Create Code Metrics with cloc

The cloc Perl script (yes, Perl!) by Al Danial (https://github.com/AlDanial/cloc) has been one of the go-to tools for generating code metrics. Given a single file, directory tree, archive, or git repo, cloc can speedily give you metrics on the count of blank lines, comment lines, and physical lines of source code in a vast array of programming languages.

I don’t remember the full context but someone in the R community asked about about this type of functionality and I had tossed together a small script-turned-package to thinly wrap the Perl cloc utility. Said package was and is unimaginatively named cloc🔗. Thanks to some collaborative input from @ma_salmon, the package gained more features. Recently I added the ability to process R markdown (Rmd) files (i.e. only count lines in code chunks) to the main cloc Perl script and was performing some general cleanup when the idea to create some RStudio addins hit me.

cloc Basics

As noted, you can cloc just about anything. Here’s some metrics for dplyr::group_by:

cloc("https://raw.githubusercontent.com/tidyverse/dplyr/master/R/group-by.r")## # A tibble: 1 x 10##   source language file_count file_count_pct   loc loc_pct blank_lines blank_line_pct comment_lines comment_line_pct## 1 group… R                 1             1.    44      1.          13             1.           110               1.

and, here’s a similar set of metrics for the whole dplyr package:

cloc_cran("dplyr")## # A tibble: 7 x 11##   source language file_count file_count_pct   loc loc_pct blank_lines blank_line_pct comment_lines comment_line_pct## 1 dplyr… R               148        0.454   13216 0.442          2671       0.380             3876          0.673  ## 2 dplyr… C/C++ H…        125        0.383    6687 0.223          1836       0.261              267          0.0464 ## 3 dplyr… C++              33        0.101    4724 0.158           915       0.130              336          0.0583 ## 4 dplyr… HTML             11        0.0337   3602 0.120           367       0.0522              11          0.00191## 5 dplyr… Markdown          2        0.00613  1251 0.0418          619       0.0880               0          0.     ## 6 dplyr… Rmd               6        0.0184    421 0.0141          622       0.0884            1270          0.220  ## 7 dplyr… C                 1        0.00307    30 0.00100           7       0.000995             0          0.     ## # ... with 1 more variable: pkg 

We can also measure (in bulk) from afar, such as the measuring the dplyr git repo:

cloc_git("git://github.com/tidyverse/dplyr.git")## # A tibble: 12 x 10##    source    language     file_count file_count_pct   loc  loc_pct blank_lines blank_line_pct comment_lines##  1 dplyr.git HTML                108        0.236   21467 0.335           3829       0.270             1114##  2 dplyr.git R                   156        0.341   13648 0.213           2682       0.189             3736##  3 dplyr.git Markdown             12        0.0263  10100 0.158           3012       0.212                0##  4 dplyr.git C/C++ Header        126        0.276    6891 0.107           1883       0.133              271##  5 dplyr.git CSS                   2        0.00438  5684 0.0887          1009       0.0711              39##  6 dplyr.git C++                  33        0.0722   5267 0.0821          1056       0.0744             393##  7 dplyr.git Rmd                   7        0.0153    447 0.00697          647       0.0456            1309##  8 dplyr.git XML                   1        0.00219   291 0.00454            0       0.                   0##  9 dplyr.git YAML                  6        0.0131    212 0.00331           35       0.00247             12## 10 dplyr.git JavaScript            2        0.00438    44 0.000686          10       0.000705             4## 11 dplyr.git Bourne Shell          3        0.00656    34 0.000530          15       0.00106             10## 12 dplyr.git C                     1        0.00219    30 0.000468           7       0.000493             0## # ... with 1 more variable: comment_line_pct

All in on Addins

The Rmd functionality made me realize that some interactive capabilities might be handy, so I threw together three of them.

Two of them extraction of code chunks from Rmd documents. One uses cloc other uses knitr::purl() (h/t @yoniceedee). The knitr one adds in some very nice functionality if you want to preserve chunk options and have “eval=FALSE” chunks commented out.

The final one will gather up code metrics for all the sources in an active project.

FIN

If you’d like additional features or want to contribute, give (https://github.com/hrbrmstr/cloc) a visit and drop an issue or PR.



*** This is a Security Bloggers Network syndicated blog from rud.is authored by hrbrmstr. Read the original post at: https://rud.is/b/2018/05/19/create-code-metrics-with-cloc/