folder stricture reorganize

This commit is contained in:
Dobromir Popov
2025-06-25 11:42:12 +03:00
parent 61b31a3089
commit 03fa28a12d
127 changed files with 3108 additions and 1774 deletions

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# Debug Files
This folder contains debug scripts and utilities for troubleshooting various components of the trading system.
## Contents
- `debug_callback_simple.py` - Simple callback debugging
- `debug_dashboard.py` - Dashboard debugging utilities
- `debug_dashboard_500.py` - Dashboard 500 error debugging
- `debug_dashboard_issue.py` - Dashboard issue debugging
- `debug_mexc_auth.py` - MEXC authentication debugging
- `debug_orchestrator_methods.py` - Orchestrator method debugging
- `debug_simple_callback.py` - Simple callback testing
- `debug_trading_activity.py` - Trading activity debugging
## Usage
These files are used for debugging specific issues and should not be run in production. They contain diagnostic code and temporary fixes for troubleshooting purposes.

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#!/usr/bin/env python3
"""
Simple callback debug script to see exact error
"""
import requests
import json
def test_simple_callback():
"""Test a simple callback to see the exact error"""
try:
# Test the simplest possible callback
callback_data = {
"output": "current-balance.children",
"inputs": [
{
"id": "ultra-fast-interval",
"property": "n_intervals",
"value": 1
}
]
}
print("Sending callback request...")
response = requests.post(
'http://127.0.0.1:8051/_dash-update-component',
json=callback_data,
timeout=15,
headers={'Content-Type': 'application/json'}
)
print(f"Status Code: {response.status_code}")
print(f"Response Headers: {dict(response.headers)}")
print(f"Response Text (first 1000 chars):")
print(response.text[:1000])
print("=" * 50)
if response.status_code == 500:
# Try to extract error from HTML
if "Traceback" in response.text:
lines = response.text.split('\n')
for i, line in enumerate(lines):
if "Traceback" in line:
# Print next 20 lines for error details
for j in range(i, min(i+20, len(lines))):
print(lines[j])
break
except Exception as e:
print(f"Request failed: {e}")
if __name__ == "__main__":
test_simple_callback()

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#!/usr/bin/env python3
"""
Debug Dashboard - Minimal version to test callback functionality
"""
import logging
import sys
from pathlib import Path
from datetime import datetime
# Add project root to path
project_root = Path(__file__).parent
sys.path.insert(0, str(project_root))
import dash
from dash import dcc, html, Input, Output
import plotly.graph_objects as go
# Setup logging
logging.basicConfig(level=logging.INFO, format='%(asctime)s - %(name)s - %(levelname)s - %(message)s')
logger = logging.getLogger(__name__)
def create_debug_dashboard():
"""Create minimal debug dashboard"""
app = dash.Dash(__name__)
app.layout = html.Div([
html.H1("🔧 Debug Dashboard - Callback Test", className="text-center"),
html.Div([
html.H3(id="debug-time", className="text-center"),
html.H4(id="debug-counter", className="text-center"),
html.P(id="debug-status", className="text-center"),
dcc.Graph(id="debug-chart")
]),
dcc.Interval(
id='debug-interval',
interval=2000, # 2 seconds
n_intervals=0
)
])
@app.callback(
[
Output('debug-time', 'children'),
Output('debug-counter', 'children'),
Output('debug-status', 'children'),
Output('debug-chart', 'figure')
],
[Input('debug-interval', 'n_intervals')]
)
def update_debug_dashboard(n_intervals):
"""Debug callback function"""
try:
logger.info(f"🔧 DEBUG: Callback triggered, interval: {n_intervals}")
current_time = datetime.now().strftime("%H:%M:%S")
counter = f"Updates: {n_intervals}"
status = f"Callback working! Last update: {current_time}"
# Create simple test chart
fig = go.Figure()
fig.add_trace(go.Scatter(
x=list(range(max(0, n_intervals-10), n_intervals + 1)),
y=[i**2 for i in range(max(0, n_intervals-10), n_intervals + 1)],
mode='lines+markers',
name='Debug Data',
line=dict(color='#00ff88')
))
fig.update_layout(
title=f"Debug Chart - Update #{n_intervals}",
template="plotly_dark",
paper_bgcolor='#1e1e1e',
plot_bgcolor='#1e1e1e'
)
logger.info(f"✅ DEBUG: Returning data - time={current_time}, counter={counter}")
return current_time, counter, status, fig
except Exception as e:
logger.error(f"❌ DEBUG: Error in callback: {e}")
import traceback
logger.error(f"Traceback: {traceback.format_exc()}")
return "Error", "Error", "Callback failed", {}
return app
def main():
"""Run the debug dashboard"""
logger.info("🔧 Starting debug dashboard...")
