Harwinder
1100b9eaf2
- XAU/XAG always route to Yahoo Finance and skip Twelve Data entirely (excluded from batch prefetch, served per-symbol via yfinance). - Daily chart cleanly skipped for gold/silver — engine drops it from MTF. - Telegram /scan limited to EURUSD, USDJPY, GBPUSD, XAUUSD. - SCAN_TIMEFRAMES reduced to single H1 primary; engine still pulls M15+H1+D1 internally via confirmation TFs (halves API credits per scan). - Default confirmation TFs swapped H4 -> D1 in config and main.py. - mtf_agreement_threshold kept at 2-of-3. - CLAUDE.md cleaned up — old XAUUSD/synthetic-data bug reports removed. Co-Authored-By: Claude Opus 4.7 <noreply@anthropic.com>
519 lines
22 KiB
Python
519 lines
22 KiB
Python
#!/usr/bin/env python3
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"""
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Forex Signal Intelligence Platform
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====================================
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Main entry point. Runs full analysis and outputs formatted signal reports.
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Usage:
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python main.py # Analyze all major pairs
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python main.py --pairs EURUSD GBPUSD # Specific pairs
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python main.py --timeframe H4 # Different primary TF
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python main.py --json # JSON output
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python main.py --watch # Continuous monitoring mode
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"""
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import argparse
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import json
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import logging
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import sys
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import time
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from datetime import datetime, timezone
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from typing import List
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# Force UTF-8 output on Windows so box-drawing / Unicode chars render correctly
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if hasattr(sys.stdout, "reconfigure"):
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sys.stdout.reconfigure(encoding="utf-8")
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if hasattr(sys.stderr, "reconfigure"):
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sys.stderr.reconfigure(encoding="utf-8")
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from config import (
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PlatformConfig, Timeframe, SignalStrength,
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MAJOR_PAIRS, CROSS_PAIRS,
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)
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from signal_aggregator import SignalAggregator, SignalReport
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# ══════════════════════════════════════════════════════════════════
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# TERMINAL FORMATTING
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# ══════════════════════════════════════════════════════════════════
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class Colors:
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"""ANSI color codes for terminal output."""
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RESET = "\033[0m"
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BOLD = "\033[1m"
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DIM = "\033[2m"
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UNDERLINE = "\033[4m"
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RED = "\033[91m"
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GREEN = "\033[92m"
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YELLOW = "\033[93m"
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BLUE = "\033[94m"
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MAGENTA = "\033[95m"
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CYAN = "\033[96m"
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WHITE = "\033[97m"
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GRAY = "\033[90m"
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BG_RED = "\033[41m"
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BG_GREEN = "\033[42m"
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BG_YELLOW = "\033[43m"
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BG_BLUE = "\033[44m"
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BG_MAGENTA = "\033[45m"
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BG_CYAN = "\033[46m"
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def signal_color(signal: SignalStrength) -> str:
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"""Get color for a signal strength."""
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return {
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SignalStrength.STRONG_BUY: Colors.GREEN + Colors.BOLD,
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SignalStrength.BUY: Colors.GREEN,
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SignalStrength.NEUTRAL: Colors.GRAY,
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SignalStrength.SELL: Colors.RED,
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SignalStrength.STRONG_SELL: Colors.RED + Colors.BOLD,
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}.get(signal, Colors.RESET)
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def quality_color(quality: str) -> str:
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"""Get color for signal quality grade."""
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return {
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"A+": Colors.GREEN + Colors.BOLD,
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"A": Colors.GREEN,
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"B": Colors.CYAN,
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"C": Colors.YELLOW,
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"D": Colors.GRAY,
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"F": Colors.DIM,
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}.get(quality, Colors.RESET)
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def score_bar(score: float, width: int = 30) -> str:
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"""Create a visual score bar from -100 to +100."""
