152 lines
5.0 KiB
Python
152 lines
5.0 KiB
Python
"""Reddit DD (Due Diligence) scanner."""
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from typing import Any, Dict, List
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from tradingagents.dataflows.discovery.scanner_registry import BaseScanner, SCANNER_REGISTRY
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from tradingagents.dataflows.discovery.utils import Priority
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from tradingagents.tools.executor import execute_tool
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class RedditDDScanner(BaseScanner):
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"""Scan Reddit for high-quality DD posts."""
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name = "reddit_dd"
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pipeline = "social"
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def __init__(self, config: Dict[str, Any]):
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super().__init__(config)
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def scan(self, state: Dict[str, Any]) -> List[Dict[str, Any]]:
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if not self.is_enabled():
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return []
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print(f" 📝 Scanning Reddit DD posts...")
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try:
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# Use Reddit DD scanner tool
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result = execute_tool(
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"scan_reddit_dd",
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limit=self.limit
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)
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if not result:
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print(f" Found 0 DD posts")
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return []
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candidates = []
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# Handle different result formats
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if isinstance(result, list):
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# Structured result with DD posts
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for post in result[:self.limit]:
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ticker = post.get("ticker", "").upper()
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if not ticker:
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continue
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title = post.get("title", "")
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score = post.get("score", 0)
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# Higher score = higher priority
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priority = Priority.HIGH.value if score > 1000 else Priority.MEDIUM.value
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candidates.append({
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"ticker": ticker,
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"source": self.name,
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"context": f"Reddit DD: {title[:80]}... (score: {score})",
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"priority": priority,
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"strategy": "undiscovered_dd",
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"dd_score": score,
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})
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elif isinstance(result, dict):
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# Dict format
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for ticker_data in result.get("posts", [])[:self.limit]:
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ticker = ticker_data.get("ticker", "").upper()
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if not ticker:
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continue
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candidates.append({
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"ticker": ticker,
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"source": self.name,
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"context": f"Reddit DD post",
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"priority": Priority.MEDIUM.value,
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"strategy": "undiscovered_dd",
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})
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elif isinstance(result, str):
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# Text result - extract tickers
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candidates = self._parse_text_result(result)
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print(f" Found {len(candidates)} DD posts")
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return candidates
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except Exception as e:
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print(f" ⚠️ Reddit DD scan failed, using fallback: {e}")
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return self._fallback_dd_scan()
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def _fallback_dd_scan(self) -> List[Dict[str, Any]]:
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"""Fallback using general Reddit API."""
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try:
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# Try to get Reddit posts with DD flair
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from tradingagents.dataflows.reddit_api import get_reddit_client
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reddit = get_reddit_client()
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subreddit = reddit.subreddit("wallstreetbets+stocks")
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candidates = []
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seen_tickers = set()
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# Look for DD posts
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for submission in subreddit.search("flair:DD", limit=self.limit * 2):
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# Extract ticker from title
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import re
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ticker_pattern = r'\$([A-Z]{2,5})\b|^([A-Z]{2,5})\s'
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matches = re.findall(ticker_pattern, submission.title)
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if not matches:
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continue
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ticker = (matches[0][0] or matches[0][1]).upper()
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if ticker in seen_tickers:
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continue
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seen_tickers.add(ticker)
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candidates.append({
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"ticker": ticker,
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"source": self.name,
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"context": f"Reddit DD: {submission.title[:80]}...",
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"priority": Priority.MEDIUM.value,
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"strategy": "undiscovered_dd",
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})
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if len(candidates) >= self.limit:
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break
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return candidates
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except:
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return []
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def _parse_text_result(self, text: str) -> List[Dict[str, Any]]:
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"""Parse tickers from text result."""
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import re
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candidates = []
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ticker_pattern = r'\$([A-Z]{2,5})\b|^([A-Z]{2,5})\s'
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matches = re.findall(ticker_pattern, text)
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tickers = list(set([t[0] or t[1] for t in matches if t[0] or t[1]]))
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for ticker in tickers[:self.limit]:
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candidates.append({
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"ticker": ticker,
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"source": self.name,
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"context": "Reddit DD post",
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"priority": Priority.MEDIUM.value,
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"strategy": "undiscovered_dd",
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})
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return candidates
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SCANNER_REGISTRY.register(RedditDDScanner)
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