investfly.models.strategy.StrategyDataService

Strategy data service interface.

This module defines the StrategyDataService abstract base class that provides the interface for accessing market data, indicators, and financial information from within trading strategies.

class StrategyDataService(abc.ABC):

Interface for accessing market data and indicators from strategies.

StrategyDataService is an abstract base class that defines the interface for accessing various types of market data and computing technical indicators from within trading strategies.

This service provides access to:

Technical indicators (SMA, RSI, MACD, etc.)
Market data (quotes, bars, financials)
News and fundamental data

The service is implemented by the execution engine and injected into strategy instances via TradingStrategy.setDataService().

Attributes: ALL_BARS: Constant value (-1) used with getBars() to retrieve all available historical bars for a security.

Example: Strategies access the data service via self.dataService:

```python

Compute indicators

sma = self.dataService.computeIndicatorSeries( "SMA", security, {"period": 20, "barInterval": BarInterval.ONE_DAY} )

Get current quote

quote = self.dataService.getQuote(security) if quote: current_price = quote.lastPrice

Get historical bars

bars = self.dataService.getBars( security, BarInterval.ONE_DAY, numBars=50 ) ```

ALL_BARS: int = -1

Constant for retrieving all available bars in getBars().

@abstractmethod

def computeIndicatorSeries( self, indicatorId: str, security: investfly.models.marketdata.Security, params: Dict[str, Any]) -> investfly.models.indicator.IndicatorSeries:

Compute a technical indicator series for a given security.

This method computes a technical indicator (e.g., SMA, RSI, MACD) and returns a series of indicator values over time. The series can be used for analysis, signal generation, and crossover detection.

The indicatorId parameter is declared as a string (not an enum) to support both standard indicators provided by Investfly and custom indicators defined by users. For standard indicators, the string value must match one of the values from the StandardIndicatorId enum.

Args: indicatorId: The identifier of the indicator to compute. Must be a string value. For standard indicators supported by Investfly, use one of the values from StandardIndicatorId enum:

    **Moving Averages:**
    - "SMA": Simple Moving Average
    - "EMA": Exponential Moving Average

    **Momentum Indicators:**
    - "RSI": Relative Strength Index
    - "ROC": Rate of Change
    - "CMO": Chande Momentum Oscillator
    - "CMO_SMOOTHED": Smoothed CMO
    - "PPO": Percentage Price Oscillator
    - "ULTIMATE_OSC": Ultimate Oscillator

    **Trend Indicators:**
    - "MACD": Moving Average Convergence Divergence
    - "MACDS": MACD Signal Line
    - "ADX": Average Directional Index
    - "PLUS_DI": Plus Directional Indicator
    - "MINUS_DI": Minus Directional Indicator
    - "PSAR": Parabolic SAR

    **Volatility Indicators:**
    - "ATR": Average True Range
    - "STD_DEV": Standard Deviation
    - "UPPER_BBAND": Upper Bollinger Band
    - "LOWER_BBAND": Lower Bollinger Band
    - "BBAND": Bollinger Bands (composite, for charts only)

    **Oscillators:**
    - "CCI": Commodity Channel Index
    - "WILLIAM_R": Williams' %R
    - "FAST_STOCHASTIC_OSC": Fast Stochastic Oscillator
    - "SLOW_STOCHASTIC_OSC": Slow Stochastic Oscillator
    - "STOCHASTICS": Stochastic (composite, for charts only)

    **Price Indicators:**
    - "MEDIAN_PRICE": Median Price
    - "TYPICAL_PRICE": Typical Price
    - "MAX": Maximum value over period
    - "MIN": Minimum value over period

    **Candlestick Patterns:**
    - "DOJI": Doji pattern
    - "HAMMER": Hammer pattern
    - "INVERTED_HAMMER": Inverted Hammer pattern
    - "DRAGONFLY_DOJI": Dragonfly Doji pattern
    - "GRAVESTONE_DOJI": Gravestone Doji pattern
    - "HANGING_MAN": Hanging Man pattern
    - "BULLISH": Bullish pattern
    - "BEARISH": Bearish pattern

    **Support/Resistance:**
    - "SUPPORT": Support level
    - "RESISTANCE": Resistance level

    **Other:**
    - "AVGVOLUME": Average Volume
    - "HIGH52WEEK": 52-Week High
    - "LOW52WEEK": 52-Week Low
    - "DRAWDOWN": Drawdown
    - "PRICECHANGEPCT": Price Change Percentage

    For custom indicators, use the custom indicator ID string as
    defined when the indicator was created.

security: The security for which to compute the indicator.
params: Dictionary of parameters for the indicator computation.
    Common parameters include:
    - "period" (int): Period for the indicator (e.g., 20 for SMA(20)).
    - "barInterval" (BarInterval): Bar interval for the data source.
    - Indicator-specific parameters (e.g., "fast_period", "slow_period"
      for MACD).

Returns: IndicatorSeries object containing the computed indicator values. The series provides methods for: - Accessing the latest value: series.last.value - Converting to list: series.toList() - Crossover detection: series.cross_over(other), series.cross_under(other)

