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Perl vs R: What are the differences?

Developers describe Perl as "Highly capable, feature-rich programming language with over 26 years of development". Perl is a general-purpose programming language originally developed for text manipulation and now used for a wide range of tasks including system administration, web development, network programming, GUI development, and more. On the other hand, R is detailed as "A language and environment for statistical computing and graphics". R provides a wide variety of statistical (linear and nonlinear modelling, classical statistical tests, time-series analysis, classification, clustering, ...) and graphical techniques, and is highly extensible.

Perl and R belong to "Languages" category of the tech stack.

"Lots of libraries" is the primary reason why developers consider Perl over the competitors, whereas "Data analysis " was stated as the key factor in picking R.

Perl is an open source tool with 428 GitHub stars and 150 GitHub forks. Here's a link to Perl's open source repository on GitHub.

According to the StackShare community, R has a broader approval, being mentioned in 128 company stacks & 95 developers stacks; compared to Perl, which is listed in 132 company stacks and 61 developer stacks.

- No public GitHub repository available -

What is Perl?

Perl is a general-purpose programming language originally developed for text manipulation and now used for a wide range of tasks including system administration, web development, network programming, GUI development, and more.

What is R?

R provides a wide variety of statistical (linear and nonlinear modelling, classical statistical tests, time-series analysis, classification, clustering, ...) and graphical techniques, and is highly extensible.
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What are some alternatives to Perl and R?
PHP
Fast, flexible and pragmatic, PHP powers everything from your blog to the most popular websites in the world.
Ruby
Ruby is a language of careful balance. Its creator, Yukihiro “Matz” Matsumoto, blended parts of his favorite languages (Perl, Smalltalk, Eiffel, Ada, and Lisp) to form a new language that balanced functional programming with imperative programming.
C
Java
Java is a programming language and computing platform first released by Sun Microsystems in 1995. There are lots of applications and websites that will not work unless you have Java installed, and more are created every day. Java is fast, secure, and reliable. From laptops to datacenters, game consoles to scientific supercomputers, cell phones to the Internet, Java is everywhere!
Python
Python is a general purpose programming language created by Guido Van Rossum. Python is most praised for its elegant syntax and readable code, if you are just beginning your programming career python suits you best.
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Decisions about Perl and R
Seth Ammons
Seth Ammons
Principal Software Developer at SendGrid · | 10 upvotes · 14.8K views
atTwilio SendGridTwilio SendGrid
Go
Go
Perl
Perl
Docker
Docker
#ContinuousIntegration
#CodeCollaborationVersionControl

In addition to our fancy Docker setup, we have captured and sanitized production logs for the behavior of our legacy Perl MTA, and we can test that the log output from the new Go version behaves the same way as the old version. These tests are set up to allow us to switch between the legacy and new version of the MTA and ensure that both systems behave in a legacy-compatible way. Not only can we ensure that we operate against a variety of issues we've seen over time from inboxes, but we know that the newest version of our MTA continues to cover all the same expected behaviors of the legacy version. #CodeCollaborationVersionControl #ContinuousIntegration

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Eric Colson
Eric Colson
Chief Algorithms Officer at Stitch Fix · | 19 upvotes · 260.9K views
atStitch FixStitch Fix
Amazon EC2 Container Service
Amazon EC2 Container Service
Docker
Docker
PyTorch
PyTorch
R
R
Python
Python
Presto
Presto
Apache Spark
Apache Spark
Amazon S3
Amazon S3
PostgreSQL
PostgreSQL
Kafka
Kafka
#Data
#DataStack
#DataScience
#ML
#Etl
#AWS

The algorithms and data infrastructure at Stitch Fix is housed in #AWS. Data acquisition is split between events flowing through Kafka, and periodic snapshots of PostgreSQL DBs. We store data in an Amazon S3 based data warehouse. Apache Spark on Yarn is our tool of choice for data movement and #ETL. Because our storage layer (s3) is decoupled from our processing layer, we are able to scale our compute environment very elastically. We have several semi-permanent, autoscaling Yarn clusters running to serve our data processing needs. While the bulk of our compute infrastructure is dedicated to algorithmic processing, we also implemented Presto for adhoc queries and dashboards.

Beyond data movement and ETL, most #ML centric jobs (e.g. model training and execution) run in a similarly elastic environment as containers running Python and R code on Amazon EC2 Container Service clusters. The execution of batch jobs on top of ECS is managed by Flotilla, a service we built in house and open sourced (see https://github.com/stitchfix/flotilla-os).

At Stitch Fix, algorithmic integrations are pervasive across the business. We have dozens of data products actively integrated systems. That requires serving layer that is robust, agile, flexible, and allows for self-service. Models produced on Flotilla are packaged for deployment in production using Khan, another framework we've developed internally. Khan provides our data scientists the ability to quickly productionize those models they've developed with open source frameworks in Python 3 (e.g. PyTorch, sklearn), by automatically packaging them as Docker containers and deploying to Amazon ECS. This provides our data scientist a one-click method of getting from their algorithms to production. We then integrate those deployments into a service mesh, which allows us to A/B test various implementations in our product.

For more info:

#DataScience #DataStack #Data

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Interest over time
Reviews of Perl and R
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How developers use Perl and R
Avatar of benyomin
benyomin uses RR

What are my other choices for a vectorized statistics language. Professor was pushing SAS Jump (or was that SPSS) with a menu-driven point and click approach. (Reproducibility can still be accomplished, you publish the script generated by all your clicks.) But I want to type everything, great online tutorials for R. I think I made the right pick.

Avatar of Perljobs.Ru
Perljobs.Ru uses PerlPerl

The whole backend part (deployment and other scripts, business logic, web interface) is written in Perl.

Весь бэкенд (скрипты деплоя и прочие, бизнес-логика, веб-интерфейс) написан на Perl.

Avatar of John Galbraith
John Galbraith uses PerlPerl

I use Perl to rip through log files and compare them to some signature files I have created. When I get a match, it adds the bad guy to the list of shame in MySQL.

Avatar of Ralic Lo
Ralic Lo uses RR

Connect to database, data analytics, draw diagram. Machine Learning application, and also used Spark-R for big data processing.

Avatar of Tino Gehlert
Tino Gehlert uses RR

Visualisation of air quality in various rooms by RShiny (hosted free on shinyapps.io)

Avatar of Alexander Karelas
Alexander Karelas uses PerlPerl

A very expressive language, lets you say the same thing in many different ways

Avatar of rapt.fm
rapt.fm uses PerlPerl

We use perl with rex to control our distributed systems.

Avatar of Sesync
Sesync uses RR

R is primarily used by SESYNC's researchers

Avatar of ssshake
ssshake uses PerlPerl

I use perl on some legacy applications.

Avatar of STILLWATER SUPERCOMPUTING INC
STILLWATER SUPERCOMPUTING INC uses RR

Offline deep analytics and modeling

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