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normalized = (score + 100) / 200 # 0 to 1
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filled = int(normalized * width)
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center = width // 2
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bar = ""
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for i in range(width):
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if i == center:
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bar += "│"
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elif (score >= 0 and center < i <= filled) or \
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(score < 0 and filled <= i < center):
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bar += "█"
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else:
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bar += "░"
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if score >= 0:
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color = Colors.GREEN if score > 20 else Colors.GRAY
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else:
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color = Colors.RED if score < -20 else Colors.GRAY
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return f"{color}{bar}{Colors.RESET}"
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def print_header():
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"""Print the platform header."""
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now = datetime.now(timezone.utc).strftime("%Y-%m-%d %H:%M:%S UTC")
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width = 80
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print(f"\n{Colors.CYAN}{'═' * width}{Colors.RESET}")
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print(f"{Colors.BOLD}{Colors.CYAN} ╔═══════════════════════════════════════════════════════╗{Colors.RESET}")
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print(f"{Colors.BOLD}{Colors.CYAN} ║ FOREX SIGNAL INTELLIGENCE PLATFORM ║{Colors.RESET}")
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print(f"{Colors.BOLD}{Colors.CYAN} ║ Multi-Layer Signal Analysis Engine ║{Colors.RESET}")
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print(f"{Colors.BOLD}{Colors.CYAN} ╚═══════════════════════════════════════════════════════╝{Colors.RESET}")
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print(f"{Colors.GRAY} Scan Time: {now}{Colors.RESET}")
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print(f"{Colors.CYAN}{'═' * width}{Colors.RESET}\n")
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def print_summary_table(reports: List[SignalReport]):
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"""Print a summary table of all pairs."""
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print(f"{Colors.BOLD}{Colors.WHITE} ┌─────────────┬───────────┬──────────────────────────────────┬────────┬────────────┐{Colors.RESET}")
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print(f"{Colors.BOLD}{Colors.WHITE} │ Pair │ Signal │ Score │ Grade │ Confidence │{Colors.RESET}")
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print(f"{Colors.BOLD}{Colors.WHITE} ├─────────────┼───────────┼──────────────────────────────────┼────────┼────────────┤{Colors.RESET}")
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for r in reports:
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sig = r.final_signal.name.replace("_", " ")
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sc = signal_color(r.final_signal)
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qc = quality_color(r.signal_quality)
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bar = score_bar(r.final_score, 30)
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pair = f"{r.display_name:<11}"
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signal_str = f"{sc}{sig:<9}{Colors.RESET}"
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grade_str = f"{qc}{r.signal_quality:<6}{Colors.RESET}"
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conf_str = f"{r.final_confidence:5.1f}%"
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# Add warning indicator
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warn = ""
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if r.event_risk == "danger":
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warn = f" {Colors.RED}⚠{Colors.RESET}"
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elif r.event_risk == "caution":
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warn = f" {Colors.YELLOW}△{Colors.RESET}"
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print(f" │ {pair} │ {signal_str} │ {bar} │ {grade_str} │ {conf_str:>8}{warn} │")
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print(f"{Colors.BOLD}{Colors.WHITE} └─────────────┴───────────┴──────────────────────────────────┴────────┴────────────┘{Colors.RESET}")
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# Legend
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print(f"\n{Colors.GRAY} Legend: "
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f"{Colors.GREEN}██ Bullish{Colors.GRAY} | "
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f"{Colors.RED}██ Bearish{Colors.GRAY} | "
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f"│ Center (0) | "
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f"{Colors.RED}⚠ Event Risk{Colors.GRAY} | "
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f"{Colors.YELLOW}△ Caution{Colors.RESET}")
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def print_detailed_report(report: SignalReport):
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"""Print detailed analysis for a single pair."""
