100x faster using numpy

or optionally numba. The result is the same to 4  decimal places

pandas_ta/candles/ha.py

@@ -1,8 +1,33 @@
 # -*- coding: utf-8 -*-
+import numpy as np
 from pandas import DataFrame, Series
-from pandas_ta._typing import DictLike, Int
+from pandas_ta._typing import DictLike, Int, List
 from pandas_ta.utils import v_offset, v_series
 
+try:
+    from numba import njit
+except ImportError:
+    def njit(_): return _
+
+
+@njit
+def heiken_ashi_numpy(c_open, c_high, c_low, c_close):
+    """fast version using numpy and optionally numba"""
+    ha_close = (c_open + c_high + c_low + c_close) / 4
+    ha_open = np.empty_like(ha_close)
+    ha_open[0] = (c_open[0] + c_close[0]) / 2
+    for i in range(1, len(c_close)):
+        ha_open[i] = (ha_open[i - 1] + ha_close[i - 1]) / 2
+    ha_high = np.maximum(np.maximum(ha_open, ha_close), c_high)
+    ha_low = np.minimum(np.minimum(ha_open, ha_close), c_low)
+    return ha_open, ha_high, ha_low, ha_close
+
+def heiken_ashi_series(open: Series, high: Series, low: Series, close: Series) -> List[Series]:
+    """takes in series, outputs series."""
+    inputs = [open, high, low, close]
+    outs = heiken_ashi_numpy(open.values, high.values, low.values, close.values)
+    outs = [Series(outs[i], index=inputs[i].index) for i in range(len(inputs))]
+    return outs
 
 def ha(
     open_: Series, high: Series, low: Series, close: Series,
@@ -47,21 +72,15 @@ def ha(
         return
 
     # Calculate
+    ha_open, ha_high, ha_low, ha_close = heiken_ashi_series(open_, high, low, close)
     m = close.size
     df = DataFrame({
-        "HA_open": 0.5 * (open_.iloc[0] + close.iloc[0]),
-        "HA_high": high,
-        "HA_low": low,
-        "HA_close": 0.25 * (open_ + high + low + close),
+        "HA_open": ha_open,
+        "HA_high": ha_high,
+        "HA_low": ha_low,
+        "HA_close": ha_close,
     })
 
-    for i in range(1, m):
-        df["HA_open"].iloc[i] = 0.5 * (df["HA_open"].iloc[i - 1] \
-            + df["HA_close"].iloc[i - 1])
-
-    df["HA_high"] = df[["HA_open", "HA_high", "HA_close"]].max(axis=1)
-    df["HA_low"] = df[["HA_open", "HA_low", "HA_close"]].min(axis=1)
-
     # Offset
     if offset != 0:
         df = df.shift(offset)