try:
app = create_debug_dashboard()
logger.info("✅ Debug dashboard created")
logger.info("🚀 Starting debug dashboard on http://127.0.0.1:8053")
logger.info("This will test if Dash callbacks work at all")
logger.info("Press Ctrl+C to stop")
app.run(host='127.0.0.1', port=8053, debug=True)
except KeyboardInterrupt:
logger.info("Debug dashboard stopped by user")
except Exception as e:
logger.error(f"❌ Error: {e}")
import traceback
traceback.print_exc()
if __name__ == "__main__":
main()

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#!/usr/bin/env python3
"""
Debug Dashboard - Enhanced error logging to identify 500 errors
"""
import logging
import sys
import traceback
from pathlib import Path
from datetime import datetime
import pandas as pd
# Add project root to path
project_root = Path(__file__).parent
sys.path.insert(0, str(project_root))
import dash
from dash import dcc, html, Input, Output
import plotly.graph_objects as go
from core.config import setup_logging
from core.data_provider import DataProvider
# Setup logging without emojis
logging.basicConfig(
level=logging.DEBUG,
format='%(asctime)s - %(name)s - %(levelname)s - %(message)s',
handlers=[
logging.StreamHandler(sys.stdout),
logging.FileHandler('debug_dashboard.log')
]
)
logger = logging.getLogger(__name__)
class DebugDashboard:
"""Debug dashboard with enhanced error logging"""
def __init__(self):
logger.info("Initializing debug dashboard...")
try:
self.data_provider = DataProvider()
logger.info("Data provider initialized successfully")
except Exception as e:
logger.error(f"Error initializing data provider: {e}")
logger.error(f"Traceback: {traceback.format_exc()}")
raise
# Initialize app
self.app = dash.Dash(__name__)
logger.info("Dash app created")
# Setup layout and callbacks
try:
self._setup_layout()
logger.info("Layout setup completed")
except Exception as e:
logger.error(f"Error setting up layout: {e}")
logger.error(f"Traceback: {traceback.format_exc()}")
raise
try:
self._setup_callbacks()
logger.info("Callbacks setup completed")
except Exception as e:
logger.error(f"Error setting up callbacks: {e}")
logger.error(f"Traceback: {traceback.format_exc()}")
raise
logger.info("Debug dashboard initialized successfully")
def _setup_layout(self):
"""Setup minimal layout for debugging"""
logger.info("Setting up layout...")
self.app.layout = html.Div([
html.H1("Debug Dashboard - 500 Error Investigation", className="text-center"),
# Simple metrics
html.Div([
html.Div([
html.H3(id="current-time", children="Loading..."),
html.P("Current Time")
], className="col-md-3"),
html.Div([
html.H3(id="update-counter", children="0"),
html.P("Update Count")
], className="col-md-3"),
html.Div([
html.H3(id="status", children="Starting..."),
html.P("Status")
], className="col-md-3"),
html.Div([
html.H3(id="error-count", children="0"),
html.P("Error Count")
], className="col-md-3")
], className="row mb-4"),
# Error log
html.Div([
html.H4("Error Log"),
html.Div(id="error-log", children="No errors yet...")
