How to Build a Running Maximum List in Python

Compute a list where each element is the maximum of all numbers seen so far from an input list.

Easy Python 3.9+ Aug 9, 2026 Lists & loops 16 views 0 copies

running-max iteration lists algorithms

Python code

14 lines

Python 3.9+

def running_maximum(numbers):
    result = []
    current_max = float('-inf')
    for num in numbers:
        if num > current_max:
            current_max = num
        result.append(current_max)
    return result

if __name__ == "__main__":
    numbers = [3, 1, 4, 1, 5, 9, 2, 6]
    max_list = running_maximum(numbers)
    print(f"Input:  {numbers}")
    print(f"Output: {max_list}")

Output

stdout

Input:  [3, 1, 4, 1, 5, 9, 2, 6]
Output: [3, 3, 4, 4, 5, 9, 9, 9]

How it works

The function running_maximum iterates over each number once. It maintains a current_max variable that holds the largest value encountered so far. For each number, if it's greater than the current max, the max is updated; otherwise, it stays the same. The updated max is then appended to the result list. This algorithm runs in O(n) time and uses O(1) extra space besides the output list.

Common mistakes

Forgetting to initialize `current_max` properly; using 0 can break for negative numbers.
Updating `current_max` only when a new max is found but appending the wrong value.
Trying to use `max()` on the entire prefix each time, leading to O(n²) complexity.

Variations

Use `itertools.accumulate(numbers, max)` to achieve the same result in one line.
Use a list comprehension with a temporary variable if you prefer a functional style.

Real-world use cases

Tracking the highest score seen so far while processing a stream of game events.
Calculating cumulative record highs in financial time series data for analytics dashboards.
Monitoring peak resource usage (like CPU or memory) over a series of measurements.

How to Build a Running Maximum List in Python

Python code

Output

How it works

Common mistakes

Variations

Real-world use cases

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Python code

Output

How it works

Common mistakes

Variations

Real-world use cases

More from Lists & loops

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