Python

pip install wickra

No system dependencies. No C toolchain. The Rust core ships as a pre-built wheel for every Python 3.9–3.13 on Linux, macOS, and Windows (x86_64 and aarch64 where the registry has the platform).

• Latest: wickra 0.4.5
• Supported Python: 3.9 / 3.11 / 3.12 / 3.13 (3.10 omitted upstream)

Batch — TA-Lib-style on a NumPy array

import numpy as np
import wickra as ta

prices = np.linspace(100, 200, 1000)
rsi = ta.RSI(14)
values = rsi.batch(prices)              # numpy array, NaN during warmup

Streaming — tick-by-tick

import wickra as ta

rsi = ta.RSI(14)
for price in live_feed:
    v = rsi.update(price)               # O(1)
    if v is not None and v > 70:
        print("overbought", v)

Multi-output indicators (MACD, Bollinger …)

import wickra as ta

macd = ta.MACD(12, 26, 9)
for price in live_feed:
    out = macd.update(price)            # dict or None
    if out is not None:
        print(out["macd"], out["signal"], out["histogram"])

bb = ta.BollingerBands(20, 2.0)
out = bb.update(price)                  # {"upper", "middle", "lower", "stddev"}

Candle-input indicators

ATR, Stochastic, and the volume-aware family take a Candle-shaped dict or tuple:

import wickra as ta

atr = ta.ATR(14)
for c in candles:
    v = atr.update({"high": c.h, "low": c.l, "close": c.c})
    if v is not None:
        ...

The dict form is the explicit one; tuples ((o, h, l, c, v, t)) work too and are documented per indicator on the Indicator pages (docs).

Live trading example

The repo ships a runnable example at examples/python/live_trading.py that pairs wickra with the standard websockets library to stream a Binance Spot kline feed.

More

• Quickstart-Python (docs)
• Warmup-Periods — how many bars before each indicator emits a non-None value
• Benchmarks