], className="mb-4"),
# Simple chart
html.Div([
dcc.Graph(id="debug-chart", style={"height": "300px"})
]),
# Interval component
dcc.Interval(
id='debug-interval',
interval=2000, # 2 seconds for easier debugging
n_intervals=0
)
], className="container-fluid")
logger.info("Layout setup completed")
def _setup_callbacks(self):
"""Setup callbacks with extensive error handling"""
logger.info("Setting up callbacks...")
# Store reference to self
dashboard_instance = self
error_count = 0
error_log = []
@self.app.callback(
[
Output('current-time', 'children'),
Output('update-counter', 'children'),
Output('status', 'children'),
Output('error-count', 'children'),
Output('error-log', 'children'),
Output('debug-chart', 'figure')
],
[Input('debug-interval', 'n_intervals')]
)
def update_debug_dashboard(n_intervals):
"""Debug callback with extensive error handling"""
nonlocal error_count, error_log
logger.info(f"=== CALLBACK START - Interval {n_intervals} ===")
try:
# Current time
current_time = datetime.now().strftime("%H:%M:%S")
logger.info(f"Current time: {current_time}")
# Update counter
counter = f"Updates: {n_intervals}"
logger.info(f"Counter: {counter}")
# Status
status = "Running OK" if n_intervals > 0 else "Starting"
logger.info(f"Status: {status}")
# Error count
error_count_str = f"Errors: {error_count}"
logger.info(f"Error count: {error_count_str}")
# Error log display
if error_log:
error_display = html.Div([
html.P(f"Error {i+1}: {error}", className="text-danger")
for i, error in enumerate(error_log[-5:]) # Show last 5 errors
])
else:
error_display = "No errors yet..."
# Create chart
logger.info("Creating chart...")
try:
chart = dashboard_instance._create_debug_chart(n_intervals)
logger.info("Chart created successfully")
except Exception as chart_error:
logger.error(f"Error creating chart: {chart_error}")
logger.error(f"Chart error traceback: {traceback.format_exc()}")
error_count += 1
error_log.append(f"Chart error: {str(chart_error)}")
chart = dashboard_instance._create_error_chart(str(chart_error))
logger.info("=== CALLBACK SUCCESS ===")
return current_time, counter, status, error_count_str, error_display, chart
except Exception as e:
error_count += 1
error_msg = f"Callback error: {str(e)}"
error_log.append(error_msg)
logger.error(f"=== CALLBACK ERROR ===")
logger.error(f"Error: {e}")
logger.error(f"Error type: {type(e)}")
logger.error(f"Traceback: {traceback.format_exc()}")
# Return safe fallback values
error_chart = dashboard_instance._create_error_chart(str(e))
error_display = html.Div([
html.P(f"CALLBACK ERROR: {str(e)}", className="text-danger"),
html.P(f"Error count: {error_count}", className="text-warning")
])
return "ERROR", f"Errors: {error_count}", "FAILED", f"Errors: {error_count}", error_display, error_chart
logger.info("Callbacks setup completed")
def _create_debug_chart(self, n_intervals):
"""Create a simple debug chart"""
logger.info(f"Creating debug chart for interval {n_intervals}")
try:
# Try to get real data every 5 intervals
if n_intervals % 5 == 0:
logger.info("Attempting to fetch real data...")
