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