This content originally appeared on DEV Community and was authored by Tawhid
Let’s be real for a second. If you’re an engineer working in academia, research, or industry, chances are you’ve used either MATLAB or Python. If you’ve been around long enough, maybe you’ve used both. And maybe you’ve wondered if you really have to choose between them. The good news is you don’t. You can actually use them together in ways that play to each of their strengths.
This post isn’t about which one is better. That argument has been going in circles for years. Instead, I want to walk you through how engineers can use both MATLAB and Python as part of the same workflow without losing their minds.
Why Use Both?
Here’s the thing. MATLAB is amazing for things like control systems, signal processing, numerical simulations, and basically anything math-heavy that needs a GUI and good plotting. Engineers love it because it just works out of the box and the documentation is actually readable.
Python, on the other hand, is free, open-source, and has a massive community. It’s super flexible and integrates with pretty much everything. It’s especially strong when it comes to machine learning, automation, web apps, and handling large-scale data.
Using both means you can run heavy-duty numerical models in MATLAB, then pass your results over to Python to analyze them with pandas, visualize them in seaborn, or use them in a machine learning pipeline with scikit-learn.
Getting Them to Talk
So how do you actually get MATLAB and Python to play nice?
1. Calling MATLAB from Python
MathWorks has a library called matlab.engine that lets you run MATLAB from within Python. You can call MATLAB functions, pass variables back and forth, and even run MATLAB scripts.
Here’s what it looks like:
import matlab.engine
eng = matlab.engine.start_matlab()
result = eng.sqrt(16.0)
print(result)
You just used MATLAB’s sqrt function in Python.
You can also run entire MATLAB scripts like this:
eng.run("your_script.m", nargout=0)
The setup takes a few steps, especially on Windows, but once it’s working, it’s surprisingly smooth.
2. Calling Python from MATLAB
You can also do the reverse. Starting in R2014b, MATLAB can call Python functions. This is huge because it means you don’t need to switch tools just to use a Python library.
Here’s an example:
py.print('Hello from Python')
You can even import and use libraries like NumPy or scikit-learn directly:
np = py.importlib.import_module('numpy');
array = np.array({1, 2, 3, 4});
If you’re working on simulations in MATLAB but want to push the results to a cloud dashboard or run a Python-based ML model, this kind of integration is a game changer.
Common Use Cases:
Let’s talk real-world. Here’s how engineers are actually combining MATLAB and Python:
Signal processing in MATLAB, then using Python to build dashboards or run analytics
Simulation modeling in Simulink, followed by Python automation for batch processing of outputs
Using MATLAB to generate synthetic data, then feeding it to TensorFlow or PyTorch
Building control systems in MATLAB, then integrating with Python-based edge devices (like Raspberry Pi or Jetson)
Tips for Staying Sane
Keep things modular – Write your code so each part (MATLAB or Python) can run independently. That way if something breaks, you know where to look.
Watch your data types – Passing data back and forth can get messy. Make sure to explicitly convert types between the two (e.g., lists vs arrays vs matrices).
Version control everything – This gets even more important when you’re mixing tools. Use Git and make sure you document how to run your code.
Use virtual environments – Especially on the Python side. Don’t let one project’s dependencies mess with another.
Test early and often – Debugging across two languages isn’t fun. Start small and build up.
Final Thoughts:
Look, there’s no rule that says you have to choose between MATLAB and Python. They’re just tools, and smart engineers use whatever tools help them solve problems faster and more reliably.
If you’re a Python fan but stuck in a MATLAB shop, learn how to bridge the gap. If you’re deep into MATLAB but want to experiment with open-source libraries, don’t be afraid to bring Python into the mix.
Combining them might just be the best of both worlds.
This content originally appeared on DEV Community and was authored by Tawhid