try:
df = self.data_provider.get_historical_data('ETH/USDT', '1m', limit=20)
if df is not None and not df.empty:
logger.info(f"Fetched {len(df)} real candles")
self.chart_data = df
else:
logger.warning("No real data returned")
except Exception as data_error:
logger.error(f"Error fetching real data: {data_error}")
logger.error(f"Data fetch traceback: {traceback.format_exc()}")
# Create chart
fig = go.Figure()
if hasattr(self, 'chart_data') and not self.chart_data.empty:
logger.info("Using real data for chart")
fig.add_trace(go.Scatter(
x=self.chart_data['timestamp'],
y=self.chart_data['close'],
mode='lines',
name='ETH/USDT Real',
line=dict(color='#00ff88')
))
title = f"ETH/USDT Real Data - Update #{n_intervals}"
else:
logger.info("Using mock data for chart")
# Simple mock data
x_data = list(range(max(0, n_intervals-10), n_intervals + 1))
y_data = [3500 + 50 * (i % 5) for i in x_data]
fig.add_trace(go.Scatter(
x=x_data,
y=y_data,
mode='lines',
name='Mock Data',
line=dict(color='#ff8800')
))
title = f"Mock Data - Update #{n_intervals}"
fig.update_layout(
title=title,
template="plotly_dark",
paper_bgcolor='#1e1e1e',
plot_bgcolor='#1e1e1e',
showlegend=False,
height=300
)
logger.info("Chart created successfully")
return fig
except Exception as e:
logger.error(f"Error in _create_debug_chart: {e}")
logger.error(f"Chart creation traceback: {traceback.format_exc()}")
raise
def _create_error_chart(self, error_msg):
"""Create error chart"""
logger.info(f"Creating error chart: {error_msg}")
fig = go.Figure()
fig.add_annotation(
text=f"Chart Error: {error_msg}",
xref="paper", yref="paper",
x=0.5, y=0.5, showarrow=False,
font=dict(size=14, color="#ff4444")
)
fig.update_layout(
template="plotly_dark",
paper_bgcolor='#1e1e1e',
plot_bgcolor='#1e1e1e',
height=300
)
return fig
def run(self, host='127.0.0.1', port=8053, debug=True):
"""Run the debug dashboard"""
logger.info(f"Starting debug dashboard at http://{host}:{port}")
logger.info("This dashboard has enhanced error logging to identify 500 errors")
try:
self.app.run(host=host, port=port, debug=debug)
except Exception as e:
logger.error(f"Error running dashboard: {e}")
logger.error(f"Run error traceback: {traceback.format_exc()}")
raise
def main():
"""Main function"""
logger.info("Starting debug dashboard main...")
try:
dashboard = DebugDashboard()
dashboard.run()
except KeyboardInterrupt:
logger.info("Dashboard stopped by user")
except Exception as e:
logger.error(f"Fatal error: {e}")
logger.error(f"Fatal traceback: {traceback.format_exc()}")
if __name__ == "__main__":
main()

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#!/usr/bin/env python3
"""
Debug Dashboard Data Flow
Check if the dashboard is receiving data and updating properly.
"""
import sys
import logging
import time
import requests
import json
from pathlib import Path
# Add project root to path
project_root = Path(__file__).parent
sys.path.insert(0, str(project_root))
from core.config import get_config, setup_logging
from core.data_provider import DataProvider
# Setup logging
setup_logging()
logger = logging.getLogger(__name__)
def test_data_provider():
"""Test if data provider is working"""
logger.info("=== TESTING DATA PROVIDER ===")
try:
# Test data provider
data_provider = DataProvider()
# Test current price
logger.info("Testing current price retrieval...")
current_price = data_provider.get_current_price('ETH/USDT')
logger.info(f"Current ETH/USDT price: ${current_price}")
# Test historical data
logger.info("Testing historical data retrieval...")
df = data_provider.get_historical_data('ETH/USDT', '1m', limit=5, refresh=True)
if df is not None and not df.empty:
logger.info(f"Historical data: {len(df)} rows")
logger.info(f"Latest price: ${df['close'].iloc[-1]:.2f}")
logger.info(f"Latest timestamp: {df.index[-1]}")
else:
logger.error("No historical data available!")
