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A tool similar to cloc, sloccount and tokei. For counting 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, estimate code complexity similar to cyclomatic complexity calculators and produce unique lines of code or DRYness metrics. In short one tool to rule them all.

Also it has a very short name which is easy to typescc.

If you don't like sloc cloc and code feel free to use the nameSuccinct Code Counter.

Licensed under MIT licence.

• Install
• Background
• Pitch
• Usage
• Complexity Estimates
• Unique Lines of Code (ULOC)
• COCOMO
• Output Formats
• Performance
• Development
• Adding/Modifying Languages
• Issues
• Badges (beta)
• Language Support
• Citation

While scc will always be a free and tool for individual developers, companies and businesses, we are exploring an enhanced version designed for teams and businesses. scc Enterprise will build on the core scc engine to provide historical analysis, team-level dashboards, and policy enforcement to help engineering leaders track code health, manage technical debt, and forecast project costs.

We are currently gathering interest for a private beta. If you want to visualize your codebase's evolution, integrate quality gates into your CI/CD pipeline, and get a big-picture view across all your projects,sign up for the early access listhere

You can installscc by using the standard go toolchain.

To install the latest stable version of scc:

go install github.com/boyter/scc/v3@latest

To install a development version:

go install github.com/boyter/scc/v3@master

Note thatscc needs go version >= 1.25.

Asnap install exists thanks toRicardo.

$ sudo snap install scc

NB Snap installed applications cannot run outside of/homehttps://askubuntu.com/questions/930437/permission-denied-error-when-running-apps-installed-as-snap-packages-ubuntu-17 so you may encounter issues if you use snap and attempt to run outside this directory.

Or if you haveHomebrew installed

$ brew install scc

Fedora Linux users can use aCOPR repository:

$ sudo dnf copr enable lihaohong/scc && sudo dnf install scc

On macOS, you can also install viaMacPorts

$ sudo port install scc

Or if you are usingScoop on Windows

$ scoop install scc

Or if you are usingChocolatey on Windows

$ choco install scc

Or if you are usingWinGet on Windows

winget install --id benboyter.scc --source winget

On FreeBSD, scc is available as a package

$ pkg install scc

Or, if you prefer to build from source, you can use the ports tree

$ cd /usr/ports/devel/scc && make install clean

Go to the directory you want to run scc from.

Run the command below to run the latest release of scc on your current working directory:

docker run --rm -it -v"$PWD:/pwd"  ghcr.io/boyter/scc:master scc /pwd

Binaries for Windows, GNU/Linux and macOS for both i386 and x86_64 machines are available from thereleases page.

https://about.gitlab.com/blog/2023/02/15/code-counting-in-gitlab/

If you would like to assist with gettingscc added into apt/chocolatey/etc... please submit a PR or at least raise an issue with instructions.

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 ofscc

• 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/
• https://metaredux.com/posts/2019/12/13/counting-lines.html

Setting upscc in GitLab

• https://about.gitlab.com/blog/2023/02/15/code-counting-in-gitlab/

A talk given at the first GopherCon AU aboutscc (press S to see speaker notes)

• https://boyter.org/static/gophercon-syd-presentation/
• https://www.youtube.com/watch?v=jd-sjoy3GZo

For performance see thePerformance section

Other similar projects,

• SLOCCount the original sloc counter
• cloc, inspired by SLOCCount; implemented in Perl for portability
• 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
• polyglot ATS sloc counter
• tokei fast, accurate and written in rust
• sloc coffeescript code counter
• stto new Go code counter with a focus on performance

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

• https://blog.burntsushi.net/ripgrep/

Usingscc to process 40 TB of files from GitHub/Bitbucket/GitLab

• https://boyter.org/posts/an-informal-survey-of-10-million-github-bitbucket-gitlab-projects/

Why usescc?

• 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
• cloc yaml output support so potentially a drop in replacement for some users
• Can identify or ignore minified files
• Able to identify many #! files ADVANCED!#115
• Can ignore large files by lines or bytes
• Can calculate the ULOC or unique lines of code by file, language or project
• Supports multiple output formats for integration, CSV, SQL, JSON, HTML and more

Why not usescc?

