Order Blocks

Warmup Window

Minimum bars needed: 2 × swing_length + 1 bars (default params: 21 bars (swing_length=10))

Swing pivots need swing_length bars on each side to be confirmed. After the first pivot is confirmed, new order blocks can appear in real-time.

✅ After the warmup window is filled, this indicator produces a new value on every incoming bar in real-time.

Real-time Indicator

Order blocks appear after pivot confirmation, not after smoothing delay.

Event	Lag	Detail
Order block zone appears	≈ swing_length bars after the pivot	Swing pivots need swing_length bars on each side to be confirmed
Signal fires when price returns to zone	0 bars	Once the zone exists, the signal fires instantly when price enters it

Order Blocks are zones where institutional traders (banks, hedge funds) placed large orders, causing significant price moves. They represent areas of supply and demand imbalance that often act as support/resistance when price returns.

Bullish Order Block: The last bearish candle before a strong upward move. When price returns to this zone, it often bounces up (support).

Bearish Order Block: The last bullish candle before a strong downward move. When price returns to this zone, it often reverses down (resistance).

Breaker Blocks: When an Order Block is broken (invalidated), it becomes a breaker block and may act as the opposite type of support/resistance.

def order_blocks(
    data: Union[PdDataFrame, PlDataFrame],
    swing_length: int = 10,
    use_body: bool = False,
    high_column: str = 'High',
    low_column: str = 'Low',
    open_column: str = 'Open',
    close_column: str = 'Close',
    bullish_ob_column: str = 'bullish_ob',
    bearish_ob_column: str = 'bearish_ob',
    bullish_ob_top_column: str = 'bullish_ob_top',
    bullish_ob_bottom_column: str = 'bullish_ob_bottom',
    bearish_ob_top_column: str = 'bearish_ob_top',
    bearish_ob_bottom_column: str = 'bearish_ob_bottom',
    bullish_breaker_column: str = 'bullish_breaker',
    bearish_breaker_column: str = 'bearish_breaker'
) -> Union[PdDataFrame, PlDataFrame]:

Example

import pandas as pd
from pyindicators import order_blocks, ob_signal, get_active_order_blocks

# Create sample OHLC data
df = pd.DataFrame({
    'Open': [100, 102, 101, 105, 110, 108, 112, 115, 113, 118],
    'High': [103, 104, 106, 112, 115, 112, 118, 120, 117, 122],
    'Low': [99, 100, 100, 104, 108, 106, 110, 113, 111, 116],
    'Close': [102, 101, 105, 110, 108, 110, 115, 113, 116, 120]
})

# Detect Order Blocks
df = order_blocks(df, swing_length=5)
print(df[['bullish_ob', 'bearish_ob', 'bullish_ob_top', 'bullish_ob_bottom']])

# Generate signals when price enters an OB zone
df = ob_signal(df)
print(df['ob_signal'])  # 1 = in bullish zone, -1 = in bearish zone, 0 = outside

# Get currently active Order Blocks
active = get_active_order_blocks(df, max_bullish=3, max_bearish=3)
print(f"Active bullish OBs: {len(active['bullish'])}")
print(f"Active bearish OBs: {len(active['bearish'])}")

The function returns columns for:

• bullish_ob / bearish_ob: 1 when Order Block is detected, 0 otherwise
• bullish_ob_top / bullish_ob_bottom: Zone boundaries for bullish OBs
• bearish_ob_top / bearish_ob_bottom: Zone boundaries for bearish OBs
• bullish_breaker / bearish_breaker: 1 when OB is broken (becomes breaker block)

The ob_signal function generates signals:

• 1: Price is within a bullish OB zone (potential long entry)
• -1: Price is within a bearish OB zone (potential short entry)
• 0: Price is outside any OB zone

Chart Parameters

The image above uses the following parameters:

Parameter	Value
swing_length	10