What Can Python Programming Do For MEs that MATLAB and Excel Can’t?
There is a reason Excel and Google sheets are used so extensively within businesses. Spreadsheets have a lot of easy-to-use features and it is fairly quick for new users to ramp up big projects in these programs.
However, Excel and others like it have their limitations. Excel suffers when the data gets very large. Python, on the other hand, is the go-to data science tool for big data jobs.
Not only do Python’s high-level features accelerate code development and make solving problems more intuitive, but the scientific community already has a wealth of libraries that are ready to use out of the box.
These include scientific packages like NumPy and SciPy that we mentioned above, but that’s just the tip of the iceberg.
Matplotlib is a 2D graph plotting library that’s ideal for scientific and engineering jobs, while SymPy is designed specifically for symbolic computing tasks that range from calculus to quantum physics.
There’s even mechpy, a Python toolbox built just for mechanical engineers.
When we compare MATLAB to Python, the difference is also clear. While both are interpreted languages, there are both technical and philosophical differences between them.
Besides details like variations in MATLAB and Python syntax, Python is much more versatile than MATLAB, has a much more vibrant support community, and has most of the same functionality. The exception is MATLAB’s Simulink for simulation and model-based design.
These technical details mostly stem from their divergent approaches to development: MATLAB is proprietary, closed-source software, while Python is an open-source project that’s supported by hundreds of developers.
This ultimately boils down to a few key benefits in Python’s favor. First, Python’s versatility allows us to do more with less. The same program can integrate functions from across multiple libraries, simplifying workflows and requiring less user input. And we all know what happens when a company has way too many spreadsheets. Python programming reduces this complexity by allowing us to combine much of this work into a single, unified platform.
Computer programming may not be our main focus as mechanical engineers, but in today’s digital world these skills are crucial. Learning a user-friendly language like Python can pay huge dividends. Since this language comes pre-equipped with all the scientific and mathematical tools we need, it’s easy to expand Python scripting into many use cases as your command over it grows.
There’s a good reason we’ve seen such a meteoric rise in Python’s popularity. It’s one of three official languages at Google. It’s the basis for major services like DropBox and Netflix. Just like these web services, our mechanical designs benefit from Python expertise.
Want to discover how Very’s engineers use Python and other programming languages to deliver the next generation of IoT devices? Learn more here.