How to Build a Weighted Random Load Balancer in Python

A Python load balancer mock that distributes requests across servers based on configurable weights using a cumulative weighted random selection algorithm.

Easy Python 3.9+ Aug 9, 2026 System design patterns 13 views 0 copies

python how build weighted random load

Python code

32 lines

Python 3.9+

import random
from collections import Counter

SERVERS = {
    "server-a": 50,
    "server-b": 30,
    "server-c": 20,
}


def weighted_random_server(servers: dict[str, int]) -> str:
    """Select a server based on its weight (higher weight = more likely)."""
    total_weight = sum(servers.values())
    rand = random.uniform(0, total_weight)
    cumulative = 0
    for server, weight in servers.items():
        cumulative += weight
        if rand <= cumulative:
            return server
    return list(servers.keys())[-1]


if __name__ == "__main__":
    random.seed(42)
    num_requests = 10_000
    selections = [weighted_random_server(SERVERS) for _ in range(num_requests)]
    distribution = Counter(selections)

    print(f"Requests: {num_requests}")
    for server, weight in SERVERS.items():
        actual = distribution[server] / num_requests * 100
        print(f"{server}: weight={weight}%, actual={actual:.1f}%")

Output

stdout

Requests: 10000
server-a: weight=50%, actual=49.6%
server-b: weight=30%, actual=29.8%
server-c: weight=20%, actual=20.6%

How it works

The algorithm first totals all server weights, then generates a random float between 0 and that total. Each server adds its weight to a cumulative sum, and the first server whose cumulative sum surpasses the random value gets selected. This creates a direct proportion between weight and selection probability — a server with weight 50 is chosen roughly 50% of the time. Using random.seed(42) makes the output reproducible for testing.

Common mistakes

Skipping error handling when how to build a weighted random load balancer in python can hide bad input.
Forgetting to match the Python version if you use newer syntax.

Variations

Wrap the core logic in a function and call it from `if __name__ == "__main__":` for reuse.

Real-world use cases

Inside automation scripts and CLIs that need to how to build a weighted random load balancer in python as one step of a larger job.
In data-cleaning or ETL pipelines where you how to build a weighted random load balancer in python before validating or storing records.
In backend services and background workers that how to build a weighted random load balancer in python while processing requests or files.

How to Build a Weighted Random Load Balancer in Python

Python code

Output

How it works

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Real-world use cases

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Python code

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How it works

Common mistakes

Variations

Real-world use cases

More from System design patterns

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