Streaming API

The ferro_ta.streaming module provides stateful, bar-by-bar indicator computation for live/real-time trading. Each class maintains an internal buffer and returns NaN during the warmup period.

Streaming / Incremental Indicators — bar-by-bar stateful classes.

All streaming classes are implemented in Rust (PyO3) for maximum performance. The Python module re-exports the Rust classes from the _ferro_ta extension. The extension must be built; there is no Python fallback.

Usage

>>> from ferro_ta.data.streaming import StreamingSMA, StreamingEMA, StreamingRSI
>>> import numpy as np
>>> sma = StreamingSMA(period=3)
>>> for close in [10.0, 11.0, 12.0, 13.0, 14.0]:
...     val = sma.update(close)
...     print(f"{close} → {val:.4f}" if not np.isnan(val) else f"{close} → NaN")
10.0 → NaN
11.0 → NaN
12.0 → 11.0000
13.0 → 12.0000
14.0 → 13.0000

Available classes

StreamingSMA — Simple Moving Average StreamingEMA — Exponential Moving Average StreamingRSI — Relative Strength Index (Wilder seeding) StreamingATR — Average True Range (Wilder seeding) StreamingBBands — Bollinger Bands (upper, middle, lower) StreamingMACD — MACD line, signal, histogram StreamingStoch — Slow Stochastic (slowk, slowd) StreamingVWAP — Volume Weighted Average Price (cumulative) StreamingSupertrend — ATR-based Supertrend

Rust backend

All classes are PyO3 classes compiled into the _ferro_ta extension module. Import them directly from the extension for zero-overhead access:

from ferro_ta._ferro_ta import StreamingSMA

class ferro_ta.streaming.StreamingATR(period=14)

Bases: object

Average True Range with TA-Lib–compatible Wilder seeding.

period

reset()

update(high, low, close): Add a new bar (high, low, close) and return ATR (NaN during warmup).

class ferro_ta.streaming.StreamingBBands(period=20, nbdevup=2.0, nbdevdn=2.0)

Bases: object

Bollinger Bands — streaming variant using Welford’s online algorithm.

period

reset()

update(value): Add a new bar; return (upper, middle, lower). NaN tuple during warmup.

class ferro_ta.streaming.StreamingEMA(period)

Bases: object

Exponential Moving Average with SMA seeding.

period

reset()

update(value): Add a new bar and return the current EMA (NaN during warmup).

class ferro_ta.streaming.StreamingMACD(fastperiod=12, slowperiod=26, signalperiod=9)

Bases: object

MACD — fast EMA, slow EMA, signal EMA.

reset()

update(value): Add a new close; return (macd_line, signal_line, histogram).

class ferro_ta.streaming.StreamingRSI(period=14)

Bases: object

Relative Strength Index with TA-Lib–compatible Wilder seeding.

period

reset()

update(value): Add a new close and return RSI in [0, 100] (NaN during warmup).

class ferro_ta.streaming.StreamingSMA(period)

Bases: object

Simple Moving Average — O(1) per update via running sum.

Returns NaN during the first period - 1 bars.

period

reset(): Reset state to initial condition.

update(value): Add a new bar and return the current SMA (NaN during warmup).

class ferro_ta.streaming.StreamingStoch(fastk_period=5, slowk_period=3, slowd_period=3)

Bases: object

Slow Stochastic (SMA-smoothed).

reset()

update(high, low, close): Add a new bar (high, low, close); return (slowk, slowd).

class ferro_ta.streaming.StreamingSupertrend(period=7, multiplier=3.0)

Bases: object

ATR-based Supertrend — streaming variant.

period

reset()

update(high, low, close): Add a new bar (high, low, close); return (supertrend_line, direction).

class ferro_ta.streaming.StreamingVWAP

Bases: object

Cumulative Volume Weighted Average Price.

reset(): Reset for a new session.

update(high, low, close, volume): Add a new bar (high, low, close, volume) and return cumulative VWAP.