Note: - The indicatorId parameter is a string type (not StandardIndicatorId enum) to support both standard and custom indicators. - When using standard indicators, the string value must exactly match one of the StandardIndicatorId enum values (see investfly.models.indicator.IndicatorEnums.StandardIndicatorId). - Custom indicators can be referenced by their custom ID string.

Example: ```python

Compute 20-period SMA on daily bars (standard indicator)

sma20 = self.dataService.computeIndicatorSeries( "SMA", # Must match StandardIndicatorId.SMA.value security, {"period": 20, "barInterval": BarInterval.ONE_DAY} )

Compute 14-period RSI (standard indicator)

rsi = self.dataService.computeIndicatorSeries( "RSI", # Must match StandardIndicatorId.RSI.value security, {"period": 14, "barInterval": BarInterval.ONE_DAY} )

Compute custom indicator

custom_indicator = self.dataService.computeIndicatorSeries( "MY_CUSTOM_INDICATOR", # Custom indicator ID security, {"param1": 10, "barInterval": BarInterval.ONE_DAY} )

Check for crossover

if sma20.cross_over(rsi): # SMA crossed above RSI - bullish signal pass

Access latest value

current_rsi = rsi.last.value ```

@abstractmethod

def getFinancials( self, symbol: str) -> Dict[investfly.models.marketdata.FinancialField, float]:

Retrieve fundamental financial metrics for the given symbol.

This method returns fundamental financial data such as market cap, P/E ratio, revenue, earnings, etc. for a security.

Args: symbol: The stock symbol (e.g., "AAPL", "MSFT") for which to retrieve financial data.

Returns: Dictionary mapping FinancialField enums to their corresponding float values. Returns an empty dictionary if data is unavailable.

Example: python financials = self.dataService.getFinancials("AAPL") market_cap = financials.get(FinancialField.MARKET_CAP) pe_ratio = financials.get(FinancialField.PE_RATIO)

@abstractmethod

def getQuote( self, security: investfly.models.marketdata.Security) -> investfly.models.marketdata.Quote | None:

Retrieve the latest quote for the given security.

This method returns the most recent quote data including bid/ask prices, last trade price, volume, and other market data fields.

Args: security: The Security object for which to retrieve the quote.

Returns: Quote object containing the latest market data, or None if the quote is unavailable. The Quote object provides fields such as: - lastPrice: Last trade price - bidPrice, askPrice: Current bid and ask prices - volume: Trading volume - And other quote fields (see QuoteField enum).

Example: python quote = self.dataService.getQuote(security) if quote: current_price = quote.lastPrice volume = quote.volume

@abstractmethod

def getNews( self, security: investfly.models.marketdata.Security) -> List[investfly.models.marketdata.StockNews]:

Retrieve latest news articles for the given security.

This method returns recent news articles related to the specified security. News data can be used for sentiment analysis or event-driven trading strategies.

Args: security: The Security object for which to retrieve news.

Returns: List of StockNews objects containing news articles. Returns an empty list if no news is available. Each StockNews object contains: - title: News article title - content: Article content or summary - publishedDate: Publication date - source: News source - url: Article URL

Example: python news = self.dataService.getNews(security) for article in news: print(f"{article.title} - {article.publishedDate}")

@abstractmethod

def getBars( self, security: investfly.models.marketdata.Security, barInterval: investfly.models.marketdata.BarInterval, numBars: int) -> List[investfly.models.marketdata.Bar]:

Retrieve historical bars (candlestick/OHLC data) for a security.

This method returns historical price bars at the specified interval. Bars contain open, high, low, close (OHLC) prices and volume data.

Args: security: The Security object for which to fetch bars. barInterval: The interval of bars to retrieve. Options include: - BarInterval.ONE_MINUTE - BarInterval.FIVE_MINUTE - BarInterval.FIFTEEN_MINUTE - BarInterval.THIRTY_MINUTE - BarInterval.SIXTY_MINUTE - BarInterval.ONE_DAY numBars: Number of bars to return. Use StrategyDataService.ALL_BARS to retrieve all available bars. Bars are returned in chronological order (oldest first).

Returns: List of Bar objects containing OHLC data. Each Bar object contains: - open: Opening price - high: Highest price - low: Lowest price - close: Closing price - volume: Trading volume - timestamp: Bar timestamp

Example: ```python

Get last 50 daily bars

bars = self.dataService.getBars( security, BarInterval.ONE_DAY, numBars=50 )

Get all available 1-minute bars

all_bars = self.dataService.getBars( security, BarInterval.ONE_MINUTE, StrategyDataService.ALL_BARS )

Access bar data

latest_bar = bars[-1] close_price = latest_bar.close ```