import asyncio import json import logging import threading import time from pathlib import Path from flask import Flask, jsonify, render_template_string from analysis import CrashAnalysis from crash import CrashProcessor from engine import Engine from protocol import CrashProtocol # ============================================================ # APPLICATION SETUP # ============================================================ BASE_DIR = Path(__file__).resolve().parent with open( BASE_DIR / "config.json", "r", encoding="utf-8" ) as file: CONFIG = json.load(file) HOST = CONFIG.get( "dashboard", {} ).get("host", "127.0.0.1") PORT = int( CONFIG.get( "dashboard", {} ).get("port", 8000) ) app = Flask(__name__) logging.basicConfig( level=logging.INFO, format=( "%(asctime)s | " "%(levelname)s | " "%(name)s | " "%(message)s" ) ) logger = logging.getLogger("Dashboard") # ============================================================ # CORE SYSTEM COMPONENTS # ============================================================ protocol = CrashProtocol() crash = CrashProcessor() analysis = CrashAnalysis() engine = Engine() # ============================================================ # ENGINE STATE # ============================================================ engine_state = { "running": False, "connected": False, "messages": 0, "last_message": None, "last_message_time": None, "error": None, "started_at": None } engine_thread = None # ============================================================ # ENGINE MESSAGE PIPELINE # ============================================================ async def handle_engine_message(message): """ Complete message pipeline: WebSocket ↓ Protocol parser ↓ Crash processor ↓ Stored analysis data ↓ Dashboard """ engine_state["messages"] += 1 engine_state["last_message_time"] = time.time() try: packet = protocol.parse(message) engine_state["last_message"] = { "type": packet.get("type"), "format": packet.get("format"), "length": packet.get("length") } crash.process(packet) except Exception as error: engine_state["error"] = str(error) logger.exception( "Message processing error" ) async def engine_worker(): engine_state["running"] = True engine_state["started_at"] = time.time() engine_state["error"] = None try: await engine.run( message_handler=handle_engine_message ) except asyncio.CancelledError: raise except Exception as error: engine_state["error"] = str(error) logger.exception( "Engine worker stopped" ) finally: engine_state["running"] = False engine_state["connected"] = False def start_engine(): global engine_thread if ( engine_thread and engine_thread.is_alive() ): return False def runner(): asyncio.run( engine_worker() ) engine_thread = threading.Thread( target=runner, daemon=True ) engine_thread.start() return True # ============================================================ # DATA HELPERS # ============================================================ def get_history(): return crash.get_history(500) def get_prediction(): history = crash.get_history( max( analysis.minimum_samples, 500 ) ) return analysis.predict_range( history ) def get_analysis_snapshot(): history = crash.get_history(1000) return analysis.analyze( history ) def get_prediction_performance(): return analysis.performance() def safe_round(value, digits=4): if value is None: return None try: return round( float(value), digits ) except ( TypeError, ValueError ): return None # ============================================================ # API ROUTES # ============================================================ @app.route("/api/status") def api_status(): history = get_history() latest = ( history[-1] if history else None ) prediction = get_prediction() return jsonify({ "system": "BC Crash Research System", "running": engine_state["running"], "connected": engine_state["connected"], "messages": engine_state["messages"], "last_message_time": engine_state["last_message_time"], "error": engine_state["error"], "samples": len(history), "latest": latest, "prediction": prediction }) @app.route("/api/history") def api_history(): history = get_history() return jsonify({ "count": len(history), "history": history }) @app.route("/api/analysis") def api_analysis(): return jsonify( get_analysis_snapshot() ) @app.route("/api/prediction") def api_prediction(): prediction = get_prediction() return jsonify( prediction ) @app.route("/api/performance") def api_performance(): return jsonify( get_prediction_performance() ) @app.route("/api/sequence") def api_sequence(): history = crash.get_history(1000) return jsonify( analysis.sequence_analysis( history ) ) @app.route("/api/runs") def api_runs(): history = crash.get_history(1000) return jsonify( analysis.run_analysis( history ) ) @app.route("/api/rolling") def api_rolling(): history = crash.get_history(1000) return jsonify({ "50": analysis.rolling_statistics( history, 50 ), "100": analysis.rolling_statistics( history, 100 ), "250": analysis.rolling_statistics( history, 250 ) }) # ============================================================ # DASHBOARD PAGE # ============================================================ HTML = r""" BC Crash Research System
Research Dashboard
Historical sequence analysis, range estimation and model diagnostics.
System offline Waiting for capture engine.
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Samples
0
Recorded observations
Latest
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Most recent result
Median
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Historical distribution
Coverage
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Evaluated range predictions
Crash History
Most recent recorded observations
0 observations
Next-Round Range
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Target confidence —
Model: —
The displayed interval is a statistical research estimate generated before the next recorded observation. It is not an exact outcome prediction.
Model Diagnostics
Distribution and rolling-window measurements
Mean
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Standard Deviation
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90th Percentile
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Recent Mean
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Tested Predictions
0
Correct Ranges
0
Recent Observations
Recorded multiplier history
# Multiplier Timestamp
BC Crash Research System · Statistical analysis interface · Historical data only