Update app.py

app.py

@@ -2,9 +2,12 @@ import streamlit as st
 import requests
 import pandas as pd
 from datetime import datetime
+import time
+import threading
 
 # Define the markets (cryptocurrencies to monitor)
 markets = ['DOTUSDT', 'BTCUSDT', 'ADAUSDT', 'BNBUSDT', 'SUIUSDT', 'XRPUSDT']
+filename = 'USDT.csv'
 
 # Function to get price and volume data from CoinEx
 def get_crypto_price_from_coinex(symbol):
@@ -29,26 +32,77 @@ def get_crypto_price_from_coinex(symbol):
         st.error(f"JSON decode error: {e}")
         return ["JSON decode error", "JSON decode error"]
 
+# Initialize a flag to control the loop
+loop_running = False
+
+# Check if the file exists and write the header if it doesn't
+file_exists = False
+try:
+    with open(filename, 'r') as file:
+        file_exists = True
+except FileNotFoundError:
+    file_exists = False
+
+if not file_exists:
+    with open(filename, 'w', newline='') as file:
+        writer = csv.writer(file)
+        # Write header: price and volume for all cryptos in markets list, with a timestamp
+        header = []
+        for market in markets:
+            header.append(f'{market} Price')
+            header.append(f'{market} Volume')
+        header.append('Timestamp')  # Add timestamp to the end
+        writer.writerow(header)
+
+# Function to fetch data in a loop
+def fetch_data():
+    global loop_running
+    while loop_running:
+        try:
+            all_data = []
+            for market in markets:
+                crypto_data = get_crypto_price_from_coinex(market)
+                all_data += crypto_data  # Add price and volume to the list
+
+            timestamp = datetime.now().strftime('%Y-%m-%d %H:%M:%S')  # Get the current timestamp
+            all_data.append(timestamp)  # Add the timestamp to the data list
+
+            # Append the data to the CSV file
+            with open(filename, 'a', newline='') as file:
+                writer = csv.writer(file)
+                writer.writerow(all_data)
+
+            # Print confirmation to console
+            print(f'{all_data} data added')
+
+            # Sleep for 1 second before the next iteration
+            time.sleep(1)
+        except Exception as e:
+            st.error(f"An error occurred: {e}")
+            loop_running = False  # Stop the loop in case of an error
+
 # Streamlit UI elements
-st.title("Live Cryptocurrency Data")
-
-# Create a button to fetch the data
-if st.button("Fetch Live Data"):
-    # Create a list to store data for all markets
-    all_data = []
-    
-    # Fetch data for each market
-    for market in markets:
-        crypto_data = get_crypto_price_from_coinex(market)
-        all_data.append([market, crypto_data[0], crypto_data[1]])  # [market, price, volume]
-    
-    # Convert the data into a DataFrame for easier display
-    df = pd.DataFrame(all_data, columns=["Market", "Price (USDT)", "Volume (24h)"])
-    df['Timestamp'] = datetime.now().strftime('%Y-%m-%d %H:%M:%S')  # Add a timestamp column
-    
-    # Display the table
-    st.write(df)
-
-# To update the page every 30 seconds to show live data:
-st.text("Refreshing data every 30 seconds...")
-st.experimental_rerun()  # Automatically rerun the app to update the data every 30 seconds
+st.title("Live Cryptocurrency Data with Start/Stop Loop")
+
+# Button to start the loop
+if st.button("Start Fetching Data"):
+    if not loop_running:
+        loop_running = True
+        # Run the fetch data function in a separate thread so it doesn't block the Streamlit UI
+        threading.Thread(target=fetch_data, daemon=True).start()
+        st.success("Started fetching data and saving it to CSV.")
+    else:
+        st.warning("Data fetching is already running.")
+
+# Button to stop the loop
+if st.button("Stop Fetching Data"):
+    loop_running = False
+    st.success("Stopped fetching data.")
+
+# Display the latest data from the CSV (if available)
+st.text("Latest Data from CSV:")
+try:
+    df = pd.read_csv(filename)
+    st.write(df.tail())  # Show the last few rows of the CSV
+except Exception as e:
+    st.error(f"Error reading the CSV: {e}")