Indicators¶

IndicatorManager¶

Manages multiple indicators with automatic multi-timeframe resampling.

from replaybt import IndicatorManager

manager = IndicatorManager({
    "ema_fast": {"type": "ema", "period": 15, "timeframe": "30m", "source": "close"},
    "rsi_7":   {"type": "rsi", "period": 7, "method": "wilder"},
    "atr_14":  {"type": "atr", "period": 14, "timeframe": "1h"},
})

Methods¶

Method	Returns	Description
`update(bar)`	`None`	Feed a 1m bar
`get(name)`	`Any`	Get indicator value
`all()`	`Dict[str, Any]`	All values as dict
`ready()`	`bool`	All indicators ready
`reset()`	`None`	Reset all state

Indicator (ABC)¶

Base class for all indicators.

Constructor¶

Indicator(name: str, period: int = 14)

Methods¶

Method	Returns	Description
`update(bar)`	`None`	Process completed bar
`value()`	`Any`	Current value
`reset()`	`None`	Reset state

Properties¶

Property	Type	Description
`ready`	`bool`	Enough data for valid output

Static Methods¶

Method	Returns	Description
`batch_ema(series, period)`	`Series`	EMA on pandas Series
`batch_rsi_wilder(closes, period)`	`Series`	Wilder's RSI
`batch_rsi_simple(closes, period)`	`Series`	Simple RSI

EMA¶

Exponential Moving Average.

{"type": "ema", "period": 15, "source": "close", "timeframe": "30m"}

Param	Type	Default	Description
`period`	`int`	`14`	EMA window
`source`	`str`	`"close"`	Price field (`close`, `open`, `high`, `low`)
`timeframe`	`str`	`"1m"`	Bar timeframe

Value: Optional[float]

SMA¶

Simple Moving Average.

{"type": "sma", "period": 14, "source": "close", "timeframe": "30m"}

Same parameters as EMA. Value: Optional[float]

RSI¶

Relative Strength Index. Supports Wilder's exponential or simple rolling.

{"type": "rsi", "period": 7, "method": "wilder", "source": "close", "timeframe": "30m"}

Param	Type	Default	Description
`period`	`int`	`14`	RSI window
`method`	`str`	`"wilder"`	`"wilder"` (exponential) or `"simple"` (rolling)
`source`	`str`	`"close"`	Price field
`timeframe`	`str`	`"1m"`	Bar timeframe

Value: Optional[float] (0-100)

ATR¶

Average True Range.

{"type": "atr", "period": 14, "mode": "sma", "timeframe": "1h"}

Param	Type	Default	Description
`period`	`int`	`14`	ATR window
`mode`	`str`	`"sma"`	`"sma"` or `"wilder"`
`timeframe`	`str`	`"1m"`	Bar timeframe

Value: Optional[float]

CHOP¶

Choppiness Index. High values = choppy/ranging, low values = trending.

{"type": "chop", "period": 14, "atr_mode": "sma", "timeframe": "1h"}

Param	Type	Default	Description
`period`	`int`	`14`	Window
`atr_mode`	`str`	`"sma"`	ATR calculation mode
`timeframe`	`str`	`"1m"`	Bar timeframe

Value: Optional[float] (expressed as ATR/Close ratio)

BollingerBands¶

Upper, middle, lower bands + bandwidth + %B.

{"type": "bollinger", "period": 20, "num_std": 2.0, "source": "close"}

Param	Type	Default	Description
`period`	`int`	`20`	SMA window
`num_std`	`float`	`2.0`	Standard deviation multiplier
`source`	`str`	`"close"`	Price field
`timeframe`	`str`	`"1m"`	Bar timeframe

Value: Optional[Dict[str, float]] with keys: upper, middle, lower, bandwidth, pct_b

MACD¶

Moving Average Convergence Divergence.

{"type": "macd", "fast_period": 12, "slow_period": 26, "signal_period": 9, "source": "close"}

Param	Type	Default	Description
`fast_period`	`int`	`12`	Fast EMA period
`slow_period`	`int`	`26`	Slow EMA period
`signal_period`	`int`	`9`	Signal line period
`source`	`str`	`"close"`	Price field
`timeframe`	`str`	`"1m"`	Bar timeframe

Value: Optional[Dict[str, float]] with keys: macd, signal, histogram

Stochastic¶

Stochastic Oscillator (%K and %D).

{"type": "stochastic", "k_period": 14, "d_period": 3, "smooth_k": 3}

Param	Type	Default	Description
`k_period`	`int`	`14`	%K lookback
`d_period`	`int`	`3`	%D smoothing
`smooth_k`	`int`	`3`	%K smoothing (1 = fast stochastic)
`timeframe`	`str`	`"1m"`	Bar timeframe

Value: Optional[Dict[str, float]] with keys: k, d

VWAP¶

Volume-Weighted Average Price. Resets daily at midnight UTC.

{"type": "vwap"}

Value: Optional[float]

OBV¶

On-Balance Volume. Running sum: +volume on up bars, -volume on down bars.

{"type": "obv"}

Value: float

Resampler¶

Batch resampling utilities for DataFrame-based workflows.

Static Methods¶

from replaybt import Resampler

# Resample 1m DataFrame to higher timeframe
df_30m = Resampler.resample(df_1m, "30m")

# Add indicators
df = Resampler.add_ema(df, period=15, col="close", name="ema_15")
df = Resampler.add_rsi_wilder(df, period=14, col="close", name="rsi_14")
df = Resampler.add_rsi_simple(df, period=14, col="close", name="rsi_14_simple")
df = Resampler.add_chop(df, period=14, name="chop_14")

Method	Description
`resample(df, timeframe)`	Resample to `"5m"`, `"15m"`, `"30m"`, `"1h"`, `"2h"`, `"4h"`, `"1d"`
`add_ema(df, period, col, name)`	Add EMA column
`add_rsi_wilder(df, period, col, name)`	Add Wilder's RSI column
`add_rsi_simple(df, period, col, name)`	Add Simple RSI column
`add_chop(df, period, name)`	Add CHOP column