README
¶
Sloc Cloc and Code (scc)
A tool similar to cloc, sloccount and tokei. For counting physical the lines of code, blank lines, comment lines, and physical lines of source code in many programming languages.
Goal is to be the fastest code counter possible, but also perform COCOMO calculation like sloccount and to estimate code complexity similar to cyclomatic complexity calculators. In short one tool to rule them all.
Also it has a very short name which is easy to type scc.
If you don't like sloc cloc and code feel free to use the name Succinct Code Counter.
Dual-licensed under MIT or the UNLICENSE.
Read all about how it came to be along with performance benchmarks,
- https://boyter.org/posts/sloc-cloc-code/
- https://boyter.org/posts/why-count-lines-of-code/
- https://boyter.org/posts/sloc-cloc-code-revisited/
- https://boyter.org/posts/sloc-cloc-code-performance/
- https://boyter.org/posts/sloc-cloc-code-performance-update/
Some reviews of scc
- https://nickmchardy.com/2018/10/counting-lines-of-code-in-koi-cms.html
- https://www.feliciano.tech/blog/determine-source-code-size-and-complexity-with-scc/
For performance see the Performance section
Other similar projects,
- cloc the original sloc counter
- gocloc a sloc counter in Go inspired by tokei
- loc rust implementation similar to tokei but often faster
- loccount Go implementation written and maintained by ESR
- ployglot ATS sloc counter
- sloccount written as a faster cloc
- tokei fast, accurate and written in rust
Interesting reading about other code counting projects tokei, loc, polyglot and loccount
- https://www.reddit.com/r/rust/comments/59bm3t/a_fast_cloc_replacement_in_rust/
- https://www.reddit.com/r/rust/comments/82k9iy/loc_count_lines_of_code_quickly/
- http://blog.vmchale.com/article/polyglot-comparisons
- http://esr.ibiblio.org/?p=8270
Further reading about processing files on the disk performance
Install
If you are comfortable using Go and have >= 1.10 installed the usual go get -u github.com/boyter/scc/ will install for you.
If you are looking for binaries see Releases for Windows, GNU/Linux and macOS for both i386 and x86_64 bit machines.
A snap install exists https://snapcraft.io/scc thanks to Ricardo. You can run sudo snap install scc to install it.
If you would like to assist with getting scc added into apt/homebrew/chocolatey/etc... please submit a PR or at least raise an issue with instructions.
Pitch
Why use scc?
- It is very fast and gets faster the more CPU you throw at it
- Accurate
- Works very well across multiple platforms without slowdown (Windows, Linux, macOS)
- Large language support
- Can ignore duplicate files
- Has complexity estimations
- You need to tell the difference between Coq and Verilog in the same directory
Why not use scc?
- You don't like Go for some reason
Usage
Command line usage of scc is designed to be as simple as possible.
Full details can be found in scc --help.
Sloc, Cloc and Code. Count lines of code in a directory with complexity estimation.
Ben Boyter <ben@boyter.org> + Contributors
Usage:
scc [flags]
Flags:
--avg-wage int average wage value used for basic COCOMO calculation (default 56286)
--binary disable binary file detection
--by-file display output for every file
--cocomo remove COCOMO calculation output
--debug enable debug output
--exclude-dir strings directories to exclude (default [.git,.hg,.svn])
--file-gc-count int number of files to parse before turning the GC on (default 10000)
-f, --format string set output format [tabular, wide, json, csv, cloc-yaml] (default "tabular")
-h, --help help for scc
-i, --include-ext strings limit to file extensions [comma separated list: e.g. go,java,js]
-l, --languages print supported languages and extensions
-c, --no-complexity skip calculation of code complexity
-d, --no-duplicates remove duplicate files from stats and output
--no-gitignore disables .gitignore file logic
--no-ignore disables .ignore file logic
-M, --not-match stringArray ignore files and directories matching regular expression
-o, --output string output filename (default stdout)
-s, --sort string column to sort by [files, name, lines, blanks, code, comments, complexity] (default "files")
-t, --trace enable trace output. Not recommended when processing multiple files
-v, --verbose verbose output
--version version for scc
-w, --wide wider output with additional statistics (implies --complexity)
Output should look something like the below for the redis project
$ scc .
