TradingAgents/tradingagents/domains/marketdata/fundamental_data_service.py

83 lines
2.5 KiB
Python

"""
Fundamental Data Service for aggregating and analyzing financial statement data.
"""
import logging
logger = logging.getLogger(__name__)
class FundamentalDataService:
"""Service for fundamental financial data aggregation and analysis."""
def __init__(
self,
simfin_client: SimFinClient,
repository: FundamentalDataRepository,
):
"""Initialize Fundamental Data Service.
Args:
simfin_client: Client for SimFin/financial API access
repository: Repository for cached fundamental data
online_mode: Whether to fetch live data
data_dir: Directory for data storage
"""
self.simfin_client = simfin_client
self.repository = repository
def update_fundamental_data(
self,
symbol: str,
start_date: str,
end_date: str,
frequency: str = "quarterly",
) -> FundamentalContext:
pass # TODO: fetch fundementals from simfin, save in repo
def get_fundamental_context(
self,
symbol: str,
start_date: str,
end_date: str,
frequency: str = "quarterly",
) -> FundamentalContext:
"""Get fundamental analysis context for a company.
Args:
symbol: Stock ticker symbol
start_date: Start date in YYYY-MM-DD format
end_date: End date in YYYY-MM-DD format
frequency: Reporting frequency ('quarterly' or 'annual')
force_refresh: If True, skip local data and fetch fresh from APIs
Returns:
FundamentalContext with financial statements and key ratios
"""
balance_sheet = None
income_statement = None
cash_flow = None
error_info = {}
errors = []
data_source = "unknown"
# return FundamentalContext(
# symbol=symbol,
# period={"start": start_date, "end": end_date},
# balance_sheet=balance_sheet,
# income_statement=income_statement,
# cash_flow=cash_flow,
# key_ratios=key_ratios,
# metadata={
# "data_quality": data_quality,
# "service": "fundamental_data",
# "online_mode": self.is_online(),
# "frequency": frequency,
# "data_source": data_source,
# "force_refresh": force_refresh,
# **error_info,
# },
# )
pass # TODO: read data from repo