Streaming Indicators

A python library for computing technical analysis indicators on streaming data.

Installation

pip install streaming-indicators

Why another TA library?

There are many other technical analysis python packages, most notably ta-lib, then why another library?
All other libraries work on static data, you can not add values to any indicator. But in real-time trading system, price values (ticks/candles) keeps streaming, and indicators should update on real-time. This library is for that purpose.

Usage

Each indicator is a class, and is statefull. It will have 3 main functions:

1. Constructor: initialise all parameters such as period.
2. update: To add new data point in the indicator computation. Returns the new value of the indicator.
3. compute: Compute indicator value with a new data point, but don't update it's state. This is useful in some cases, for example, compute indictor on ltp, but don't update it.

List of indicators (and usage)

• Simple Moving Average (SMA)

import streaming_indicators as si

period = 14
SMA = si.SMA(period)
for idx, candle in candles.iterrows():
    sma = SMA.update(candle['close'])
    print(sma)

• Exponential Moving Average (EMA)

period = 14
EMA = si.EMA(period)
for idx, candle in candles.iterrows():
    ema = EMA.update(candle['close'])
    print(ema)

• Weighted Moving Average (WMA)
• Smoothed Moving Average (SMMA)
• Volume Weighted Average Price (VWAP) Computes VWAP using hlc3 and volume, anchors at first candle.

VWAP = si.VWAP()
for idx, candle in candles.iterrows():
    vwap = VWAP.update(candle)
    print(vwap)

• Relative Strength Index (RSI)

period = 14
RSI = si.RSI(period)
for idx, candle in candles.iterrows():
    rsi = RSI.update(candle['close'])
    print(rsi)

• Central Pivot Range (CPR)
• True Range (TRANGE)
• Average True Range (ATR)

atr_period = 20
ATR = si.ATR(atr_period)
for idx, candle in candles.iterrows():
    atr = ATR.update(candle)  # Assumes candle to have 'open',high','low','close' - TODO: give multiple inputs to update.
    print(atr)

• Bollinger Bands (BBands)
• SuperTrend (SuperTrend)

st_atr_length = 10
st_factor = 3
ST = si.SuperTrend(st_atr_length, st_factor)
for idx, candle in candles.iterrows():
    st = ST.update(candle)
    print(st) # (st_direction:1/-1, band_value)

To use some historical candles to initiate, use: ST = si.SuperTrend(st_atr_length, st_factor, candles=initial_candles) where initial_candles is pandas dataframe with open,high,low,close columns, and requires talib package.

• Heikin Ashi Candlesticks (HeikinAshi)

HA = si.HeikinAshi()
for idx, candle in candles.iterrows():
    ha_candle = HA.update(candle)
    print(ha_candle) # {'close': float, 'open': float, 'high': float, 'low': float}

• Renko Bricks (Renko)

# For fixed brick size
brick_size = 20
Renko = si.Renko()
for idx, candle in candles.iterrows():
    bricks = Renko.update(candle['close'], brick_size)
    print(bricks) # [{'direction': 1/-1, 'brick_num': int, 'wick_size': float, 'brick_size': float, 'brick_end_price': float, 'price': float}, {}]: list of bricks formed after this candle

# For brick size using ATR
atr_period = 20
ATR = si.ATR(atr_period)
Renko = si.Renko()
for idx, candle in candles.iterrows():
    atr = ATR.update(candle)
    print(atr)
    bricks = Renko.update(candle['close'], atr)
    print(bricks)

• Order Checking (IsOrder)
  Checks if the running sequence is in a given order, eg increasing, decreasing, exponential, etc. Useful when checking if consecutive n candles/ltps were increasing.

period = 10
all_increasing = si.IsOrder('>', period)
for idx, candle in candles.iterrows():
    is_increasing = all_increasing.update(candle['close'])
    print(is_increasing) # True/False

• HalfTrend (HalfTrend)
  HalfTrend indicator by Alex Orekhov (everget) in tradingview. Refered it's pine script. trend = 0 for uptrend and 1 for downtrend.

HT = si.HalfTrend(amplitude=2, channel_deviation=2, atr_period=100)
for idx, candle in candles.iterrows():
    trend, half_trend, up, down, atr_high, atr_low = HT.update(candle)

• CWA 2-Sigma (CWA2Sigma)
  As discussed by Mr Rakesh Pujara in his interview.

CWA2Sigma = si.CWA2Sigma(bb_period=50, bb_width=2, ema_period=100, atr_period=14, atr_factor=1.8, sl_perc=20)
for idx, candle in candles.iterrows():
    cwa_signal,cwa_entry_price = CWA2Sigma.update(candle)

Changelogs and TODOs

• Version History
• TODOs

If you find this repo useful, do consider giving a star. Contributions are most welcome.