return True
except Exception as e:
logger.error(f"Data provider test failed: {e}")
return False
def test_dashboard_api():
"""Test if dashboard API is responding"""
logger.info("=== TESTING DASHBOARD API ===")
try:
# Test main dashboard page
response = requests.get("http://127.0.0.1:8050", timeout=5)
logger.info(f"Dashboard main page status: {response.status_code}")
if response.status_code == 200:
logger.info("Dashboard is responding")
# Check if there are any JavaScript errors in the page
content = response.text
if 'error' in content.lower():
logger.warning("Possible errors found in dashboard HTML")
return True
else:
logger.error(f"Dashboard returned status {response.status_code}")
return False
except Exception as e:
logger.error(f"Dashboard API test failed: {e}")
return False
def test_dashboard_callbacks():
"""Test dashboard callback updates"""
logger.info("=== TESTING DASHBOARD CALLBACKS ===")
try:
# Test the callback endpoint (this would need to be exposed)
# For now, just check if the dashboard is serving content
# Wait a bit and check again
time.sleep(2)
response = requests.get("http://127.0.0.1:8050", timeout=5)
if response.status_code == 200:
logger.info("Dashboard callbacks appear to be working")
return True
else:
logger.error("Dashboard callbacks may be stuck")
return False
except Exception as e:
logger.error(f"Dashboard callback test failed: {e}")
return False
def main():
"""Run all diagnostic tests"""
logger.info("DASHBOARD DIAGNOSTIC TOOL")
logger.info("=" * 50)
results = {
'data_provider': test_data_provider(),
'dashboard_api': test_dashboard_api(),
'dashboard_callbacks': test_dashboard_callbacks()
}
logger.info("=" * 50)
logger.info("DIAGNOSTIC RESULTS:")
for test_name, result in results.items():
status = "PASS" if result else "FAIL"
logger.info(f" {test_name}: {status}")
if all(results.values()):
logger.info("All tests passed - issue may be browser-side")
logger.info("Try refreshing the dashboard at http://127.0.0.1:8050")
else:
logger.error("Issues detected - check logs above")
logger.info("Recommendations:")
if not results['data_provider']:
logger.info(" - Check internet connection")
logger.info(" - Verify Binance API is accessible")
if not results['dashboard_api']:
logger.info(" - Restart the dashboard")
logger.info(" - Check if port 8050 is blocked")
if not results['dashboard_callbacks']:
logger.info(" - Dashboard may be frozen")
logger.info(" - Consider restarting")
if __name__ == "__main__":
main()

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#!/usr/bin/env python3
"""
Debug script for MEXC API authentication
"""
import os
import hmac
import hashlib
import time
import requests
from urllib.parse import urlencode
from dotenv import load_dotenv
# Load environment variables
load_dotenv()
def debug_mexc_auth():
"""Debug MEXC API authentication step by step"""
api_key = os.getenv('MEXC_API_KEY')
api_secret = os.getenv('MEXC_SECRET_KEY')
print("="*60)
print("MEXC API AUTHENTICATION DEBUG")
print("="*60)
print(f"API Key: {api_key}")
print(f"API Secret: {api_secret[:10]}...{api_secret[-10:]}")
print()
# Test 1: Public API (no auth required)
print("1. Testing Public API (ping)...")
try:
response = requests.get("https://api.mexc.com/api/v3/ping")
print(f" Status: {response.status_code}")
print(f" Response: {response.json()}")
print(" ✅ Public API works")
except Exception as e:
print(f" ❌ Public API failed: {e}")
return
print()
# Test 2: Get server time
print("2. Testing Server Time...")
try:
response = requests.get("https://api.mexc.com/api/v3/time")
server_time_data = response.json()
server_time = server_time_data['serverTime']
print(f" Server Time: {server_time}")
print(" ✅ Server time retrieved")
except Exception as e:
print(f" ❌ Server time failed: {e}")
return
print()
# Test 3: Manual signature generation and account request
print("3. Testing Authentication (manual signature)...")
