streaming-indicators 0.0.8

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

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)
• Relative Strength Index (RSI)

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

• 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)

• 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.

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

TODO

• Not all indicators currently support compute method.
• Add documentation.
• SuperTrend,HeikinAshi,ATR depends on key names, eg ('open','close'). Should be independent, i.e. given in input. (similar to pandas_ta)
• Add initalisation to all indicators similar to SuperTrend.
• Implement more indicators. MIT License

Copyright (c) [2023] [Rishabh Gupta]

Permission is hereby granted, free of charge, to any person obtaining a copy of this software and associated documentation files (the "Software"), to deal in the Software without restriction, including without limitation the rights to use, copy, modify, merge, publish, distribute, sublicense, and/or sell copies of the Software, and to permit persons to whom the Software is furnished to do so, subject to the following conditions:

The above copyright notice and this permission notice shall be included in all copies or substantial portions of the Software.

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