IEEE Spectrum Declares Python The #1 Programming Language (ieee.org)
An anonymous reader quotes IEEE Spectrum's annual report on the top programming languages:
As with all attempts to rank the usage of different languages, we have to rely on various proxies for popularity. In our case, this means having data journalist Nick Diakopoulos mine and combine 12 metrics from 10 carefully chosen online sources to rank 48 languages. But where we really differ from other rankings is that our interactive allows you choose how those metrics are weighted when they are combined, letting you personalize the rankings to your needs. We have a few preset weightings -- a default setting that's designed with the typical Spectrum reader in mind, as well as settings that emphasize emerging languages, what employers are looking for, and what's hot in open source...
Python has continued its upward trajectory from last year and jumped two places to the No. 1 slot, though the top four -- Python, C, Java, and C++ -- all remain very close in popularity. Indeed, in Diakopoulos's analysis of what the underlying metrics have to say about the languages currently in demand by recruiting companies, C comes out ahead of Python by a good margin... Ruby has fallen all the way down to 12th position, but in doing so it has given Apple's Swift the chance to join Google's Go in the Top Ten... Outside the Top Ten, Apple's Objective-C mirrors the ascent of Swift, dropping down to 26th place. However, for the second year in a row, no new languages have entered the rankings. We seem to have entered a period of consolidation in coding as programmers digest the tools created to cater to the explosion of cloud, mobile, and big data applications.
"Speaking of stabilized programming tools and languages," the article concludes, "it's worth noting Fortran's continued presence right in the middle of the rankings (sitting still in 28th place), along with Lisp in 35th place and Cobol hanging in at 40th."
Python has continued its upward trajectory from last year and jumped two places to the No. 1 slot, though the top four -- Python, C, Java, and C++ -- all remain very close in popularity. Indeed, in Diakopoulos's analysis of what the underlying metrics have to say about the languages currently in demand by recruiting companies, C comes out ahead of Python by a good margin... Ruby has fallen all the way down to 12th position, but in doing so it has given Apple's Swift the chance to join Google's Go in the Top Ten... Outside the Top Ten, Apple's Objective-C mirrors the ascent of Swift, dropping down to 26th place. However, for the second year in a row, no new languages have entered the rankings. We seem to have entered a period of consolidation in coding as programmers digest the tools created to cater to the explosion of cloud, mobile, and big data applications.
"Speaking of stabilized programming tools and languages," the article concludes, "it's worth noting Fortran's continued presence right in the middle of the rankings (sitting still in 28th place), along with Lisp in 35th place and Cobol hanging in at 40th."
After using it, it is eh, not a big deal. You indent the same amount for everything in the block, which you are probably doing most of the time anyways. It is their little cheat around not having block delimiters.
If you need to a pick a reason to not like Python, this is not it.
Python has hit critical mass in both popularity and tools available. C, C++, Java, Perl and anything else the average /.er is going to complain about going anywhere just like FORTRAN and COLBOL haven't.
XKCD hit the nail on the head. It's something easy enough for middle schoolers to grock and powerful enough to use with TensorFlow. It's our office's go-to language for "I need this task done". It's basically BASIC where you can import math (numpy), plotting (matplotlib), neuralnetwork (TensorFlow) and other packages.
Programmers waste enormous amounts of time thinking about, or worrying about, the speed of noncritical parts of their programs, and these attempts at efficiency actually have a strong negative impact when debugging and maintenance are considered. We should forget about small efficiencies, say about 97% of the time: premature optimization is the root of all evil. Yet we should not pass up our opportunities in that critical 3%.".
You can knock out something in 30 minutes in Python that would take longer in anything else and the performance difference isn't worth doing it in something else.
How I miss thee.
OMG facts!
Not be owned by Oracle.
"Oh my God. This is terrible. This is the end of my Presidency. I'm fucked."; ~ Donald J. Trump