mirror of
https://github.com/Sabermrddz/QuantCore-FX.git
synced 2026-07-27 18:47:51 +00:00
saber
249 lines
8.3 KiB
Python
249 lines
8.3 KiB
Python
"""
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APEX Professional Trading System — Main Application Window
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Assembles all 6 tabs:
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- Tab 1: Dashboard (Layer 1 fundamental signals)
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- Tab 2: Monthly Entry (CPI + PMI data input)
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- Tab 3: Layer 2 Monitor (real-time technical analysis)
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- Tab 4: Confluence Signals (merged Layer 1 + Layer 2)
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- Tab 5: History (past signals)
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- Tab 6: Settings (configuration)
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Responsibilities:
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- Create QMainWindow with QTabWidget
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- Instantiate all UI tabs
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- Manage database connection
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- Run FRED API fetch in background thread
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- Run Alpha Vantage real-time data fetching
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- Connect inter-tab signals
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- Handle window events and cleanup
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"""
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from PyQt5.QtWidgets import QMainWindow, QTabWidget, QMessageBox
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from PyQt5.QtCore import QThread, pyqtSignal
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from typing import Dict, Optional
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import config
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from database import Database
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from layer2_technical import TechnicalAnalyzer
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from ui.dashboard_tab import DashboardTab
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from ui.entry_tab import MonthlyEntryTab
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from ui.layer2_monitor_tab import Layer2MonitorTab
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from ui.confluence_tab import ConfluenceSignalsTab
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from ui.history_tab import HistoryTab
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from ui.settings_tab import SettingsTab
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from fred_client import FredClient
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class FredFetchWorker(QThread):
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"""Background worker thread for fetching rates from FRED API."""
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# Signals
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rates_fetched = pyqtSignal(dict) # Emitted with {currency: rate} dict
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error_occurred = pyqtSignal(str) # Emitted on error
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def __init__(self, db: Database):
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"""
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Initialize FRED fetch worker.
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Args:
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db: Database instance to save rates
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"""
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super().__init__()
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self.db = db
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self.client = FredClient()
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def run(self):
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"""
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Fetch rates from FRED API and save to database.
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"""
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try:
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if config.DEBUG:
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print("[Worker] Starting FRED rate fetch...")
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rates = self.client.fetch_all_rates()
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# Save to database
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for currency, rate in rates.items():
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if rate is not None:
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self.db.upsert_rate(currency, rate, source="FRED")
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if config.DEBUG:
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print("[Worker] FRED fetch complete")
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self.rates_fetched.emit(rates)
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except Exception as e:
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error_msg = f"FRED fetch error: {str(e)}"
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if config.DEBUG:
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print(f"[Worker] {error_msg}")
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self.error_occurred.emit(error_msg)
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class MainWindow(QMainWindow):
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"""Main application window — Professional hybrid trading system."""
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def __init__(self):
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"""Initialize main window."""
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super().__init__()
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# Initialize database
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try:
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self.db = Database()
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except Exception as e:
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QMessageBox.critical(
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self,
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"Database Error",
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f"Failed to initialize database: {e}\n\nPlease check your configuration."
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)
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raise
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# Initialize Layer 2 components
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bars = config.TIMEFRAMES[config.DEFAULT_TIMEFRAME]["bars"]
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self.tech_analyzer = TechnicalAnalyzer(lookback=bars)
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# UI components
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self.dashboard_tab = None
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self.entry_tab = None
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self.layer2_tab = None
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self.confluence_tab = None
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self.history_tab = None
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self.settings_tab = None
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# Worker threads
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self.fred_worker = None
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self._init_ui()
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self._connect_signals()
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self._setup_auto_fetch()
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def _init_ui(self):
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"""Build the main window UI."""
