Implementation:TA Lib Ta lib python Lookback NaN Fill

Knowledge Sources	ta-lib-python
Domains	Technical_Analysis, Signal_Processing
Last Updated	2026-02-09 22:00 GMT

Overview

Concrete tool for handling the lookback period in TA-Lib indicator output arrays, implemented via the make_double_array and TA_*_Lookback C functions.

Description

Every indicator function in TA-Lib computes its lookback period by calling the C library's TA_<FUNC>_Lookback function, then allocates an output array pre-filled with NaN using make_double_array(length, lookback). The C function writes computed values starting at index lookback, leaving the first lookback elements as NaN.

This is an internal mechanism — users do not call these functions directly. However, understanding this behavior is essential for correctly interpreting indicator output.

Usage

This implementation is invoked automatically by every indicator function. Users should be aware that:

• Output arrays always have the same length as input arrays
• The first N elements (where N = lookback) are NaN
• The lookback value depends on the indicator and its parameters

Code Reference

Source Location

• Repository: ta-lib-python
• File: talib/_func.pxi
• Lines: L4642 (SMA lookback example), L660 (BBANDS lookback example)
• C Functions: lib.TA_SMA_Lookback(), lib.TA_BBANDS_Lookback(), etc.

Signature

# Internal Cython helpers (not user-facing)
cdef np.ndarray make_double_array(np.npy_intp length, int lookback):
    """Creates float64 array of given length with first 'lookback' elements as NaN"""

cdef np.ndarray make_int_array(np.npy_intp length, int lookback):
    """Creates int32 array of given length with first 'lookback' elements as 0"""

# C lookback functions (called internally)
# lib.TA_SMA_Lookback(timeperiod) -> int
# lib.TA_BBANDS_Lookback(timeperiod, nbdevup, nbdevdn, matype) -> int
# lib.TA_RSI_Lookback(timeperiod) -> int

Import

# These are internal functions, not importable by users.
# The lookback is handled automatically by all indicator functions.
import talib

I/O Contract

Inputs

Name	Type	Required	Description
length	int	Yes	Length of the input array
lookback	int	Yes	Computed lookback period for the indicator

Outputs

Name	Type	Description
output_array	np.ndarray	Array where elements [0:lookback] are NaN and elements [lookback:] contain computed values

Usage Examples

Observing Lookback Behavior

import numpy as np
import talib

close = np.random.random(50)

# SMA with timeperiod=20 has lookback of 19
sma = talib.SMA(close, timeperiod=20)
print(np.isnan(sma[:19]).all())  # True - first 19 elements are NaN
print(np.isnan(sma[19:]).any())  # False - remaining elements have values

# RSI with timeperiod=14 has lookback of 14
rsi = talib.RSI(close, timeperiod=14)
print(np.isnan(rsi[:14]).all())  # True

Related Pages

Implements Principle

• Principle:TA_Lib_Ta_lib_python_Lookback_Period_Handling

Requires Environment

• Environment:TA_Lib_Ta_lib_python_Python_Build_Environment
• Environment:TA_Lib_Ta_lib_python_TA_Lib_C_Library

Uses Heuristic

• Heuristic:TA_Lib_Ta_lib_python_NaN_Propagation_Behavior