Exponential Search in Python

Algorithms: Searching November 15, 2026 python

Exponential search locates a search interval by doubling its size, then uses binary search..

python
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from bisect import bisect_left

# Exponential Search in Python
#
# PURPOSE
# Exponential search locates a search interval by doubling its size, then uses binary
# search.
#
# METHOD
# Check index zero. Double a bound until it passes the target or the input end, then binary-
# search the bounded interval.
#
# COMPLEXITY
# O(log(p+1)) comparisons for a match near index p; O(log n) worst case, O(1) space.
#
# CONTRACT
# Ascending input; returns any matching index or -1.
# Public APIs infer array lengths except in C, which accepts pointer/length pairs. Vertex
# counts and matrix dimensions remain explicit. Arrays must contain signed 32-bit integers.
# Sorted order, correct tree topology, and caller-owned data-structure invariants are
# preconditions; checking them on every query would change query complexity.
# Scalar and shape checks are included. Value-range checks are included where needed to
# prevent invalid indexing or nontermination. Allocation sizes are capped at 4,000,000
# workspace entries. Arithmetic outside Python raises an error on 32-bit overflow; Python
# uses arbitrary precision. Native allocation failures propagate. In-place outputs may be
# partly updated after arithmetic failure. These are single-threaded, in-memory
# implementations.
#
# LANGUAGE DETAILS
# Python 3.9+: automatic lengths, native lists, arbitrary-precision arithmetic, and
# bisect_left for LIS. Invalid scalar/shape inputs raise ValueError. Integer element types
# and sorted/tree invariants remain caller preconditions.
#
# EXAMPLE
# Expected return: 2.
# Run: python example.py
# Tests for this exact source artifact run before publication. The accompanying source
# archive includes unit cases, runtime results, and source hashes.

def alg_require(condition):
    if not condition:
        raise ValueError("invalid algorithm input; see contract")
def alg_size(n):
    alg_require(0 <= n <= 4000000)
    return n

def exponential_search(a: list[int], target: int) -> int:
    alg_require(isinstance(a, (list, tuple)) and len(a) <= 1000000)
    alg_require(type(target) is int and -2147483648 <= target <= 2147483647)
    n: int = len(a)
    alg_require(n >= 0 and n <= 1000000)
    alg_require(len(a) == n)
    if n == 0:
        return -1
    if a[0] == target:
        return 0
    bound: int = 1
    while bound < n and a[bound] < target:
        if bound > n // 2:
            bound = n
        else:
            bound *= 2
    low: int = bound // 2
    high: int = min(bound, n - 1)
    mid: int = 0
    while low <= high:
        mid = low + (high - low) // 2
        if a[mid] == target:
            return mid
        if a[mid] < target:
            low = mid + 1
        else:
            high = mid - 1
    return -1

a = [1, 3, 5, 7]
target = 5
result = exponential_search(a, target)
print(result)