candlestick_patterns

Scan OHLC bars for classical candlestick patterns and emit one row per match.

Examples

from openbb import obb
# Scan all supported patterns on daily SPY.
data = obb.equity.price.historical(symbol='SPY', start_date='2022-01-01', provider='yfinance').results
patterns = obb.technical.candlestick_patterns(data=data)
obb.technical.signals.candlestick_patterns(data=[{'date': '2023-01-02', 'open': 110.0, 'high': 120.0, 'low': 100.0, 'close': 115.0, 'volume': 10000.0}, {'date': '2023-01-03', 'open': 165.0, 'high': 180.0, 'low': 150.0, 'close': 172.5, 'volume': 15000.0}, {'date': '2023-01-04', 'open': 146.67, 'high': 160.0, 'low': 133.33, 'close': 153.33, 'volume': 13333.33}, {'date': '2023-01-05', 'open': 137.5, 'high': 150.0, 'low': 125.0, 'close': 143.75, 'volume': 12500.0}, {'date': '2023-01-06', 'open': 132.0, 'high': 144.0, 'low': 120.0, 'close': 138.0, 'volume': 12000.0}])

Parameters

• standard

data: Data | DataFrame | Series | dict | list | list[DataFrame] | list[Data] | list[Series] | ndarray
OHLC price series.

index: str
Default: date
Index column name in data.

patterns: list[str]
Subset of patterns to scan for. None runs every entry in SUPPORTED_PATTERNS.

---

Returns

results: list[PatternEvent]

Serializable results.

provider: str

Provider name.

warnings: Optional[list[Warning_]]

List of warnings.

chart: Optional[Chart]

Chart object.

extra: dict[str, Any]

Extra info.

---

Data

• standard

date: date | datetime | str
Date of the pattern bar.

pattern: str
Pattern name, lower-snake-case.

direction: str
Bias implied by the pattern: bullish, bearish or neutral.

confidence: float
Heuristic 0-1 score derived from body/shadow ratios. Higher means the bar matches the textbook pattern more cleanly.