074787f067
Features: - FastAPI backend with stocks, news, signals, watchlist, analytics endpoints - React frontend with TailwindCSS dark mode trading dashboard - Celery workers for news fetching, sentiment analysis, pattern detection - TimescaleDB schema for time-series stock data - Docker Compose setup for all services - OpenAI integration for sentiment analysis
115 lines
2.8 KiB
Python
115 lines
2.8 KiB
Python
"""
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MarketScanner - Fear-to-Fortune Trading Intelligence
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Main FastAPI Application
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"""
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from contextlib import asynccontextmanager
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from fastapi import FastAPI
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from fastapi.middleware.cors import CORSMiddleware
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from fastapi.responses import JSONResponse
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import structlog
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from app.core.config import settings
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from app.core.database import init_db
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from app.api import router as api_router
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# Configure structured logging
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structlog.configure(
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processors=[
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structlog.stdlib.filter_by_level,
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structlog.processors.TimeStamper(fmt="iso"),
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structlog.processors.JSONRenderer()
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],
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wrapper_class=structlog.stdlib.BoundLogger,
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context_class=dict,
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logger_factory=structlog.stdlib.LoggerFactory(),
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)
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logger = structlog.get_logger()
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@asynccontextmanager
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async def lifespan(app: FastAPI):
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"""Application lifespan events."""
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# Startup
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logger.info("Starting MarketScanner API", version=settings.VERSION)
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await init_db()
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logger.info("Database initialized")
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yield
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# Shutdown
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logger.info("Shutting down MarketScanner API")
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# Create FastAPI application
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app = FastAPI(
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title="MarketScanner API",
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description="""
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🚀 **MarketScanner** - Fear-to-Fortune Trading Intelligence
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A system that identifies buying opportunities by analyzing how stocks
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historically respond to panic-inducing news.
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## Features
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* **News Monitoring** - Real-time scanning of financial news
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* **Sentiment Analysis** - NLP-powered sentiment scoring
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* **Panic Detection** - Identify market fear events
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* **Pattern Matching** - Historical recovery patterns
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* **Buy Signals** - Confidence-scored opportunities
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*"Buy when there's blood in the streets."* — Baron Rothschild
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""",
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version=settings.VERSION,
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docs_url="/docs",
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redoc_url="/redoc",
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lifespan=lifespan,
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)
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# CORS middleware
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app.add_middleware(
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CORSMiddleware,
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allow_origins=settings.CORS_ORIGINS,
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allow_credentials=True,
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allow_methods=["*"],
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allow_headers=["*"],
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)
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# Include API routes
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app.include_router(api_router, prefix="/api/v1")
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@app.get("/", tags=["Root"])
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async def root():
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"""Root endpoint with API info."""
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return {
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"name": "MarketScanner API",
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"version": settings.VERSION,
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"description": "Fear-to-Fortune Trading Intelligence",
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"docs": "/docs",
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"health": "/health",
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}
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@app.get("/health", tags=["Health"])
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async def health_check():
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"""Health check endpoint for Docker/Kubernetes."""
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return JSONResponse(
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status_code=200,
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content={
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"status": "healthy",
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"version": settings.VERSION,
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}
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)
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if __name__ == "__main__":
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import uvicorn
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uvicorn.run(
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"app.main:app",
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host=settings.BACKEND_HOST,
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port=settings.BACKEND_PORT,
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reload=settings.DEBUG,
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)
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