I am a Python guy. I have been for years.
It’s the comfortable hoodie of programming languages. If I need to build a backend, scrape a website, or analyze a massive dataset, my fingers type import pandas before my brain even fully wakes up. It’s fast to write, easy to read, and the ecosystem is massive.
But recently, I had to break up with Python. At least, for one specific project.
I was building a High-Frequency Trading (HFT) engine. If you aren't familiar with HFT, just know this: Time is not money. Time is everything.
In HFT, being "fast" isn't about how fast you can write the code; it's about how fast the code executes. We are talking microseconds. And this is where my beloved Python started to betray me.
Here is why I bit the bullet, suffered through the learning curve, and rewrote my trading engine in Rust.
The "Stop the World" Problem
The biggest issue wasn't Python's raw speed. You can optimize Python. You can use C-extensions. You can use PyPy.
The issue was unpredictability.
Python uses a Garbage Collector (GC) to manage memory. Most of the time, this is great because you don't have to worry about allocating and freeing memory manually. But the GC has a nasty habit. Every once in a while, it decides the house is too messy, and it pauses your program to clean up.
In web development, a 50-millisecond pause is unnoticeable.
In trading, a 50-millisecond pause is the difference between a profit and a loss.
I remember staring at my logs one afternoon. My strategy was mathematically perfect. The signal came in. But my order went out late. Why? Because Python decided that exact moment was a great time to clean up unused variables.
I realized I couldn't build a Ferrari engine and put it inside a minivan.
Enter Rust: The Strict Teacher
I had heard the hype about Rust. "It’s memory safe." "It’s as fast as C++." "It’s blazingly fast."
So, I decided to try it.
I won’t lie to you, the first two weeks were miserable.
Coming from Python, Rust feels like trying to write poetry while someone screams grammar rules at you. It has this thing called the Borrow Checker. It prevents you from making memory errors, but it does so by refusing to compile your code if there is even a 1% chance you might mess up.
I spent days fighting the compiler. I wanted to just "make it work," and Rust kept saying, "No, Frank. You can't do that. It’s unsafe."
But then, something clicked.
Why the Struggle Was Worth It
Once I got past the fighting stage, I noticed something incredible.
1. Consistent Latency
Rust doesn't have a Garbage Collector. It manages memory through a system of ownership at compile time. This means there are no random pauses. If my loop takes 5 microseconds to run, it takes 5 microseconds every single time.
2. Sleep-Inducing Stability
In Python, you often find bugs when the code is actually running (Runtime Errors). "AttributeError: 'NoneType' object has no attribute...", we’ve all seen it.
In Rust, if the code compiles, it (mostly) just works. The compiler forced me to handle every possible error case before I could even run the app. This meant that when I deployed the bot, I wasn't sweating. I knew it wasn't going to crash because of a silly type error.
3. Raw Performance
The numbers didn't lie.
Python Engine: Average tick-to-trade latency ~12ms (with spikes up to 80ms).
Rust Engine: Average tick-to-trade latency ~40µs (microseconds).
That is not just an improvement; that is a different sport.
Do I Hate Python Now?
Absolutely not.
I still use Python every single day. In fact, my HFT setup is a hybrid:
Python is used for research, data analysis, backtesting, and drawing charts. It handles the "thinking."
Rust is used for the execution. It handles the "doing."
If you are building a blog, a standard API, or an MVP, stick with Python. It allows you to move fast and break things.
But if you are building systems where performance is a feature—like trading, game engines, or real-time streaming—you need to look at Rust.
The Takeaway
As developers, we get attached to our tools. We identify as "Python devs" or "JavaScript devs." But the best engineers aren't married to a language. They are married to solving the problem.
For HFT, the problem was latency. Python was the wrong tool. Rust was the right one.
It was a headache to learn, but looking at my dashboard now? It was worth every headache.
Hi, I'm Frank Oge. I build high-performance software and write about the tech that powers it. If you enjoyed this, check out more of my work at My Website
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