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Python Bags 1st Position In IEEE Spectrum Programming Language Rankings

Python is once again the top programming language, according to IEEE Spectrum’s fifth interactive ranking for leading languages that was released recently.

Spectrum ranks the languages by weighting and combining 11 metrics from 9 sources. The main feature of this ranking is that it is interactive and offers 5 ranking for 4 different platforms.

Platforms:

  • Web
  • Mobile
  • Enterprise
  • Embedded

Rankings:

  • IEEE Spectrum average
  • Trending – rapidly growing
  • Jobs – in demand by employers
  • Open – popularity in open-source hubs
  • Custom – one can create their own ranking, based on date and various criteria

In this article, I will be mainly discussing the results obtained in the IEEE Spectrum average:


Like the previous year, Python still continues to top the chart. This time it has managed to strengthen its position by widening the gap between the first and second position (last year Python won by a thin margin with 100 to C’s 99.7).

It’s worth noting that Python ranks first in the default, trending and open source interactive rankings but it still stands at no. 3 behind Java and C when it comes to jobs ranking (languages that are preferred by employers).

C++ jumped from 4th to the 2nd position this year pushing C and Java one rank lower to 3rd and 4th slot respectively. While C# continues to hold its ground with a constant rank 5, both R and JavaScript have lost a rank each to PHP — which has surprisingly managed to slither to 6th position.

As for the 9th and 10th slots, they are occupied by Go and Assembly knocking out Swift from the top 10 list this time.

But let’s talk about the winner here. Why is Python continually gaining more and more programmer’s attention? There are two changes in the list this time that might tell us why.

Firstly, Python is now a highly preferred language for embedded computing. Earlier, embedded applications relied heavily on compiled languages to save code evaluation overhead on machines that came with limited processing power and memory. But modern microcontrollers can take care of that easily.

The second reason can be attributed to the decline in R’s ranking. While R is a specialized language that handles big data and statistic, the interest in large data sets is steering towards its applications in machine learning. Here, the provision of high-quality libraries for both statistics and machine learning in Python make it a more attractive option than the more specialized R.

In addition to this, the popularity of Python Web frameworks such as Django, Flask, etc. helps too. Python is also quite popular in the field of data science and heavily used for automation/scripting in IT.

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