打通了，但是预测明显是有问题的。

binance_order_flow/data_processing.py

@@ -1,4 +1,6 @@
 import json
+import time
+
 import numpy as np
 import pandas as pd
 import queue
@@ -32,6 +34,7 @@ def on_message_trade(_ws, message):
     trade_data.append(trade)
     check_and_train_model()
     predict_market_direction()
+    show_message()
 
 
 def on_message_depth(_ws, message):
@@ -47,6 +50,7 @@ def on_message_depth(_ws, message):
     })
     check_and_train_model()
     predict_market_direction()
+    show_message()
 
 
 def extract_features(order_book, trade):
@@ -114,7 +118,7 @@ def check_and_train_model():
         if len(X_train) > 0 and len(y_train) > 0:
             model.fit(X_train, y_train)
             model_trained = True  # 标记模型已经被训练
-            logger.info("Model trained with %d samples", len(X_train))
+            # logger.info("Model trained with %d samples", len(X_train))
         else:
             logger.info("Insufficient data to train the model")
     else:
@@ -124,15 +128,50 @@ def check_and_train_model():
 def predict_market_direction():
     global model_trained
     if len(order_book_snapshots) == 0 or len(trade_data) == 0:
-        logger.info("Not enough data to make a prediction")
+        # logger.info("Not enough data to make a prediction")
         return
 
     if not model_trained:
-        logger.info("Model is not trained yet")
+        # logger.info("Model is not trained yet")
         return
 
     features = extract_features(order_book_snapshots[-1], trade_data[-1])
     if features is not None:
         feature_vector = np.array([list(features.values())])
         prediction = model.predict(feature_vector)
-        logger.info("Predicted Market Direction: %s", "Up" if prediction[0] == 1 else "Down")
+        logger.info("Predicted Market Direction: %s", "Up" if prediction[0] == 1 else "Down")
+
+
+# 将消息推送到外部，看看图长什么样
+def show_message():
+    global order_book_snapshots, trade_data
+
+    if len(order_book_snapshots) > 0 and len(trade_data) > 0:
+        # 获取最新的订单簿数据和成交数据
+        latest_order_book = order_book_snapshots[-1]
+        latest_trade = trade_data[-1]
+
+        # 提取asks和bids数据
+        asks = [[float(price), float(qty)] for price, qty in latest_order_book['asks']]
+        bids = [[float(price), float(qty)] for price, qty in latest_order_book['bids']]
+
+        # 排序asks和bids数据
+        asks_sorted = sorted(asks, key=lambda x: x[0])
+        bids_sorted = sorted(bids, key=lambda x: x[0], reverse=True)
+
+        last_price = latest_trade['price']
+        last_qty = latest_trade['qty']
+        side = latest_trade['side']
+
+        # 生成数据字典
+        data = {
+            "asks": asks_sorted,
+            "bids": bids_sorted,
+            "last_price": last_price,
+            "last_qty": last_qty,
+            "side": side,
+            "time": int(time.time() * 1000)
+        }
+
+        # 将数据放入消息队列
+        messages.put(data)

binance_order_flow/ws_client.py

@@ -5,7 +5,7 @@ from logger_config import logger
 from data_processing import on_message_trade, on_message_depth, stop_event
 
 # Binance WebSocket API URL
-SYMBOL = "rsr" + "usdt"
+SYMBOL = "token" + "usdt"
 SOCKET_TRADE = "wss://fstream.binance.com/stream?streams=" + SYMBOL + "@trade"
 SOCKET_DEPTH = "wss://fstream.binance.com/stream?streams=" + SYMBOL + "@depth20@100ms"