# Get server time for accurate timestamp
try:
server_response = requests.get("https://api.mexc.com/api/v3/time")
server_time = server_response.json()['serverTime']
print(f" Using Server Time: {server_time}")
except:
server_time = int(time.time() * 1000)
print(f" Using Local Time: {server_time}")
# Parameters for account endpoint
params = {
'timestamp': server_time,
'recvWindow': 10000 # Increased receive window
}
print(f" Timestamp: {server_time}")
print(f" Params: {params}")
# Generate signature manually
# According to MEXC documentation, parameters should be sorted
sorted_params = sorted(params.items())
query_string = urlencode(sorted_params)
print(f" Query String: {query_string}")
# MEXC documentation shows signature in lowercase
signature = hmac.new(
api_secret.encode('utf-8'),
query_string.encode('utf-8'),
hashlib.sha256
).hexdigest()
print(f" Generated Signature (hex): {signature}")
print(f" API Secret used: {api_secret[:5]}...{api_secret[-5:]}")
print(f" Query string length: {len(query_string)}")
print(f" Signature length: {len(signature)}")
print(f" Generated Signature: {signature}")
# Add signature to params
params['signature'] = signature
# Make the request
headers = {
'X-MEXC-APIKEY': api_key
}
print(f" Headers: {headers}")
print(f" Final Params: {params}")
try:
response = requests.get(
"https://api.mexc.com/api/v3/account",
params=params,
headers=headers
)
print(f" Status Code: {response.status_code}")
print(f" Response Headers: {dict(response.headers)}")
if response.status_code == 200:
account_data = response.json()
print(f" ✅ Authentication successful!")
print(f" Account Type: {account_data.get('accountType', 'N/A')}")
print(f" Can Trade: {account_data.get('canTrade', 'N/A')}")
print(f" Can Withdraw: {account_data.get('canWithdraw', 'N/A')}")
print(f" Can Deposit: {account_data.get('canDeposit', 'N/A')}")
print(f" Number of balances: {len(account_data.get('balances', []))}")
# Show USDT balance
for balance in account_data.get('balances', []):
if balance['asset'] == 'USDT':
print(f" 💰 USDT Balance: {balance['free']} (locked: {balance['locked']})")
break
else:
print(f" ❌ Authentication failed!")
print(f" Response: {response.text}")
# Try to parse error
try:
error_data = response.json()
print(f" Error Code: {error_data.get('code', 'N/A')}")
print(f" Error Message: {error_data.get('msg', 'N/A')}")
except:
pass
except Exception as e:
print(f" ❌ Request failed: {e}")
if __name__ == "__main__":
debug_mexc_auth()

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#!/usr/bin/env python3
"""
Debug Orchestrator Methods - Test enhanced orchestrator method availability
"""
import sys
from pathlib import Path
project_root = Path(__file__).parent
sys.path.insert(0, str(project_root))
def debug_orchestrator_methods():
"""Debug orchestrator method availability"""
print("=== DEBUGGING ORCHESTRATOR METHODS ===")
try:
# Import the classes we need
from core.enhanced_orchestrator import EnhancedTradingOrchestrator
from core.data_provider import DataProvider
from core.orchestrator import TradingOrchestrator
print("✓ Imports successful")
# Create basic data provider (no async)
dp = DataProvider()
print("✓ DataProvider created")
# Create basic orchestrator first
basic_orch = TradingOrchestrator(dp)
print("✓ Basic TradingOrchestrator created")
# Test basic orchestrator methods
basic_methods = ['calculate_enhanced_pivot_reward', 'build_comprehensive_rl_state']
print("\nBasic TradingOrchestrator methods:")
for method in basic_methods:
available = hasattr(basic_orch, method)
print(f" {method}: {'' if available else ''}")
# Now test Enhanced orchestrator class methods (not instantiated)
print("\nEnhancedTradingOrchestrator class methods:")
for method in basic_methods:
available = hasattr(EnhancedTradingOrchestrator, method)
print(f" {method}: {'' if available else ''}")
# Check what methods are actually in the EnhancedTradingOrchestrator
print(f"\nEnhancedTradingOrchestrator all methods:")
all_methods = [m for m in dir(EnhancedTradingOrchestrator) if not m.startswith('_')]
enhanced_methods = [m for m in all_methods if 'enhanced' in m.lower() or 'comprehensive' in m.lower() or 'pivot' in m.lower()]
print(f" Total methods: {len(all_methods)}")
print(f" Enhanced/comprehensive/pivot methods: {enhanced_methods}")
# Test specific methods we're looking for
target_methods = [
'calculate_enhanced_pivot_reward',
'build_comprehensive_rl_state',
'_get_symbol_correlation'
]
print(f"\nTarget methods in EnhancedTradingOrchestrator:")
for method in target_methods:
if hasattr(EnhancedTradingOrchestrator, method):
print(f"{method}: Found")
else:
print(f"{method}: Missing")
# Check if it's a similar name
similar = [m for m in all_methods if method.replace('_', '').lower() in m.replace('_', '').lower()]
if similar:
print(f" Similar: {similar}")
print("\n=== DEBUG COMPLETE ===")
except Exception as e:
print(f"✗ Debug failed: {e}")
import traceback
traceback.print_exc()
if __name__ == "__main__":
debug_orchestrator_methods()

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#!/usr/bin/env python3
"""
Debug simple callback to see exact error
"""
import requests
import json
def debug_simple_callback():
"""Debug the simple callback"""
try:
callback_data = {
"output": "test-output.children",
"inputs": [
{
"id": "test-interval",
"property": "n_intervals",
"value": 1
}
]
}
print("Testing simple dashboard callback...")