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sc = signal_color(report.final_signal)
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qc = quality_color(report.signal_quality)
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sig_name = report.final_signal.name.replace("_", " ")
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print(f"\n{Colors.CYAN}{'─' * 80}{Colors.RESET}")
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print(f" {Colors.BOLD}{Colors.WHITE}{report.display_name}{Colors.RESET}"
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f" │ Price: {Colors.BOLD}{report.current_price:.5f}{Colors.RESET}"
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f" │ Regime: {Colors.CYAN}{report.market_regime}{Colors.RESET}"
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f" │ Vol: {report.volatility_regime}")
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print(f"\n {Colors.BOLD}SIGNAL:{Colors.RESET} {sc}{sig_name}{Colors.RESET}"
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f" │ Score: {sc}{report.final_score:+.1f}{Colors.RESET}"
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f" │ Grade: {qc}{report.signal_quality}{Colors.RESET}"
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f" │ Confidence: {report.final_confidence:.0f}%")
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print(f" {Colors.BOLD}Action:{Colors.RESET} {report.action_recommendation}")
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# Multi-timeframe breakdown
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if report.mtf_signals:
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print(f"\n {Colors.BOLD}Multi-Timeframe:{Colors.RESET}", end="")
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mtf_agree = f" {Colors.GREEN}✓ ALIGNED{Colors.RESET}" if report.mtf_agreement else f" {Colors.YELLOW}✗ DIVERGENT{Colors.RESET}"
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print(mtf_agree)
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for tf, sig in report.mtf_signals.items():
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tf_sc = signal_color(sig)
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tf_score = report.mtf_scores.get(tf, 0)
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print(f" {tf:>5}: {tf_sc}{sig.name.replace('_', ' '):<12}{Colors.RESET} ({tf_score:+.1f})")
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# Indicators detail
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if report.primary_analysis:
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print(f"\n {Colors.BOLD}Indicators ({report.primary_analysis.timeframe}):{Colors.RESET}")
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for name, ind in report.primary_analysis.indicators.items():
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if name.startswith("_") or ind.weight == 0:
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continue
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isc = signal_color(ind.signal)
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ind_name = f"{ind.name:<18}"
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print(f" {ind_name} {isc}{ind.signal.name.replace('_', ' '):<12}{Colors.RESET}"
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f" ({ind.confidence:.0f}%) │ {Colors.GRAY}{ind.description}{Colors.RESET}")
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# Bullish reasons
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if report.bullish_reasons:
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print(f"\n {Colors.GREEN}▲ Bullish Factors:{Colors.RESET}")
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for reason in report.bullish_reasons[:5]:
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print(f" {Colors.GREEN}+{Colors.RESET} {reason}")
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# Bearish reasons
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if report.bearish_reasons:
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print(f"\n {Colors.RED}▼ Bearish Factors:{Colors.RESET}")
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for reason in report.bearish_reasons[:5]:
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print(f" {Colors.RED}-{Colors.RESET} {reason}")
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# Warnings
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if report.warnings:
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print(f"\n {Colors.YELLOW}⚠ Warnings:{Colors.RESET}")
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for warning in report.warnings:
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print(f" {Colors.YELLOW}!{Colors.RESET} {warning}")
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# News context
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if report.news_description and report.news_description != "Neutral news sentiment":
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print(f"\n {Colors.MAGENTA}📰 News:{Colors.RESET} {report.news_description}")
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if report.event_description and report.event_risk != "clear":
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print(f" {Colors.YELLOW}📅 Event:{Colors.RESET} {report.event_description}")
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# Trade setup
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if report.trade_setup:
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ts = report.trade_setup
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dir_color = Colors.GREEN if ts.direction == "BUY" else Colors.RED
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print(f"\n {Colors.BOLD}Trade Setup:{Colors.RESET}")
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print(f" Direction: {dir_color}{ts.direction}{Colors.RESET}")
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print(f" Entry: {ts.entry_price:.5f}")
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print(f" Stop Loss: {Colors.RED}{ts.stop_loss:.5f}{Colors.RESET} ({ts.risk_pips:.1f} pips)")
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print(f" Take Profit 1: {Colors.GREEN}{ts.take_profit_1:.5f}{Colors.RESET} ({ts.reward_pips:.1f} pips)")
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print(f" Take Profit 2: {Colors.GREEN}{ts.take_profit_2:.5f}{Colors.RESET}")
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print(f" Risk:Reward: 1:{ts.risk_reward:.1f}")
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# Key levels
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if report.primary_analysis and report.primary_analysis.key_levels:
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levels = report.primary_analysis.key_levels
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print(f"\n {Colors.BOLD}Key Levels:{Colors.RESET}")
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level_names = ["r3", "r2", "r1", "pivot", "s1", "s2", "s3"]
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for lvl in level_names:
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if lvl in levels:
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val = levels[lvl]
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if val > report.current_price:
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color = Colors.RED # resistance
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else:
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color = Colors.GREEN # support
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label = lvl.upper()
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print(f" {label:>6}: {color}{val:.5f}{Colors.RESET}")
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def print_event_calendar(reports: List[SignalReport]):
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"""Print upcoming economic events affecting watched pairs."""
