Minimum Coin Change in Python

Algorithms: Dynamic Programming November 15, 2026 python

Minimum coin change finds the fewest coins needed to make an exact amount when each denomination can be reused.

python
 1
 2
 3
 4
 5
 6
 7
 8
 9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
38
39
40
41
42
43
44
45
46
47
48
49
50
51
52
53
54
55
56
57
58
59
60
61
62
63
64
65
66
67
68
69
70
71
72
73
74
75
76
from bisect import bisect_left

# Minimum Coin Change in Python
#
# PURPOSE
# Minimum coin change finds the fewest coins needed to make an exact amount when each
# denomination can be reused. Greedy selection fails for arbitrary denominations.
#
# METHOD
# Set the zero amount to zero coins and other amounts to an unreachable sentinel. For each
# amount, consider every coin and extend a reachable smaller amount by one coin.
#
# COMPLEXITY
# O(amount * m) time and O(amount) auxiliary space for m denominations; pseudo-polynomial in
# the numeric amount.
#
# CONTRACT
# amount >= 0, all coins > 0, m is their count. Returns -1 if impossible. The sentinel
# amount+1 must fit.
# 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 minimum_coins(coins: list[int], amount: int) -> int:
    alg_require(isinstance(coins, (list, tuple)) and len(coins) <= 1000000)
    alg_require(type(amount) is int and -2147483648 <= amount <= 2147483647)
    m: int = len(coins)
    alg_require(m >= 0 and m <= 1000000)
    alg_require(len(coins) == m)
    alg_require(amount >= 0 and amount <= 1000000)
    for value in coins:
        alg_require(value > 0)
    dp: list[int] = [0] * alg_size(amount + 1)
    x: int = 1
    j: int = 0
    while x <= amount:
        dp[x] = amount + 1
        j = 0
        while j < m:
            if coins[j] <= x:
                dp[x] = min(dp[x], dp[x - coins[j]] + 1)
            j += 1
        x += 1
    if dp[amount] > amount:
        return -1
    return dp[amount]

coins = [1, 3, 4]
amount = 6
result = minimum_coins(coins, amount)
print(result)