response = requests.post(
'http://127.0.0.1:8052/_dash-update-component',
json=callback_data,
timeout=15,
headers={'Content-Type': 'application/json'}
)
print(f"Status Code: {response.status_code}")
if response.status_code == 500:
print("Error response:")
print(response.text)
else:
print("Success response:")
print(response.text[:500])
except Exception as e:
print(f"Request failed: {e}")
if __name__ == "__main__":
debug_simple_callback()

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#!/usr/bin/env python3
"""
Trading Activity Diagnostic Script
Debug why no trades are happening after 6 hours
"""
import logging
import asyncio
from datetime import datetime, timedelta
import pandas as pd
import numpy as np
# Setup logging
logging.basicConfig(level=logging.INFO, format='%(asctime)s - %(name)s - %(levelname)s - %(message)s')
logger = logging.getLogger(__name__)
async def diagnose_trading_system():
"""Comprehensive diagnosis of trading system"""
logger.info("=== TRADING SYSTEM DIAGNOSTIC ===")
try:
# Import core components
from core.config import get_config
from core.data_provider import DataProvider
from core.enhanced_orchestrator import EnhancedTradingOrchestrator
# Initialize components
config = get_config()
data_provider = DataProvider()
orchestrator = EnhancedTradingOrchestrator(
data_provider=data_provider,
symbols=['ETH/USDT', 'BTC/USDT'],
enhanced_rl_training=True
)
logger.info("✅ Components initialized successfully")
# 1. Check data availability
logger.info("\n=== DATA AVAILABILITY CHECK ===")
for symbol in ['ETH/USDT', 'BTC/USDT']:
for timeframe in ['1m', '5m', '1h']:
try:
data = data_provider.get_historical_data(symbol, timeframe, limit=10)
if data is not None and not data.empty:
logger.info(f"{symbol} {timeframe}: {len(data)} bars available")
logger.info(f" Last price: ${data['close'].iloc[-1]:.2f}")
else:
logger.error(f"{symbol} {timeframe}: NO DATA")
except Exception as e:
logger.error(f"{symbol} {timeframe}: ERROR - {e}")
# 2. Check model status
logger.info("\n=== MODEL STATUS CHECK ===")
model_status = orchestrator.get_loaded_models_status() if hasattr(orchestrator, 'get_loaded_models_status') else {}
logger.info(f"Loaded models: {model_status}")
# 3. Check confidence thresholds
logger.info("\n=== CONFIDENCE THRESHOLD CHECK ===")
logger.info(f"Entry threshold: {getattr(orchestrator, 'confidence_threshold_open', 'UNKNOWN')}")
logger.info(f"Exit threshold: {getattr(orchestrator, 'confidence_threshold_close', 'UNKNOWN')}")
logger.info(f"Config threshold: {config.orchestrator.get('confidence_threshold', 'UNKNOWN')}")
# 4. Test decision making
logger.info("\n=== DECISION MAKING TEST ===")
try:
decisions = await orchestrator.make_coordinated_decisions()
logger.info(f"Generated {len(decisions)} decisions")
for symbol, decision in decisions.items():
if decision:
logger.info(f"{symbol}: {decision.action} "
f"(confidence: {decision.confidence:.3f}, "
f"price: ${decision.price:.2f})")
else:
logger.warning(f"{symbol}: No decision generated")
except Exception as e:
logger.error(f"❌ Decision making failed: {e}")