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events_shown = set()
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has_events = False
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for report in reports:
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if report.event_risk != "clear" and report.event_description not in events_shown:
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if not has_events:
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print(f"\n{Colors.YELLOW}{Colors.BOLD} 📅 ECONOMIC CALENDAR ALERTS{Colors.RESET}")
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has_events = True
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events_shown.add(report.event_description)
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risk_color = Colors.RED if report.event_risk == "danger" else Colors.YELLOW
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print(f" {risk_color}● {report.event_description}{Colors.RESET} → affects {report.display_name}")
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if not has_events:
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print(f"\n{Colors.GRAY} 📅 No high-impact events in the near term{Colors.RESET}")
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def report_to_dict(report: SignalReport) -> dict:
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"""Convert a SignalReport to a JSON-serializable dict."""
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d = {
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"symbol": report.symbol,
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"display_name": report.display_name,
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"timestamp": report.timestamp,
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"current_price": report.current_price,
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"signal": report.final_signal.name,
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"score": round(report.final_score, 2),
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"confidence": round(report.final_confidence, 2),
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"quality": report.signal_quality,
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"action": report.action_recommendation,
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"market_regime": report.market_regime,
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"volatility_regime": report.volatility_regime,
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"mtf_agreement": report.mtf_agreement,
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"mtf_signals": {k: v.name for k, v in report.mtf_signals.items()},
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"event_risk": report.event_risk,
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"event_description": report.event_description,
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"news_sentiment": round(report.news_sentiment, 3),
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"bullish_reasons": report.bullish_reasons,
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"bearish_reasons": report.bearish_reasons,
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"warnings": report.warnings,
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}
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if report.trade_setup:
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ts = report.trade_setup
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d["trade_setup"] = {
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"direction": ts.direction,
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"entry": ts.entry_price,
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"stop_loss": ts.stop_loss,
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"take_profit_1": ts.take_profit_1,
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"take_profit_2": ts.take_profit_2,
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"risk_reward": ts.risk_reward,
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"risk_pips": round(ts.risk_pips, 1),
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"reward_pips": round(ts.reward_pips, 1),
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}
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if report.primary_analysis:
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d["indicators"] = {}
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for name, ind in report.primary_analysis.indicators.items():
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if not name.startswith("_"):
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d["indicators"][name] = {
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"signal": ind.signal.name,
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"confidence": round(ind.confidence, 1),
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"description": ind.description,
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}
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d["key_levels"] = {
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k: round(v, 5) for k, v in report.primary_analysis.key_levels.items()
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}
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return d
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# ══════════════════════════════════════════════════════════════════
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# MAIN
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# ══════════════════════════════════════════════════════════════════
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def parse_args():
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parser = argparse.ArgumentParser(
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description="Forex Signal Intelligence Platform",
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formatter_class=argparse.RawDescriptionHelpFormatter,
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epilog="""
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Examples:
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python main.py Analyze all major pairs (H1)
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python main.py --pairs EURUSD GBPUSD Analyze specific pairs
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python main.py --timeframe H4 Use 4-hour as primary TF
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python main.py --all Include cross pairs
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python main.py --json Output as JSON
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python main.py --detail Show detailed analysis per pair