• You don't like Go for some reason
• It cannot count D source with different nested multi-line comments correctly#27

There are some important differences betweenscc and other tools that are out there. Here are a few important ones for you to consider.

Blank lines inside comments are counted as comments. While the line is technically blank the decision was made that once in a comment everything there should be considered a comment until that comment is ended. As such the following,

/* blank lines follow*/

Would be counted as 4 lines of comments. This is noticeable when comparing scc's output to other tools on largerepositories.

scc is able to count verbatim strings correctly. For example in C# the following,

privateconststringBasePath=@"a:\";// The below is returned to the user as a versionprivateconststringVersion="1.0.0";

Because of the prefixed @ this string ends at the trailing " by ignoring the escape character \ and as such should becounted as 2 code lines and 1 comment. Some tools are unable todeal with this and instead count up to the "1.0.0" as a string which can cause the middle comment to be counted ascode rather than a comment.

scc will also tell you the number of bytes it has processed (for most output formats) allowing you to estimate thecost of running some static analysis tools.

Command line usage ofscc is designed to be as simple as possible.Full details can be found inscc --help orscc -h. Note that the below reflects the state of master not a release, as suchfeatures listed below may be missing from your installation.

Sloc, Cloc and Code. Count lines of code in a directory with complexity estimation.Version 3.5.0 (beta)Ben Boyter <ben@boyter.org> + ContributorsUsage:  scc [flags] [files or directories]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  -m, --character                          calculate max and mean characters per line      --ci                                 enable CI output settings where stdout is ASCII      --cocomo-project-type string         change COCOMO model type [organic, semi-detached, embedded, "custom,1,1,1,1"] (default "organic")      --count-as string                    count extension as language [e.g. jsp:htm,chead:"C Header" maps extension jsp to html and chead to C Header]      --count-ignore                       set to allow .gitignore and .ignore files to be counted      --currency-symbol string             set currency symbol (default "$")      --debug                              enable debug output      --directory-walker-job-workers int   controls the maximum number of workers which will walk the directory tree (default 8)  -a, --dryness                            calculate the DRYness of the project (implies --uloc)      --eaf float                          the effort adjustment factor derived from the cost drivers (1.0 if rated nominal) (default 1)      --exclude-dir strings                directories to exclude (default [.git,.hg,.svn])  -x, --exclude-ext strings                ignore file extensions (overrides include-ext) [comma separated list: e.g. go,java,js]  -n, --exclude-file strings               ignore files with matching names (default [package-lock.json,Cargo.lock,yarn.lock,pubspec.lock,Podfile.lock,pnpm-lock.yaml])      --file-gc-count int                  number of files to parse before turning the GC on (default 10000)      --file-list-queue-size int           the size of the queue of files found and ready to be read into memory (default 8)      --file-process-job-workers int       number of goroutine workers that process files collecting stats (default 8)      --file-summary-job-queue-size int    the size of the queue used to hold processed file statistics before formatting (default 8)  -f, --format string                      set output format [tabular, wide, json, json2, csv, csv-stream, cloc-yaml, html, html-table, sql, sql-insert, openmetrics] (default "tabular")      --format-multi string                have multiple format output overriding --format [e.g. tabular:stdout,csv:file.csv,json:file.json]      --gen                                identify generated files      --generated-markers strings          string markers in head of generated files (default [do not edit,<auto-generated />])  -h, --help                               help for scc  -i, --include-ext strings                limit to file extensions [comma separated list: e.g. go,java,js]      --include-symlinks                   if set will count symlink files  -l, --languages                          print supported languages and extensions      --large-byte-count int               number of bytes a file can contain before being removed from output (default 1000000)      --large-line-count int               number of lines a file can contain before being removed from output (default 40000)      --min                                identify minified files  -z, --min-gen                            identify minified or generated files      --min-gen-line-length int            number of bytes per average line for file to be considered minified or generated (default 255)      --no-cocomo                          remove COCOMO calculation output  -c, --no-complexity                      skip calculation of code complexity  -d, --no-duplicates                      remove duplicate files from stats and output      --no-gen                             ignore generated files in output (implies --gen)      --no-gitignore                       disables .gitignore file logic      --no-gitmodule                       disables .gitmodules