c762564d40
- Fix 71 invalid-syntax files (class-body newline-broken assignments) - Add from/None chain to 307 B904 raise-without-from sites - Add B008 ignore to ruff.toml (already in pyproject.toml) - Noqa F401 on __init__.py re-exports (137 sites) - Noqa E402 on deferred imports (63 sites) - Bulk-add stdlib/FastAPI/project imports for F821 (127 sites) - Replace ×→x, –→-, …→... in docstrings (4093 chars) - Manual refactor of 5 SIM103/SIM116 patterns Tests: 791 passed (66 deselected due to pre-existing Redis issues in test_rag.py) Co-authored-by: opencode <opencode@rugmunch.io>
129 lines
3.7 KiB
Python
129 lines
3.7 KiB
Python
"""Sentiment pipeline - X/Twitter + Reddit crypto mentions → NLP scoring."""
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import os
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import re
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from datetime import UTC, datetime
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import httpx
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from fastapi import APIRouter
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router = APIRouter(prefix="/api/v1/sentiment", tags=["sentiment"])
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SEARXNG = os.getenv("SEARXNG_URL", "http://localhost:8088")
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POSITIVE_WORDS = {
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"bullish",
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"moon",
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"pump",
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"gem",
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"buy",
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"long",
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"green",
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"ATH",
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"breakout",
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"accumulation",
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"undervalued",
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"partnership",
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"listed",
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"launch",
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"mainnet",
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}
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NEGATIVE_WORDS = {
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"bearish",
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"dump",
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"rug",
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"scam",
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"sell",
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"short",
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"red",
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"crash",
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"hack",
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"exploit",
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"FUD",
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"dead",
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"delist",
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"bankrupt",
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"SEC",
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}
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def _score_text(text: str) -> dict:
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words = set(re.findall(r"\b\w+\b", text.lower()))
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pos = len(words & POSITIVE_WORDS)
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neg = len(words & NEGATIVE_WORDS)
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total = pos + neg
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if total == 0:
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return {"sentiment": "neutral", "score": 0.5, "positive": 0, "negative": 0, "total_mentions": 0}
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score = pos / total
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sentiment = "bullish" if score > 0.6 else "bearish" if score < 0.4 else "neutral"
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return {"sentiment": sentiment, "score": round(score, 2), "positive": pos, "negative": neg, "total_mentions": total}
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async def _search_mentions(symbol: str, source: str = "twitter") -> list[str]:
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"""Search for crypto mentions via SearXNG."""
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texts = []
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try:
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async with httpx.AsyncClient(timeout=10) as c:
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r = await c.get(
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f"{SEARXNG}/search",
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params={"q": f"${symbol} crypto {source}", "format": "json", "categories": "social media"},
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)
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if r.status_code == 200:
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results = r.json().get("results", [])
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texts = [item.get("content", "") or item.get("title", "") for item in results[:20]]
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except Exception:
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pass
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return texts
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@router.get("/token/{symbol}")
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async def token_sentiment(symbol: str):
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"""Get sentiment for a token across social media."""
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texts = await _search_mentions(symbol)
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if not texts:
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return {"symbol": symbol, "sentiment": "unknown", "note": "No mentions found"}
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all_text = " ".join(texts)
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sentiment = _score_text(all_text)
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sentiment["symbol"] = symbol
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sentiment["timestamp"] = datetime.now(UTC).isoformat()
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sentiment["sources_scanned"] = len(texts)
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# Emoji representation
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emoji = "🟢" if sentiment["sentiment"] == "bullish" else "🔴" if sentiment["sentiment"] == "bearish" else "⚪"
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sentiment["emoji"] = emoji
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return sentiment
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@router.get("/market")
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async def market_sentiment():
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"""Overall crypto market sentiment."""
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tickers = ["BTC", "ETH", "SOL"]
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results = {}
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for ticker in tickers:
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texts = await _search_mentions(ticker)
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results[ticker] = _score_text(" ".join(texts)) if texts else {"sentiment": "unknown"}
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scores = [r["score"] for r in results.values() if r.get("score")]
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avg_score = sum(scores) / len(scores) if scores else 0.5
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overall = "bullish" if avg_score > 0.55 else "bearish" if avg_score < 0.45 else "neutral"
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return {
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"overall": overall,
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"average_score": round(avg_score, 2),
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"breakdown": results,
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"emoji": "🟢" if overall == "bullish" else "🔴" if overall == "bearish" else "⚪",
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}
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@router.get("/trending-signals/{symbol}")
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async def sentiment_signal(symbol: str):
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"""Quick sentiment signal for trading: BULLISH / BEARISH / NEUTRAL."""
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result = await token_sentiment(symbol)
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return {
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"symbol": symbol,
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"signal": result["sentiment"].upper(),
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"emoji": result.get("emoji", "⚪"),
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"score": result.get("score", 0.5),
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}
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