Nowadays, more and more people get in touch with programming in their spare time. Also, companies are seeking software engineers, so the demand for computer software and hardware increases. Hardware companies like Intel, AMD, and Nvidia list high revenue in the last years, and so do many other software companies like Microsoft or Apple. [1,2]
Although the power consumption has continued to increase, it has started to level off in the last years. There might be a lot of reasons why this is happening like the lockdown, smarter usage, and/or the better efficiency of electrical gadgets. [3,4,5]
Programs can also vary in speed, energy consumption, and memory allocation. In general, one can divide programming languages into three categories: compiled, compiled in a virtual machine, or interpreted. The following table represents results of a benchmark of computational tasks among 27 different programming languages. [6]
In general, one can say that compiled languages are faster than virtual machine compilers, and virtual machine compilers are faster than interpreted languages. The same goes for memory usage. Regardless of this observation, there are a few exceptions.
There are some VM programming languages which outperform some compiled languages, these are Java and Lisp. Giving more attention to Java, you can see that it is in the top 5 fastest and also in the top 5 economical programming languages. Only 4 programming languages are faster and more efficient, and all of them are compiler-based. A closer look at the following table shows the ratio between energy and time. This shows even more how efficient some of the programming languages are
Since Python is one of the most trending programming languages of the last few years, I am surprised that it is one of the slowest and most inefficient languages in these statistics. [7] In comparison with the first place, the contrast is even bigger. Python is 75 times less efficient and 71 times slower than C. To be fair, Python is more convenient. It is much easier to write and understand code using Python, which might also be a reason why so many newcomers choose this language. But based on speed and power consumption, this programming language should be the last choice, since it is at the bottom of the chart.
[3] https://data.worldbank.org/indicator/EG.USE.ELEC.KH.PC?end=2014&locations=EU&start=1960&view=chart