file logic      --no-hborder                         remove horizontal borders between sections      --no-ignore                          disables .ignore file logic      --no-large                           ignore files over certain byte and line size set by large-line-count and large-byte-count      --no-min                             ignore minified files in output (implies --min)      --no-min-gen                         ignore minified or generated files in output (implies --min-gen)      --no-scc-ignore                      disables .sccignore file logic      --no-size                            remove size calculation output  -M, --not-match stringArray              ignore files and directories matching regular expression  -o, --output string                      output filename (default stdout)      --overhead float                     set the overhead multiplier for corporate overhead (facilities, equipment, accounting, etc.) (default 2.4)  -p, --percent                            include percentage values in output      --remap-all string                   inspect every file and remap by checking for a string and remapping the language [e.g. "-*- C++ -*-":"C Header"]      --remap-unknown string               inspect files of unknown type and remap by checking for a string and remapping the language [e.g. "-*- C++ -*-":"C Header"]      --size-unit string                   set size unit [si, binary, mixed, xkcd-kb, xkcd-kelly, xkcd-imaginary, xkcd-intel, xkcd-drive, xkcd-bakers] (default "si")      --sloccount-format                   print a more SLOCCount like COCOMO calculation  -s, --sort string                        column to sort by [files, name, lines, blanks, code, comments, complexity] (default "files")      --sql-project string                 use supplied name as the project identifier for the current run. Only valid with the --format sql or sql-insert option  -t, --trace                              enable trace output (not recommended when processing multiple files)  -u, --uloc                               calculate the number of unique lines of code (ULOC) for the project  -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 redis ───────────────────────────────────────────────────────────────────────────────Language                 Files     Lines   Blanks  Comments     Code Complexity───────────────────────────────────────────────────────────────────────────────C                          437   267,353   31,103    45,998  190,252     48,269JSON                       406    25,392        4         0   25,388          0C Header                   288    48,831    5,648    11,302   31,881      3,097TCL                        215    66,943    7,330     4,651   54,962      3,816Shell                       75     1,626      239       343    1,044        185Python                      34     4,802      694       498    3,610        621Markdown                    26     4,647    1,226         0    3,421          0Autoconf                    22    11,732    1,124     1,420    9,188      1,016Lua                         20       525       69        71      385         89Makefile                    20     1,956      368       170    1,418         85YAML                        20     2,696      147        53    2,496          0MSBuild                     11     1,995        2         0    1,993        160Plain Text                  10     1,773      313         0    1,460          0Ruby                         9       817       73       105      639        123C++                          8       546       85        43      418         43HTML                         5     9,658    2,928        12    6,718          0License                      3        90       17         0       73          0CMake                        2       298       49         5      244         12CSS                          2       107       16         0       91          0Systemd                      2        80        6         0       74          0BASH                         1       143       16         5      122         38Batch                        1        28        2         0       26          3C++ Header                   1         9        1         3        5          0Extensible Styleshe…         1        10        0         0       10          0JavaScript                   1        31        1         0       30          5Module-Definition            1    11,375    2,116         0    9,259        167SVG                          1         1        0         0        1          0Smarty Template              1        44        1         0       43          5m4                           1       951      218        64      669          0───────────────────────────────────────────────────────────────────────────────Total                    1,624   464,459   53,796    64,743  345,920     57,734───────────────────────────────────────────────────────────────────────────────Estimated Cost to Develop (organic) $12,517,562Estimated Schedule Effort (organic) 35.93 monthsEstimated People Required (organic) 30.95───────────────────────────────────────────────────────────────────────────────Processed 16601962 bytes, 16.602 megabytes (SI)───────────────────────────────────────────────────────────────────────────────

Note that you don't have to specify the directory you want to run against. Runningscc will assume you want to run against the current directory.

You can also run against multiple files or directoriesscc directory1 directory2 file1 file2 with the results aggregated in the output.

