TradingAgents/tradingagents/dataflows/discovery/scanners/volume_accumulation.py

111 lines
4.0 KiB
Python

"""Volume accumulation and compression scanner."""
from typing import Any, Dict, List
from tradingagents.dataflows.discovery.scanner_registry import SCANNER_REGISTRY, BaseScanner
from tradingagents.dataflows.discovery.utils import Priority
from tradingagents.tools.executor import execute_tool
from tradingagents.utils.logger import get_logger
logger = get_logger(__name__)
class VolumeAccumulationScanner(BaseScanner):
"""Scan for unusual volume accumulation patterns."""
name = "volume_accumulation"
pipeline = "momentum"
def __init__(self, config: Dict[str, Any]):
super().__init__(config)
self.unusual_volume_multiple = self.scanner_config.get("unusual_volume_multiple", 2.0)
self.volume_cache_key = self.scanner_config.get("volume_cache_key", "default")
def scan(self, state: Dict[str, Any]) -> List[Dict[str, Any]]:
if not self.is_enabled():
return []
logger.info("📊 Scanning volume accumulation...")
try:
# Use volume scanner tool
result = execute_tool(
"get_unusual_volume",
min_volume_multiple=self.unusual_volume_multiple,
top_n=self.limit,
)
if not result:
logger.info("Found 0 volume accumulation candidates")
return []
candidates = []
# Handle different result formats
if isinstance(result, str):
# Parse markdown/text result
candidates = self._parse_text_result(result)
elif isinstance(result, list):
# Structured result
for item in result[: self.limit]:
ticker = item.get("ticker", "").upper()
if not ticker:
continue
volume_ratio = item.get("volume_ratio", 0)
avg_volume = item.get("avg_volume", 0)
candidates.append(
{
"ticker": ticker,
"source": self.name,
"context": f"Unusual volume: {volume_ratio:.1f}x average ({avg_volume:,})",
"priority": (
Priority.MEDIUM.value if volume_ratio < 3.0 else Priority.HIGH.value
),
"strategy": "volume_accumulation",
}
)
elif isinstance(result, dict):
# Dict with tickers list
for ticker in result.get("tickers", [])[: self.limit]:
candidates.append(
{
"ticker": ticker.upper(),
"source": self.name,
"context": "Unusual volume accumulation",
"priority": Priority.MEDIUM.value,
"strategy": "volume_accumulation",
}
)
logger.info(f"Found {len(candidates)} volume accumulation candidates")
return candidates
except Exception as e:
logger.warning(f"⚠️ Volume accumulation failed: {e}")
return []
def _parse_text_result(self, text: str) -> List[Dict[str, Any]]:
"""Parse tickers from text result."""
from tradingagents.dataflows.discovery.common_utils import extract_tickers_from_text
candidates = []
tickers = extract_tickers_from_text(text)
for ticker in tickers[: self.limit]:
candidates.append(
{
"ticker": ticker,
"source": self.name,
"context": "Unusual volume detected",
"priority": Priority.MEDIUM.value,
"strategy": "volume_accumulation",
}
)
return candidates
SCANNER_REGISTRY.register(VolumeAccumulationScanner)