#1 Top reasons why Engineers must learn Python!
Invest in yourself; Knowledge Compounds
Engineer's Work Expectation (generated by GPT-4)
An engineer applies scientific and mathematical principles to design, develop, and maintain various systems, structures, and processes. They solve practical problems, optimize efficiency, and ensure safety and reliability in diverse fields such as electronics, civil, mechanical, software, and more.
Reality
However, majority of an engineer's time is spent on
1. Inputting data into software, spreadsheets, etc. ?
2. Creating and Maintaining the calculation/design files (ensuring everything is updated as the project progresses) ??
3. Communicating changes to the stakeholders ??
4. Documenting the design as Reports, Drawings, Calculations, etc. ??
5. Repeat the above for each revision ?
Job Satisfaction
Job satisfaction is possible only when we love ?? what we do at work.
Majority of the stuff that we dread at work is laborious, repetitive stuff that does not relate to our work expectation.
Humans are good at creative work while machines are great at repetitive work.
Knowing to program a machine will provide us with Time (the most precious resource). We will have more time to think on the creative aspects of our profession, like optimizing the design, etc., while the machines shall do the laborious and repetitive stuff that we hate to do.
Why Python?
Python has an enormous Open Source communities (like NumFOCUS) which abstracts complex mathematical and engineering computations into simple packages that anyone in the world can use with confidence.
An Example
A Python code to perform Fast Fourier Transformation will have only two lines
领英推荐
from numpy.fft import fft # Import function from the package
X = fft(y) # Apply the fn. on the input variable (y)
About Python (generated by GPT-4)
Python, created in 1991, is a readable, versatile, and high-level programming language with a rich ecosystem of libraries and a strong community. It supports multiple programming paradigms and runs on various platforms. Python is widely used in web development, data analysis, machine learning, and automation, making it a valuable skill for engineers.
Easy Digital Transformation with Python
Data is the new Oil
Consider a critical calculation/computation that is performed in every project, say for example design of a lifting padeye.
It could be performed with a spreadsheet. But eventually we end up with a large number of spreadsheets (each customized for individual project requirements) living in its own project folder.
Extracting key design inputs and results from all the past projects will become a nightmare in this case.
On the other hand, the same could be done using a jupyter notebook (A python notebook environment), wherein we log the key data into a Document Database (NoSQL database) like MongoDB.
In both the cases, we will have a dedicated calculation file that lives in its own project folder. But with the case of jupyter notebook we have the possibility to store key information in a centralized Database, which could be used for benchmarking and other data analytics requirements.
Why not give it a try and see how leveraging Python can transform your engineering practice?
What Next?
Stay tuned for the next edition of Python for Engineers newsletter:
#2 Experimenting Python notebooks on Colaboratory
References
ADAS | Robotics | AUTOSAR | DevOps
1 年Helpful initiative Swarup.
I help you work smart through Digital Mastery
1 年Thank you ?? Newsletter statistics: 255 subscribers in 4 days ?? 138 views in 4 days ?? Stay tuned this weekend for the next edition: Experimenting Python notebooks on Colaboratory
Chief Engineer in Saipem India Projects at Saipem India Projects Ltd
1 年Thanks Swarup.
Senior Software Engineer at HCL Technologies
1 年Very useful