───────────────────────────────────────────────────────────────────────────────
Language Files Lines Code Comments Blanks Complexity
───────────────────────────────────────────────────────────────────────────────
C 249 143701 103269 24163 16269 25906
C Header 199 27537 18543 5768 3226 1557
TCL 98 16865 14098 954 1813 1404
Shell 36 1106 775 215 116 89
Lua 20 525 387 70 68 65
Autoconf 18 10821 8469 1326 1026 951
gitignore 11 151 135 0 16 0
Makefile 9 1031 722 100 209 50
Markdown 8 1886 1363 0 523 0
Ruby 8 722 580 69 73 107
HTML 5 9658 8791 12 855 0
C++ 5 311 244 16 51 31
YAML 4 273 254 0 19 0
License 3 66 55 0 11 0
CSS 2 107 91 0 16 0
Python 2 219 162 18 39 68
C++ Header 1 9 5 3 1 0
Smarty Template 1 44 43 0 1 5
m4 1 562 393 53 116 0
Plain Text 1 23 16 0 7 0
Batch 1 28 26 0 2 3
───────────────────────────────────────────────────────────────────────────────
Total 682 215645 158421 32767 24457 30236
───────────────────────────────────────────────────────────────────────────────
Estimated Cost to Develop $5,513,136
Estimated Schedule Effort 29.350958 months
Estimated People Required 22.250054
───────────────────────────────────────────────────────────────────────────────
Note that you don't have to specify the directory you want to run against. Running scc will assume you want to run against the current directory.
You can also run against multiple files or directories scc directory1 directory2 file1 file2 with the results aggregated in the output.
Interesting Use Cases
Used inside Intel Nemu Hypervisor to track code changes between revisions https://github.com/intel/nemu/blob/topic/virt-x86/tools/cloc-change.sh#L9 Appears to also be used inside both http://codescoop.com/ and https://pinpoint.com/
Features
scc uses a small state machine in order to determine what state the code is when it reaches a newline \n. As such it is aware of and able to count
- Single Line Comments
- Multi Line Comments
- Strings
- Multi Line Strings
- Blank lines
Because of this it is able to accurately determine if a comment is in a string or is actually a comment.
It also attempts to count the complexity of code. This is done by checking for branching operations in the code. For example, each of the following for if switch while else || && != == if encountered in Java would increment that files complexity by one.
Complexity Estimates
Lets take a minute to discuss the complexity estimate itself.
The complexity estimate is really just a number that is only comparable to files in the same language. It should not be used to compare languages directly without weighting them. The reason for this is that its calculated by looking for branch and loop statements in the code and incrementing a counter for that file.
Because some languages don't have loops and instead use recursion they can have a lower complexity count. Does this mean they are less complex? Probably not, but the tool cannot see this because it does not build an AST of the code and simple scans through it.
Generally though the complexity there is to help estimate between projects written in the same language, or for finding the most complex file in a project scc --by-file -s complexity which can be useful when you are estimating on how hard something is to maintain, or when looking for those files that should probably be refactored.
Performance
Generally scc will the fastest code counter compared to any I am aware of and have compared against. The below comparisons are taken from the fastest alternative counters. See Other similar projects above to see all of the other code counters compared against. It is designed to scale to as many CPU's cores as you can provide.
However if you want greater performance and you have RAM to spare you can disable the garbage collector like the following on linux GOGC=-1 scc . which should speed things up considerably. For some repositories turning off the code complexity calculation via -c can reduce runtime as well.
Benchmarks are run on fresh 32 CPU Optimised Digital Ocean Virtual Machine 2019/03/04 all done using hyperfine with 3 warm-up runs and 10 timed runs.