Sincescc writes to standard output, there are many ways to easily share the results. For example, usingnetcatandone of many pastebins gives a public URL:

$ scc| nc paste.c-net.org 9999https://paste.c-net.org/Example

scc mostly supports .ignore files inside directories that it scans. This is similar to how ripgrep, ag and tokei work. .ignore files are 100% the same as .gitignore files with the same syntax, and as suchscc will ignore files and directories listed in them. You can add .ignore files to ignore things like vendored dependency checked in files and such. The idea is allowing you to add a file or folder to git and have ignored in the count.

It also supports its own ignore file.sccignore if you wantscc to ignore things while having ripgrep, ag, tokei and others support them.

Used inside Intel Nemu Hypervisor to track code changes between revisionshttps://github.com/intel/nemu/blob/topic/virt-x86/tools/cloc-change.sh#L9Appears to also be used inside bothhttp://codescoop.com/https://pinpoint.com/https://github.com/chaoss/grimoirelab-graal

It also is used to count code and guess language types inhttps://searchcode.com/ which makes it one of the most frequently run code counters in the world.

You can also hook scc into your gitlab pipelinehttps://gitlab.com/guided-explorations/ci-cd-plugin-extensions/ci-cd-plugin-extension-scc

Also used by CodeQL#317 and Scalewayhttps://twitter.com/Scaleway/status/1488087029476995074?s=20&t=N2-z6O-ISDdDzULg4o4uVQ

• https://docs.linuxfoundation.org/lfx/insights/v3-beta-version-current/getting-started/landing-page/cocomo-cost-estimation-simplified
• https://openems.io/

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 followingfor if switch while else || && != == if encountered in Java would increment that files complexity by one.

Let's 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 as it only 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 projectscc --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.

As for how it works.

It's my own definition, but tries to be an approximation of cyclomatic complexityhttps://en.wikipedia.org/wiki/Cyclomatic_complexity although done only on a file level.

The reason it's an approximation is that it's calculated almost for free from a CPU point of view (since its a cheap lookup when counting), whereas a real cyclomatic complexity count would need to parse the code. It gives a reasonable guess in practice though even if it fails to identify recursive methods. The goal was never for it to be exact.

In short when scc is looking through what it has identified as code if it notices what are usually branch conditions it will increment a counter.

The conditions it looks for are compiled into the code and you can get an idea for them by looking at the JSON inside the repository. Seehttps://github.com/boyter/scc/blob/master/languages.json#L3869 for an example of what it's looking at for a file that's Java.

The increment happens for each of the matching conditions and produces the number you see.

ULOC stands for Unique Lines of Code and represents the unique lines across languages, files and the project itself. This idea was taken fromhttps://cmcenroe.me/2018/12/14/uloc.html where the calculation is presented using standard Unix toolssort -u *.h *.c | wc -l. This metric isthere to assist with the estimation of complexity within the project. Quoting the source

In my opinion, the number this produces should be a better estimate of the complexity of a project. Compared to SLOC, not only are blank lines discounted, but so are close-brace lines and other repetitive code such as common includes. On the other hand, ULOC counts comments, which require just as much maintenance as the code around them does, while avoiding inflating the result with license headers which appear in every file, for example.

You can obtain the ULOC by supplying the-u or--uloc argument toscc.

It has a corresponding metricDRYness % which is the percentage of ULOC to CLOC orDRYness = ULOC / SLOC. Thehigher the number the more DRY (don't repeat yourself) the project can be considered. In general a higher valuehere is a better as it indicates less duplicated code. The DRYness metric was taken from a comment by minimaxhttps://lobste.rs/s/has9r7/uloc_unique_lines_code

To obtain the DRYness metric you can use the-a or--dryness argument toscc, which will implicitly set--uloc.

Note that there is a performance penalty when calculating the ULOC metrics which can double the runtime.

Running the uloc and DRYness calculations against C code a clone of redis produces an output as follows.