# 5. Test cold start predictions
logger.info("\n=== COLD START PREDICTIONS TEST ===")
try:
await orchestrator.ensure_predictions_available()
logger.info("✅ Cold start predictions system working")
except Exception as e:
logger.error(f"❌ Cold start predictions failed: {e}")
# 6. Check cross-asset signals
logger.info("\n=== CROSS-ASSET SIGNALS TEST ===")
try:
from core.unified_data_stream import UniversalDataStream
# Create mock universal stream for testing
mock_stream = type('MockStream', (), {})()
mock_stream.get_latest_data = lambda symbol: {'price': 2500.0 if 'ETH' in symbol else 35000.0}
mock_stream.get_market_structure = lambda symbol: {'trend': 'NEUTRAL', 'strength': 0.5}
mock_stream.get_cob_data = lambda symbol: {'imbalance': 0.0, 'depth': 'BALANCED'}
btc_analysis = await orchestrator._analyze_btc_price_action(mock_stream)
logger.info(f"BTC analysis result: {btc_analysis}")
eth_decision = await orchestrator._make_eth_decision_from_btc_signals(
{'signal': 'NEUTRAL', 'strength': 0.5},
{'signal': 'NEUTRAL', 'imbalance': 0.0}
)
logger.info(f"ETH decision result: {eth_decision}")
except Exception as e:
logger.error(f"❌ Cross-asset signals failed: {e}")
# 7. Simulate trade with lower thresholds
logger.info("\n=== SIMULATED TRADE TEST ===")
try:
# Create mock prediction with low confidence
from core.enhanced_orchestrator import EnhancedPrediction
mock_prediction = EnhancedPrediction(
model_name="TEST",
timeframe="1m",
action="BUY",
confidence=0.30, # Lower confidence
overall_action="BUY",
overall_confidence=0.30,
timeframe_predictions=[],
reasoning="Test prediction"
)
# Test if this would generate a trade
current_price = 2500.0
quantity = 0.01
logger.info(f"Mock prediction: {mock_prediction.action} "
f"(confidence: {mock_prediction.confidence:.3f})")
if mock_prediction.confidence > 0.25: # Our new lower threshold
logger.info("✅ Would generate trade with new threshold")
else:
logger.warning("❌ Still below threshold")
except Exception as e:
logger.error(f"❌ Simulated trade test failed: {e}")
# 8. Check RL reward functions
logger.info("\n=== RL REWARD FUNCTION TEST ===")
try:
# Test reward calculation
mock_trade = {
'action': 'BUY',
'confidence': 0.75,
'price': 2500.0,
'timestamp': datetime.now()
}
mock_outcome = {
'net_pnl': 25.0, # $25 profit
'exit_price': 2525.0,
'duration': timedelta(minutes=15)
}
mock_market_data = {
'volatility': 0.03,
'order_flow_direction': 'bullish',
'order_flow_strength': 0.8
}
if hasattr(orchestrator, 'calculate_enhanced_pivot_reward'):
reward = orchestrator.calculate_enhanced_pivot_reward(
mock_trade, mock_market_data, mock_outcome
)
logger.info(f"✅ RL reward for profitable trade: {reward:.3f}")
else:
logger.warning("❌ Enhanced pivot reward function not available")
except Exception as e:
logger.error(f"❌ RL reward test failed: {e}")
logger.info("\n=== DIAGNOSTIC COMPLETE ===")
logger.info("Check results above to identify trading bottlenecks")
except Exception as e:
logger.error(f"Diagnostic failed: {e}")
import traceback
traceback.print_exc()
if __name__ == "__main__":
asyncio.run(diagnose_trading_system())