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There are so many ways! For example, it allows you to automate numerous tasks in both the design phase and when analyzing the test data. There are lots of tools which have very convenient interfaces with Python. It’s absurd to waste an engineer by making them do repetitive tasks, when –if you know how to program– you can automate practically anything. With Python you can even work automatically with the much-hated Excel tables.
Python is very popular in science in general because there are a lot of scientists who find themselves having to program, even though they’re not actually programmers and don’t want to be. However, there are lots of scientific packages that can help them do anything they need, from the typical Numpy and Matplotlib –which almost everybody uses–, to more specific packages like Policastro, an excellent mechanical orbital module. Data scientists particularly have a large number of specialized packages available to them.
I’m also convinced the format of Jupyter Notebook is going to revolutionize the world of scientific publishing, as it enables you to read a scientific article while you interact with the data, and reproduces the actual procedure used by the original authors. I think the peer review process is going to be radically improved thanks to this tool.
Probably because those were the principles that guided its creator, Guido van Rossum, and which Tim Peters subsequently explicitly set down in what is known as “the Zen of Python”. This attracted programmers with this same type of goals and formed the original Python community.
They’re two different tools, like a hammer and a screwdriver. Fortran is a language that’s more difficult to read and longer to write, but it’s extremely fast. Python allows you to program much faster and is much clearer to read, but you need to make proper use of accelerator libraries to achieve anything like similar speeds, and it’s not always possible.
The best thing is to combine both languages, and use the best aspects of each one. For example, creating the algorithms that are heaviest mathematically in Fortran, and handling the program flow from Python.
My final project consisted of designing an unmanned aircraft specifically adapted to fly to Mars to support robotic exploration projects. I used Python for practically everything. For example, there’s a well known program called Xfoil, written in Fortran, which enables you to calculate the aerodynamic features of a wing profile. Using a genetic algorithm I wrote in Python, I used this program to automatically calculate an optimum profile for my flight conditions.
I also used Python to generate a mathematical model for the Martian atmosphere, implement a reliable mathematical model of a propeller, and to calculate effort distributions, derived data such as volume and weight from geometry, and the integral actions of the whole aircraft, such as autonomy and range, depending on the flight speed.
In my opinion, in Spain we’re really lacking in confidence when it comes to thinking of ourselves as a technological power. This type of event means that large numbers of people, all linked by the common factor of Python, can come together and get to know each other. Professionals can raise their profile and see they’re not alone, and for beginners, it’s a great source of inspiration and learning. It also allows sponsors to look for young talent, who also benefit by finding attractive jobs.
That’s why I think it’s very helpful to stage this type of events, not only on Python but on any technical issue. I think it could help us prevent the disastrous brain drain we’re undergoing, by giving people goals and targets inside Spain.
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