data.")

# Show Latest Data
st.text("📊 Latest Data from CSV:")

# Ensure the file exists before reading it
if not os.path.exists(CSV_FILENAME):
    download_existing_csv()

try:
    df = pd.read_csv(CSV_FILENAME)
    st.write(df.tail())  # Show last 5 rows
except Exception as e:
    st.error(f"Error reading CSV: {e}")