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self.setWindowTitle(config.APP_TITLE)
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self.setGeometry(100, 100, config.WINDOW_WIDTH, config.WINDOW_HEIGHT)
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# Tab widget
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tabs = QTabWidget()
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# Tab 1: Dashboard (Layer 1)
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self.dashboard_tab = DashboardTab(self.db)
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tabs.addTab(self.dashboard_tab, config.TAB_NAMES["dashboard"])
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# Tab 2: Monthly Entry (Data input)
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self.entry_tab = MonthlyEntryTab(self.db)
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tabs.addTab(self.entry_tab, config.TAB_NAMES["entry"])
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# Tab 3: Layer 2 Monitor (Real-time technical)
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self.layer2_tab = Layer2MonitorTab(self.tech_analyzer)
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tabs.addTab(self.layer2_tab, config.TAB_NAMES["layer2"])
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# Tab 4: Confluence Signals (Layer 1 + Layer 2)
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self.confluence_tab = ConfluenceSignalsTab(self.db, self.tech_analyzer)
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tabs.addTab(self.confluence_tab, config.TAB_NAMES["confluence"])
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# Tab 5: History
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self.history_tab = HistoryTab(self.db)
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tabs.addTab(self.history_tab, config.TAB_NAMES["history"])
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# Tab 6: Settings
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self.settings_tab = SettingsTab()
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tabs.addTab(self.settings_tab, config.TAB_NAMES["settings"])
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# Set main widget
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self.setCentralWidget(tabs)
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def _connect_signals(self):
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"""Connect inter-tab signals."""
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# Entry tab saves data → Dashboard tab refreshes
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self.entry_tab.data_saved.connect(self.dashboard_tab.on_data_saved)
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# Entry tab saves data → History tab refreshes
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self.entry_tab.data_saved.connect(self.history_tab.refresh_history)
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# Dashboard generates signal → Confluence tab receives signal
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self.dashboard_tab.signal_generated.connect(self._on_dashboard_signal)
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# Dashboard requests FRED fetch → Start worker thread
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self.dashboard_tab.fetch_rates_requested.connect(self._fetch_rates)
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def _setup_auto_fetch(self):
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"""Auto-fetch rates on startup if enabled."""
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if config.AUTO_FETCH_RATES_ON_STARTUP:
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if config.DEBUG:
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print("[Main] Auto-fetch enabled, fetching rates on startup...")
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self._fetch_rates()
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def _fetch_rates(self):
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"""
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Trigger background FRED rate fetch.
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Emits results to dashboard when complete.
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"""
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if self.fred_worker is not None and self.fred_worker.isRunning():
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# Already fetching
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return
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self.fred_worker = FredFetchWorker(self.db)
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self.fred_worker.rates_fetched.connect(self._on_rates_fetched)
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self.fred_worker.error_occurred.connect(self._on_fetch_error)
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self.fred_worker.start()
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def _on_rates_fetched(self, rates: Dict[str, Optional[float]]):
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"""
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Handle successful FRED fetch.
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Args:
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rates: Dict mapping currency to rate
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"""
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if config.DEBUG:
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print("[Main] Rates fetched successfully, updating dashboard...")
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# Update dashboard display
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self.dashboard_tab.on_rates_updated(rates)
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def _on_fetch_error(self, error_msg: str):
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"""
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Handle FRED fetch error.
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Args:
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error_msg: Error message string
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"""
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print(f"[ERROR] {error_msg}")
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# Don't show error message to user; display gracefully in dashboard
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def _on_dashboard_signal(self, strongest: str, weakest: str, gap: float,
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bias_matrix: dict = None):
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"""
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Handle dashboard signal generation.
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Pass to confluence tab for Layer 2 analysis.
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Args:
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strongest: Strongest currency
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weakest: Weakest currency
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gap: Gap score
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bias_matrix: Monthly directional bias matrix from Layer 1
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"""
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if config.DEBUG:
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print(f"[Main] Signal generated: {strongest}/{weakest} gap={gap:.1f}")
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# Update confluence tab with new Layer 1 signal + bias matrix
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self.confluence_tab.set_layer1_signal(strongest, weakest, gap, bias_matrix)
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def closeEvent(self, event):
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"""Handle window close event."""
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try:
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# Stop any running threads
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if self.fred_worker is not None and self.fred_worker.isRunning():
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self.fred_worker.quit()
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self.fred_worker.wait()
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# Stop Layer 2 monitoring
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if self.layer2_tab:
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self.layer2_tab.closeEvent(event)
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# Close database
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self.db.close()
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event.accept()
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except Exception as e:
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print(f"[ERROR] Error during shutdown: {e}")
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event.accept()
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