suggestions

crypto/gogo/.vscode/launch.json

@@ -0,0 +1,31 @@
+{
+  "version": "0.2.0",
+  "configurations": [
+    {
+      "name": "Train (Live Data)",
+      "type": "python",
+      "request": "launch",
+      "program": "${workspaceFolder}/main.py",
+      "console": "integratedTerminal",
+      "justMyCode": false,
+      "args": ["--mode", "train"]
+    },
+    {
+      "name": "Backtest (Historical Data)",
+      "type": "python",
+      "request": "launch",
+      "program": "${workspaceFolder}/main.py",
+      "console": "integratedTerminal",
+      "justMyCode": false,
+      "args": ["--mode", "backtest"]
+    },
+    {
+      "name": "Unit Tests",
+      "type": "python",
+      "request": "launch",
+      "program": "${workspaceFolder}/tests/test_data.py",
+      "console": "integratedTerminal",
+      "justMyCode": false
+    }
+  ]
+}

crypto/gogo/.vscode/settings.json

@@ -0,0 +1,11 @@
+{
+    "python.testing.unittestArgs": [
+        "-v",
+        "-s",
+        "./tests",
+        "-p",
+        "test_*.py"
+    ],
+    "python.testing.pytestEnabled": false,
+    "python.testing.unittestEnabled": true
+}

crypto/gogo/candles_cache.json

@@ -0,0 +1 @@
+{"1m": [], "5m": [], "15m": [], "1h": [], "1d": []}

crypto/gogo/main.py

@@ -1,5 +1,3 @@
-# main.py
-
 import asyncio
 import torch
 import torch.nn as nn
@@ -17,8 +15,9 @@ from model.trading_model import TradingModel
 from training.rl_agent import ContinuousRLAgent, ReplayBuffer
 from training.train_historical import train_on_historical_data, load_best_checkpoint, save_candles_cache, CACHE_FILE, BEST_DIR
 from data.data_utils import get_aligned_candle_with_index, get_features_for_tf
+import argparse
 
-async def main():
+async def main_training():
     symbol = 'BTC/USDT'
     data_manager = LiveDataManager(symbol)
 
@@ -293,4 +292,11 @@ def plot_trade_history(candles, trade_history):
     plt.show()
 
 if __name__ == '__main__':
-    asyncio.run(main_backtest())
+    parser = argparse.ArgumentParser(description='Trading Bot Modes')
+    parser.add_argument('--mode', type=str, default='backtest', choices=['train', 'backtest'], help='Choose mode: train or backtest')
+    args = parser.parse_args()
+
+    if args.mode == 'train':
+        asyncio.run(main_training())
+    elif args.mode == 'backtest':
+        asyncio.run(main_backtest())

crypto/gogo/model/transformer.py

@@ -219,4 +219,4 @@ if __name__ == '__main__':
 
     print("Future Candle Prediction Shape:", future_candle_pred.shape)  # Expected: [batch_size, 1, 5]
     print("Future Volume Prediction Shape:", future_volume_pred.shape)  # Expected: [batch_size, 1, 1]
-    print("Future Ticks Prediction Shape:", future_ticks_pred.shape)   # Expected: [batch_size, 30, 2]
+    print("Future Ticks Prediction Shape:", future_ticks_pred.shape)   # Expected: [batch_size, 30, 2]

crypto/gogo/readme.md

@@ -1,4 +1,3 @@
-
 To run this code:
 
 Install Dependencies: pip install -r requirements.txt
@@ -28,4 +27,4 @@ Overfitting: Monitor for overfitting (the model performing well on training data
 
 Memory usage: the code uses a deque to store the data. This prevents out of memory errors and keeps only the most recent N samples.
 
-Learned indicators: This is a complex part. you can create a new NN, that will be trained to predict the next candle data based only on HLOCV. the weights of this NN can be used as new indicators, concatenated to the others.
+Learned indicators: This is a complex part. you can create a new NN, that will be trained to predict the next candle data based only on HLOCV. the weights of this NN can be used as new indicators, concatenated to the others.

crypto/gogo/requirements.txt

@@ -3,4 +3,4 @@ ccxt
 python-dotenv
 torch
 numpy
-matplotlib
+matplotlib

crypto/gogo/tests/test_data.py

@@ -0,0 +1,51 @@
+import asyncio
+import unittest
+from unittest.mock import patch, AsyncMock
+from data.live_data import LiveDataManager
+import ccxt.async_support as ccxt
+
+class TestLiveData(unittest.IsolatedAsyncioTestCase):
+
+    async def asyncSetUp(self):
+        self.symbol = 'BTC/USDT'
+        self.data_manager = LiveDataManager(self.symbol)
+        self.exchange = self.data_manager.exchange
+
+    async def asyncTearDown(self):
+        await self.data_manager.close()
+
+    @patch('data.live_data.ccxt.mexc.fetch_trades', new_callable=AsyncMock)
+    async def test_fetch_and_process_ticks(self, mock_fetch_trades):
+        # Mock the exchange response
+        mock_fetch_trades.return_value = [
+            {'timestamp': 1678886400000, 'symbol': 'BTC/USDT', 'price': 25000.0, 'quantity': 1.0},
+            {'timestamp': 1678886460000, 'symbol': 'BTC/USDT', 'price': 25050.0, 'quantity': 0.5}
+        ]
+
+        # Call the method
+        await self.data_manager.fetch_and_process_ticks()
+
+        # Assert that the ticks are processed
+        candles, ticks = await self.data_manager.get_data()
+        self.assertEqual(len(ticks), 2)
+        self.assertEqual(len(candles), 1)
+
+    @patch('data.live_data.ccxt.mexc.fetch_ohlcv', new_callable=AsyncMock)
+    async def test_fetch_initial_candles(self, mock_fetch_ohlcv):
+        # Mock the exchange response
+        mock_fetch_ohlcv.return_value = [
+            [1678886400000, 25000.0, 25050.0, 24950.0, 25025.0, 100.0],
+            [1678886460000, 25025.0, 25100.0, 25000.0, 25075.0, 120.0]
+        ]
+
+        # Call the method
+        await self.data_manager._fetch_initial_candles()
+
+        # Assert that the candles are fetched and formatted
+        candles, _ = await self.data_manager.get_data()
+        self.assertEqual(len(candles), 2)
+        self.assertEqual(candles[0]['open'], 25000.0)
+        self.assertEqual(candles[0]['close'], 25025.0)
+
+if __name__ == '__main__':
+    unittest.main()

crypto/gogo/training/train.py

@@ -154,4 +154,4 @@ async def train(model, data_manager, optimizer, criterion_candle, criterion_volu
             # Plot data
             if len(trade_history)>0: # only after the first trade
                 plot_live_data(candles, list(trade_history))
-            await asyncio.sleep(1)  # Adjust sleep time as needed
+            await asyncio.sleep(1)  # Adjust sleep time as needed

crypto/gogo/visualization/plotting.py

@@ -32,4 +32,4 @@ def plot_live_data(candles, trade_history):
     ax.grid(True)
     plt.tight_layout()
 
-    plt.show()
+    plt.show()