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python main.py --watch Continuous monitoring (5min refresh)
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""",
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)
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parser.add_argument(
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"--pairs", nargs="+", default=None,
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help="Specific pairs to analyze (e.g., EURUSD GBPUSD)",
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)
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parser.add_argument(
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"--timeframe", "-tf", default="H1",
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choices=["M5", "M15", "M30", "H1", "H4", "D1"],
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help="Primary analysis timeframe (default: H1)",
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)
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parser.add_argument(
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"--all", action="store_true",
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help="Include cross pairs in analysis",
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)
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parser.add_argument(
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"--json", action="store_true",
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help="Output results as JSON",
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)
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parser.add_argument(
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"--detail", action="store_true",
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help="Show detailed analysis for each pair",
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)
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parser.add_argument(
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"--top", type=int, default=None,
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help="Show only top N signals by strength",
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)
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parser.add_argument(
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"--watch", action="store_true",
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help="Continuous monitoring mode (refreshes every 5 min)",
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)
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parser.add_argument(
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"--min-grade", default="F",
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choices=["A+", "A", "B", "C", "D", "F"],
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help="Minimum signal quality to display",
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)
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parser.add_argument(
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"--verbose", "-v", action="store_true",
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help="Enable debug logging",
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)
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return parser.parse_args()
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def symbol_from_name(name: str) -> str:
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"""
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Convert pair name like 'EURUSD' or 'XAUUSD' to internal symbol 'EURUSD=X'.
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Returns None for clearly invalid inputs (e.g. timeframe strings like '15M').
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"""
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clean = name.upper().replace("/", "").replace("_", "").replace("=X", "")
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if not clean.isalpha() or len(clean) < 5:
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print(f" Warning: '{name}' is not a valid pair symbol — skipping.")
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print(f" Hint: timeframes go in --timeframe (e.g. --timeframe M15), not --pairs.")
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return None
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return clean + "=X"
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def run_analysis(args) -> List[SignalReport]:
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"""Run a single analysis cycle."""
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config = PlatformConfig()
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# Configure timeframe
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tf_map = {
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"M5": Timeframe.M5, "M15": Timeframe.M15, "M30": Timeframe.M30,
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"H1": Timeframe.H1, "H4": Timeframe.H4, "D1": Timeframe.D1,
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}
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config.primary_timeframe = tf_map[args.timeframe]
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# Configure confirmation timeframes based on primary.
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# H1 uses M15 + D1 for high-conviction confluence (3-of-3 threshold).
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tf_confirmations = {
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"M5": [Timeframe.M1, Timeframe.M15],
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"M15": [Timeframe.H1, Timeframe.D1],
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"M30": [Timeframe.H1, Timeframe.D1],
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"H1": [Timeframe.M15, Timeframe.D1],
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"H4": [Timeframe.H1, Timeframe.D1],
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"D1": [Timeframe.H4, Timeframe.W1],
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}
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config.confirmation_timeframes = tf_confirmations.get(
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args.timeframe, [Timeframe.M15, Timeframe.D1]
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)
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# Configure pairs
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if args.pairs:
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symbols = [symbol_from_name(p) for p in args.pairs]
|
|
config.watch_pairs = [s for s in symbols if s is not None]
|
|
if not config.watch_pairs:
|
|
print(" Error: No valid pair symbols provided. Exiting.")
