Category: Programming

Professional, amateur, and something else

I opened a blog posts a while back by saying One of the differences between amateur and professional software development is whether you’re writing software for yourself or for someone else. It’s like the difference between keeping a journal and being a journalist. This morning I saw where someone pulled that quote and I thought […]

Piping is Method Chaining

What R users now call piping, popularized by Stefan Milton Bache and Hadley Wickham, is inline function application (this is notationally similar to, but distinct from the powerful interprocess communication and concurrency tool introduced to Unix by Douglas McIlroy in 1973). In object oriented languages this sort of notation for function application has been called … Continue reading Piping is Method Chaining

Standard Evaluation Versus Non-Standard Evaluation in R

There is a lot of unnecessary worry over “Non Standard Evaluation” (NSE) in R versus “Standard Evaluation” (SE, or standard “variables names refer to values” evaluation). This very author is guilty of over-discussing the issue. But let’s give this yet another try. The entire difference between NSE and regular evaluation can be summed up in … Continue reading Standard Evaluation Versus Non-Standard Evaluation in R

Tidyverse users: gather/spread are on the way out

From From There are two important new features inspired by other R packages that have been advancing of reshaping in R: The reshaping operation can be specified with a data frame that describes precisely how metadata stored in column names becomes data variables (and vice versa). This is inspired by the cdata package … Continue reading Tidyverse users: gather/spread are on the way out


I would like to once again recommend our readers to our note on wrapr::let(), an R function that can help you eliminate many problematic NSE (non-standard evaluation) interfaces (and their associate problems) from your R programming tasks. The idea is to imitate the following lambda-calculus idea: let x be y in z := ( λ … Continue reading wrapr::let()

Unit Tests in R

I am collecting here some notes on testing in R. There seems to be a general (false) impression among non R-core developers that to run tests, R package developers need a test management system such as RUnit or testthat. And a further false impression that testthat is the only R test management system. This is … Continue reading Unit Tests in R

rquery Substitution

The rquery R package has several places where the user can ask for what they have typed in to be substituted for a name or value stored in a variable. This becomes important as many of the rquery commands capture column names from un-executed code. So knowing if something is treated as a symbol/name (which … Continue reading rquery Substitution

Quoting Concatenate

In our last note we used wrapr::qe() to help quote expressions. In this note we will discuss quoting and code-capturing interfaces (interfaces that capture user source code) a bit more. My position on code-capturing interfaces (or non-standard-evaluation/NSE) is: if poorly handled, they can be a large interface price/risk to pay for the minor convenience of … Continue reading Quoting Concatenate

Reusable Pipelines in R

Pipelines in R are popular, the most popular one being magrittr as used by dplyr. This note will discuss the advanced re-usable piping systems: rquery/rqdatatable operator trees and wrapr function object pipelines. In each case we have a set of objects designed to extract extra power from the wrapr dot-arrow pipe %.>%. Piping Piping is … Continue reading Reusable Pipelines in R