Rust Performance Pitfalls: When Rust Runs Slower Than Python

How It All Started

The idea was simple: rewrite a Python data pipeline in Rust. The motivation? You know how it goes - Rust is fast, the compiler is strict, memory safety is guaranteed, and after the rewrite I could show off in code review saying “look, 10x performance improvement.”

So what happened? Python finished in 412 milliseconds, while my carefully crafted Rust version took 1.2 seconds. That’s right, Rust was nearly 3 times slower than Python. I ran the benchmark multiple times, added timestamps, added logging, even pulled out a profiler. The evidence was undeniable - Rust was indeed slower.

It felt like buying an expensive Ferrari only to get overtaken by a minivan on the highway. My ego was shattered into a million pieces.

Rust Isn’t Magic, It’s a Tool

After calming down, the problem became clear: Rust isn’t automatically fast, it’s potentially fast. It’s like buying a set of professional kitchen equipment - that doesn’t mean you can cook a Michelin-star meal. No matter how good your tools are, if you mistake salt for sugar, the dish will still be inedible.

Rust gives you precise memory control, lifetime management, zero-cost abstractions, and fearless concurrency. But it can’t save you from poor data structure choices, can’t save you from cloning everything everywhere, and can’t save you from brain-dead code design. In other words, Rust gives you a great gun, but if you can’t aim, you still won’t hit the target.

What On Earth Did I Write

Alright, let me show you the embarrassing code:

fn filter_and_sum(data: &Vec<i64>) -> i64 {
    let mut total = 0;
    for v in data.iter() {
        if data.contains(v) {     // the culprit is right here
            total += v;
        }
    }
    total
}

If you’ve written Rust before, your eye is probably twitching right now. What’s the problem? data.contains(v) on a Vec has O(n) time complexity, meaning for each element checked, it scans through the entire array from start to finish. The outer loop iterates through n elements, and each element triggers another n scans inside, giving us O(n^2) total.

Here’s an analogy: imagine you’re shopping at a supermarket, and every time you pick up an item, you have to dig through everything in your cart to check “do I already have this?” Buy 10 items and you’re checking 100 times. Buy 100 items and you’re checking 10,000 times. How could that not be slow?

Now look at how the Python version does it:

def filter_and_sum(data):
    total = 0
    s = set(data)  # the key is right here
    for v in data:
        if v in s:
            total += v
    return total

Python uses a set with O(1) lookup complexity, making the whole loop O(n). Same supermarket scenario, but the Python version has the shopping list on your phone - one glance tells you if you have it, no digging through the cart needed.

After the Fix, Everything Changed

Once I knew where the problem was, the fix was simple - just swap Vec for HashSet:

use std::collections::HashSet;

fn filter_and_sum(data: &Vec<i64>) -> i64 {
    let set: HashSet<i64> = data.iter().cloned().collect();
    let mut total = 0;
    for v in data.iter() {
        if set.contains(v) {
            total += v;
        }
    }
    total
}

Running it again, Rust now takes just 38 milliseconds - over 10 times faster than Python’s 412ms. Now that’s more like it. But the prerequisite is using the right tools. Otherwise, no language, no matter how fast, can save you.

Mistakes That Make Rust Slower Than Python

I’m not the only one making these blunders. Many Rust newcomers fall into these traps.

First, there’s the .clone() everywhere problem. When the borrow checker complains, a newbie’s first instinct is to add .clone() - as long as it compiles, right? But you might not realize that cloning a 3MB struct takes several milliseconds. It’s like photocopying your ID card every time you leave the house - convenient, but the copier will eventually overheat.

Then there’s using unwrap() in tight loops. Every unwrap has a branch check, and on hot paths, these branches add up. There’s also using String when &str would suffice - String allocates on the heap, &str borrows without allocation. If you can borrow, don’t allocate. That’s fundamental.

Next is forced parallelization. Python’s single-threaded model may look primitive, but at least it won’t let you shoot yourself in the foot. Rust’s concurrency is powerful, but misuse just adds overhead - thread scheduling, lock contention, channel costs, none of them are free.

Finally, there’s over-abstraction and using Vec for everything. Generics are indeed “zero-cost abstractions,” but abuse leads to monomorphization bloat. Vec is great, but it’s not universal. Use HashSet when you need HashSet, use HashMap when you need HashMap. Don’t be lazy.

When Does Rust Win

After all these pitfalls, when can Rust actually show its true power? The conditions for performance optimization aren’t that complicated: choose the right data structures, avoid unnecessary allocations, pre-allocate capacity, avoid clone storms, use iterators correctly, minimize IO blocking, keep algorithmic complexity in check. Do these things, and Rust’s performance advantages will naturally emerge.

Conversely, if you misuse Vec, clone everywhere, fight the borrow checker with workaround code, have the wrong algorithm to begin with, or rewrite without profiling the Python version first, then Python beating you is perfectly normal.

Final Thoughts

After this whole ordeal, my biggest takeaway is this: Python didn’t beat Rust - I beat myself. Rust gave me freedom, and I used that freedom to write slow code. Python gave me constraints, and those constraints protected me. If you don’t understand time complexity, memory allocation, ownership models, and data structure selection, Rust won’t save you. It will expose you.

So let me ask you: have you ever written Rust code that ran slower than Python? Have you ever gone on a cloning spree because the borrow checker complained? Have you ever stuffed everything into Vec because “it’s convenient”? Share your story in the comments - after all, Rust is fast, but only when you are too.

Did you find this article helpful?

If this article helped you avoid a moment of self-doubt, consider giving it a like so more people can see this pitfall, or share it with your Rust friends - they might be making the same mistakes right now. Follow Dream Beast Programming for more war stories like this. Got questions or your own painful experiences? Drop them in the comments - your story might be even better than mine.