|
|
sys.exit(1)
|
|
elif args.all:
|
|
config.watch_pairs = MAJOR_PAIRS + CROSS_PAIRS
|
|
else:
|
|
config.watch_pairs = MAJOR_PAIRS
|
|
|
|
# Run analysis
|
|
aggregator = SignalAggregator(config)
|
|
reports = aggregator.analyze_all_pairs()
|
|
|
|
# Filter by grade
|
|
grade_order = ["A+", "A", "B", "C", "D", "F"]
|
|
min_idx = grade_order.index(args.min_grade) if args.min_grade in grade_order else len(grade_order) - 1
|
|
reports = [r for r in reports if grade_order.index(r.signal_quality) <= min_idx]
|
|
|
|
# Top N
|
|
if args.top:
|
|
reports = reports[:args.top]
|
|
|
|
return reports
|
|
|
|
|
|
def main():
|
|
args = parse_args()
|
|
|
|
# Setup logging
|
|
log_level = logging.DEBUG if args.verbose else logging.WARNING
|
|
logging.basicConfig(
|
|
level=log_level,
|
|
format="%(asctime)s [%(levelname)s] %(name)s: %(message)s",
|
|
datefmt="%H:%M:%S",
|
|
)
|
|
|
|
if args.watch:
|
|
# Continuous monitoring mode
|
|
print(f"{Colors.BOLD}Starting continuous monitoring mode (Ctrl+C to stop)...{Colors.RESET}")
|
|
while True:
|
|
try:
|
|
reports = run_analysis(args)
|
|
if args.json:
|
|
output = [report_to_dict(r) for r in reports]
|
|
print(json.dumps(output, indent=2))
|
|
else:
|
|
print("\033[2J\033[H") # clear screen
|
|
print_header()
|
|
print_summary_table(reports)
|
|
print_event_calendar(reports)
|
|
if args.detail:
|
|
for r in reports:
|
|
print_detailed_report(r)
|
|
print(f"\n{Colors.GRAY} Next refresh in 5 minutes...{Colors.RESET}")
|
|
|
|
time.sleep(300)
|
|
except KeyboardInterrupt:
|
|
print(f"\n{Colors.YELLOW}Monitoring stopped.{Colors.RESET}")
|
|
break
|
|
else:
|
|
# Single run
|
|
print(f"{Colors.GRAY} Fetching market data and running analysis...{Colors.RESET}\n")
|
|
reports = run_analysis(args)
|
|
|
|
if args.json:
|
|
output = [report_to_dict(r) for r in reports]
|
|
print(json.dumps(output, indent=2))
|
|
else:
|
|
print_header()
|
|
if reports:
|
|
print_summary_table(reports)
|
|
print_event_calendar(reports)
|
|
|
|
if args.detail:
|
|
for r in reports:
|
|
print_detailed_report(r)
|
|
else:
|
|
# Show detail for top signals only
|
|
actionable = [r for r in reports if r.signal_quality in ("A+", "A", "B")]
|
|
if actionable:
|
|
print(f"\n{Colors.BOLD}{Colors.WHITE} ═══ ACTIONABLE SIGNALS (Grade B or above) ═══{Colors.RESET}")
|
|
for r in actionable:
|
|
print_detailed_report(r)
|
|
else:
|
|
print(f"\n{Colors.GRAY} No high-grade signals detected. "
|
|
f"Use --detail for full breakdown or --min-grade C to see more.{Colors.RESET}")
|
|
else:
|
|
print(f"{Colors.YELLOW} No data available. Check your internet connection.{Colors.RESET}")
|
|
|
|
print(f"\n{Colors.CYAN}{'═' * 80}{Colors.RESET}")
|
|
print(f"{Colors.GRAY} Disclaimer: This tool is for educational/research purposes only.{Colors.RESET}")
|
|
print(f"{Colors.GRAY} Past performance ≠ future results. Always use proper risk management.{Colors.RESET}")
|
|
print(f"{Colors.CYAN}{'═' * 80}{Colors.RESET}\n")
|
|
|
|
|
|
if __name__ == "__main__":
|
|
main() |