Quick Start

Start here. This page covers one indicator, a stream of candles, and reading the latest value. You do not need Hexital, timeframes, or custom indicators yet.

For the next steps, see Choose your path on the home page.

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Your first indicator

Hexital is built for incremental updates: append a candle, get the new reading — without recalculating the full history.

from hexital import EMA, Candle

candles = Candle.from_dicts([
    {"open": 17213, "high": 2395, "low": 7813, "close": 3615, "volume": 19661},
    {"open": 1301, "high": 3007, "low": 11626, "close": 19048, "volume": 28909},
    {"open": 12615, "high": 923, "low": 7318, "close": 1351, "volume": 33765},
])

ema = EMA(candles=candles, period=3)
ema.calculate()

print(ema.reading())  # latest EMA value

Append a new candle

Call append() when new market data arrives. The indicator recalculates automatically — you do not need to call calculate() again.

ema.append(
    Candle.from_dict(
        {"open": 19723, "high": 4837, "low": 11631, "close": 6231, "volume": 38993}
    )
)
print(ema.reading())

Indicator names

If you omit name, Hexital generates one from the indicator type and settings — e.g. EMA_3 for EMA(period=3). Use that name with reading(), series(), and analysis helpers. For nested dict outputs, use : — e.g. MACD_12_26_9:signal.

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Live trading

Hexital does not fetch candles — your exchange, websocket, or database layer delivers OHLCV. Hexital tells you how much history you need, accepts append() / prepend(), and keeps indicators incremental from there.

Typical bootstrap:

from hexital import EMA, RSI, Candle, Hexital

strategy = Hexital("live", [], [EMA(period=10), RSI(period=14)])

# 1. Your feed decides what to request (Hexital only advises bar counts)
prefetch = strategy.minimum_candles_by_timeframe()
# e.g. {"DEFAULT": 15}  → fetch 15 bars on your default stream

history = fetch_from_your_exchange(count=prefetch["DEFAULT"])  # not Hexital

# 2. Load history, then check readiness on Hexital's side
for candle in history:
    strategy.append(candle)

if strategy.has_sufficient_candles():
    strategy.calculate()

# 3. Live loop — append recalculates automatically
while True:
    strategy.append(await next_candle_from_feed())
    if strategy.exists("RSI_14"):  # valid latest reading
        ...

Step	Your code	Hexital
How many bars to fetch?	Read minimum_candles_by_timeframe()	Per-series bar counts
Enough loaded yet?	has_sufficient_candles()	Compares bar count to each indicator's minimum_candles
First full calc	calculate() once after history	Fills missing readings
Each new tick	append(candle)	Incremental update

Multi-timeframe strategies: fetch each series separately using the matching key from minimum_candles_by_timeframe() (e.g. "DEFAULT" vs "T10"). See History and readiness.

Persisting candles with indicator readings: Serialisation and Readings on candles.

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Candles

Every indicator works on Candle objects. The minimum fields are open, high, low, close, and volume.

The quickest path for bulk data is usually a list of dicts:

candles = Candle.from_dicts([
    {"open": 1.0, "high": 1.2, "low": 0.9, "close": 1.1, "volume": 1000},
])

You can also pass dicts or lists directly to append() — Hexital converts them for you.

For every input format (lists, timestamps, Pandas, and more), see the Candles guide.

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What next?

Goal	Guide
Live feed bootstrap (history + append)	Live trading above
Run several indicators on one candle stream	Hexital strategies
Typed indicator access (HexitalCol)	Hexital strategies
Save and restore strategy config	Hexital strategies
Trim memory, timestamps, timeframes	Candles
Export candles with readings	Candles
Crossovers, rising/falling checks	Analysis
Write your own indicator	Custom indicators