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I can help you extract real-time data from the Binance API and plot it simultaneously using Matplotlib. However, I need to clarify that there are some issues with your current code.

First, the createFrame function is not defined anywhere in your code. You will need to define this function or replace it with an existing one that fetches frame data from Binance.

Second, the socket object seems to be used for WebSocket connections, but Matplotlib does not have a built-in API for real-time plotting. However, you can use the matplotlib.ticker module to create automatic tickers for your chart. This will allow you to visualize real-time data without having to constantly query the Binance API.

Here is an example of how you can modify your code to achieve this:

import socket
import time
import matplotlib.pyplot as plt









Define the function to fetch the frame data from Binance
def create_frame(msg):

Assuming msg is a byte object, decode it first
frame = msg.decode('utf-8')
return frame
class BinanceClient:
def __init__(self):
self.socket = socket.socket(socket.AF_INET, socket.SOCK_STREAM)
async def connect_to_binance(self, url):
await self.socket.connect((url, 443))
self.socket.settimeout(1) 
Set a timeout for the connection
async def send_message(self, msg):
await self.socket.recv()
frame = create_frame(msg)
return frame.decode('utf-8')

Create a BinanceClient instance
client = BinanceClient()
async def main():
while True:

Connect to Binance API and get the latest frame data
url = "
client.connect_to_binance(url)
msg = await client.send_message("GET ORDERBOOK")

Plot received frame data using Matplotlib
frames = []
while True:
frame = create_frame(msg)
frames.append(frame.decode('utf-8'))
time.sleep(0.01) 
Wait 10 milliseconds
plt.figure(figsize=(20, 10))
plt.plot(frames)
plt.title("Binance Frame Data")
plt.xlabel("Time")
plt.ylabel("Frame Data")
plt.show()

Get the latest frame data from Binance
msg = await client.send_message("GET ORDERBOOK")
if __name__ == "__main__":
play()

This code creates a BinanceClient instance and uses it to connect to the Binance API. It then plots the received frame data using Matplotlib.

Note that this is a simplified example and you may need to adjust the connection timeout and plot interval to suit your specific needs. Additionally, you will need to replace the create_frame function with an existing one that retrieves the frame data from Binance.

Also, keep in mind that plotting live data requires making periodic requests to the server, which can be resource-intensive. If you plan to handle large volumes of data, you may want to consider using a more efficient data streaming API.

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