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This Week in Programming: Would Renaming Perl Save It from Terminal Unpopularity?

4 Nov 2017 6:00am, by

It’s been another week of new releases, such as Node.js 9 and Angular 5.0, but we’ll get there in time. There have also been some announcements in the world of machine learning and data science, and a slew of new Github features.

First off, however, we’re going to dive back into the ever-interesting horse race that is programming language popularity with another great, data-driven blog post from StackOverflow and look at a few related and follow up pieces that deal with one of the losers in that regard, the language that is just about to celebrate 30 years of existence — Perl.

  • So, StackOverflow has continued its series of posts, this time examining the opinions of hundreds of thousands of developers by looking at what they prefer to work with (or not). This time around, It looks at what are the most disliked programming languages, which happen to be (drumroll please) Perl, Delphi, and VBA, “by a fairly large margin”, followed by PHP, Objective-C, CoffeeScript, and Ruby. Before diving in too deeply here, we found a series of other stories this week that fall right in line with an add-on to these findings…
  • Jaxenter also covered this topic, but instead focused on the other end of the spectrum, noting that Kotlin, R and TypeScript were among least disliked programming languages, offering a recent survey from RebelLabs that “showed that Kotlin is the most beloved programming language and they’re not wrong — as it turns out, Stack Overflow measured programming languages’ popularity and reached the same conclusion.”
  • Meanwhile, SDTimes kept the focus on the general disdain for Perl and rounded out the list with some more general technologies. Atop this list were Internet Explorer, Visual Basic, Flash, COBOL, Fortran and Pascal, as disliked, and machine learning, Git, Python 3.x, HTML5 and CSS3, as well-loved.
  • But why is Perl so universally disliked? According to one author on the Perl blogs this week, it’s primarily because of the name, suggesting that Perl6 should be renamed Perl++. It has saddened him to see Perl lose ground to Python, Ruby and PHP, he writes, and he thinks that “one of the primary reasons for Perl’s declining image is the naming of a completely new language with the same name. I believe that calling it Perl6 has been the most destructive thing that has been done to the Perl language and will continue to be so.” Click through to read more of his reasoning, as we will move on to look at a piece from our own pages this week…
  • Following this thread, The New Stack’s David Cassel (who writes some seriously interesting stories) looks at Perl creator Larry Wall’s quest for a 100-year programming language. While apparently unpopular, Perl nonetheless celebrates its 30th anniversary in two months. Wall, he writes, “shared his own history of Perl, starting with his fateful decision to break backward compatibility in 2000 to develop an entirely new language called Perl 6 — which famously took 15 years before a stable version was finally released.” Wall’s quest, which he says was inspired by a 2003 essay by computer scientist Paul Graham envisioning “The Hundred-Year Language.” Cassel’s post goes on to detail a talk discussion earlier this year between Wall and Joe Armstrong, creator of Erlang, which we include below:

This Week in Programming News

This Week in Machine Learning and Data Science

  • First, Kaggle offers a look at the state of data science and machine learning with a survey of over 16,000 responses. Findings include that Python is still the most commonly used tool, but statisticians prefer R. Also, the average age of your common data scientist is around 30 years old and, surprise surprise, most have a masters degree and make some pretty healthy salaries. The company “shared the full, anonymized dataset on Kaggle for you to download and explore.”
  • Google’s mobile platform Firebase got some new machine learning capabilities “focused on tightening the integration of Firebase services and incorporating more machine learning technology into the toolkit.” These include the integration of Crashlytics by Fabric, overall UI and console overhauls, a new A/B testing framework, and Firebase Predictions, which uses machine learning to measure analytics and group users based on predicted behavior.
  • Finally, Redmonk looks at NVidia’s moves to simplify working with common deep learning frameworks. With this, they say that “Life has just got easier for people working on deep learning on AWS.” NVidia’s deep learning stack is “a curated set of software, distributed as containers, that they planned to make available to end users of GPUs on various cloud providers. The first of these cloud offerings came out this week in conjunction with the announcements of NVIDIA Tesla V100 GPUs availability on AWS.”

Feature image: Actor Nicolas Cage in the 1997 movie “Face/Off.”

A digest of the week’s most important stories & analyses.

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