scc v2.2.0 (compiled with Go 1.12)
tokei v9.0.0 (compiled with Rust 1.33)
loc v0.5.0 (compiled with Rust 1.33)
polyglot v0.5.19 (downloaded from github)
Redis https://github.com/antirez/redis/
| Program | Runtime |
|---|---|
| scc | 24.0 ms ± 2.7 ms |
| scc (no complexity) | 18.9 ms ± 2.2 ms |
| tokei | 26.6 ms ± 3.3 ms |
| loc | 80.1 ms ± 54.7 ms |
| polyglot | 15.0 ms ± 1.1 ms |
CPython https://github.com/python/cpython
| Program | Runtime |
|---|---|
| scc | 64.3 ms ± 6.3 ms |
| scc (no complexity) | 53.8 ms ± 6.5 ms |
| tokei | 74.9 ms ± 11.6 ms |
| loc | 155.1 ms ± 58.9 ms |
| polyglot | 83.9 ms ± 9.4 ms |
Linux Kernel https://github.com/torvalds/linux
| Program | Runtime |
|---|---|
| scc | 537.3 ms ± 33.1 ms |
| scc (no complexity) | 438.9 ms ± 30.3 ms |
| tokei | 525.9 ms ± 32.7 ms |
| loc | 1.543 s ± 0.059 s |
| polyglot | 1.022 s ± 0.056 s |
If you enable duplicate detection expect performance to fall by about 50%
API Support
The core part of scc which is the counting engine is exposed publicly to be integrated into other Go applications. See https://github.com/pinpt/ripsrc for an example of how to do this.
Adding/Modifying Languages
To add or modify a language you will need to edit the languages.json file in the root of the project, and then run go generate to build it into the application. You can then go install or go build as normal to produce the binary with your modifications.
Issues
Its possible that you may see the counts vary between runs. This usually means one of two things. Either something is changing or locking the files under scc, or that you are hitting ulimit restrictions. To change the ulimit see the following links.
- https://superuser.com/questions/261023/how-to-change-default-ulimit-values-in-mac-os-x-10-6#306555
- https://unix.stackexchange.com/questions/108174/how-to-persistently-control-maximum-system-resource-consumption-on-mac/221988#221988
- https://access.redhat.com/solutions/61334
- https://serverfault.com/questions/356962/where-are-the-default-ulimit-values-set-linux-centos
- https://www.tecmint.com/increase-set-open-file-limits-in-linux/
To help identify this issue run scc like so scc -v . and look for the message too many open files in the output. If it is there you can rectify it by setting your ulimit to a higher value.
Low Memory
If you are running scc in a low memory environment < 512 MB of RAM you may need to set --filegccount or --fgc to a lower value such as 0 to force the garbage collector to be on at all times.
A sign that this is required will be scc crashing with panic errors.
Tests
scc is pretty well tested with many unit, integration and benchmarks to ensure that it is fast and complete.
Package
Run go build for windows and linux then the following in linux, keep in mind need to update the version
GOOS=darwin GOARCH=amd64 go build -ldflags="-s -w" && zip -r9 scc-2.5.0-x86_64-apple-darwin.zip scc
GOOS=darwin GOARCH=386 go build -ldflags="-s -w" && zip -r9 scc-2.5.0-i386-apple-darwin.zip scc
GOOS=windows GOARCH=amd64 go build -ldflags="-s -w" && zip -r9 scc-2.5.0-x86_64-pc-windows.zip scc.exe
GOOS=windows GOARCH=386 go build -ldflags="-s -w" && zip -r9 scc-2.5.0-i386-pc-windows.zip scc.exe
GOOS=linux GOARCH=amd64 go build -ldflags="-s -w" && zip -r9 scc-2.5.0-x86_64-unknown-linux.zip scc
GOOS=linux GOARCH=386 go build -ldflags="-s -w" && zip -r9 scc-2.5.0-i386-unknown-linux.zip scc
Badges (beta)
You can use scc to provide badges on your github/bitbucket/gitlab open repositories. For example,
The format to do so is,
https://sloc.xyz/PROVIDER/USER/REPO
An example of the badge for scc is included below, and is used on this page.
[](https://github.com/boyter/scc/)
By default the badge will show the repo's lines count. You can also specify for it to show a different category, by using the ?category= query string.
Valid values include code, blanks, lines, comments, cocomo and examples of the appearance are included below.
NB it may not work for VERY large repositories (has been tested on Apache hadoop/spark without issue).
Languages
List of supported languages. The master version of scc supports 239 languages at last count. Note that this is always assumed that you built from master, and it might trail behind what is actually supported. To see what your version of scc supports run scc --languages
Documentation
¶
There is no documentation for this package.
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