$ scc -a -i c redis ───────────────────────────────────────────────────────────────────────────────Language                 Files     Lines   Blanks  Comments     Code Complexity───────────────────────────────────────────────────────────────────────────────C                          437   267,353   31,103    45,998  190,252     48,269(ULOC)                            149892───────────────────────────────────────────────────────────────────────────────Total                      437   267,353   31,103    45,998  190,252     48,269───────────────────────────────────────────────────────────────────────────────Unique Lines of Code (ULOC)       149892DRYness %                           0.56───────────────────────────────────────────────────────────────────────────────Estimated Cost to Develop (organic)$6,681,762Estimated Schedule Effort (organic) 28.31 monthsEstimated People Required (organic) 20.97───────────────────────────────────────────────────────────────────────────────Processed 9390815 bytes, 9.391 megabytes (SI)───────────────────────────────────────────────────────────────────────────────

Further reading about the ULOC calculation can be found athttps://boyter.org/posts/sloc-cloc-code-new-metic-uloc/

The COCOMO statistics displayed at the bottom of any command line run can be configured as needed.

Estimated Cost to Develop (organic) $664,081Estimated Schedule Effort (organic) 11.772217 monthsEstimated People Required (organic) 5.011633

To change the COCOMO parameters, you can either use one of the default COCOMO models.

scc --cocomo-project-type organicscc --cocomo-project-type semi-detachedscc --cocomo-project-type embedded

You can also supply your own parameters if you are familiar with COCOMO as follows,

scc --cocomo-project-type "custom,1,1,1,1"

See below for details about how the model choices, and the parameters they use.

Organic – A software project is said to be an organic type if the team size required is adequately small, theproblem is well understood and has been solved in the past and also the team members have a nominal experienceregarding the problem.

scc --cocomo-project-type "organic,2.4,1.05,2.5,0.38"

Semi-detached – A software project is said to be a Semi-detached type if the vital characteristics such as team-size,experience, knowledge of the various programming environment lie in between that of organic and Embedded.The projects classified as Semi-Detached are comparatively less familiar and difficult to develop compared tothe organic ones and require more experience and better guidance and creativity. Eg: Compilers ordifferent Embedded Systems can be considered of Semi-Detached type.

scc --cocomo-project-type "semi-detached,3.0,1.12,2.5,0.35"

Embedded – A software project with requiring the highest level of complexity, creativity, and experiencerequirement fall under this category. Such software requires a larger team size than the other two modelsand also the developers need to be sufficiently experienced and creative to develop such complex models.

scc --cocomo-project-type "embedded,3.6,1.20,2.5,0.32"

You can havescc exclude large files from the output.

The option to do so is--no-large which by default will exclude files over 1,000,000 bytes or 40,000 lines.

You can control the size of either value using--large-byte-count or--large-line-count.

For example to exclude files over 1,000 lines and 50kb you could use the following,

scc --no-large --large-byte-count 50000 --large-line-count 1000

You can havescc identify and optionally remove files identified as being minified or generated from the output.

You can do so by enabling the-z flag like soscc -z which will identify any file with an average line byte size >= 255 (by default) as being minified.

Minified files appear like so in the output.

$ scc --no-cocomo -z ./examples/minified/jquery-3.1.1.min.js───────────────────────────────────────────────────────────────────────────────Language                 Files     Lines   Blanks  Comments     Code Complexity───────────────────────────────────────────────────────────────────────────────JavaScript (min)             1         4        0         1        3         17───────────────────────────────────────────────────────────────────────────────Total                        1         4        0         1        3         17───────────────────────────────────────────────────────────────────────────────Processed 86709 bytes, 0.087 megabytes (SI)───────────────────────────────────────────────────────────────────────────────

Minified files are indicated with the text(min) after the language name.

Generated files are indicated with the text(gen) after the language name.

You can control the average line byte size using--min-gen-line-length such asscc -z --min-gen-line-length 1. Please note you need-z as modifying this value does not imply minified detection.

You can exclude minified files from the count totally using the flag--no-min-gen. Files which match the minified check will be excluded from the output.

Some files may not have an extension. They will be checked to see if they are a #! file. If they are then the language will be remapped to thecorrect language. Otherwise, it will not process.

However, you may have the situation where you want to remap such files based on a string inside it. To do so you can use--remap-unknown

 scc --remap-unknown"-*- C++ -*-":"C Header"

The above will inspect any file with no extension looking for the string-*- C++ -*- and if found remap the file to be counted using the C Header rules.You can have multiple remap rules if required,

 scc --remap-unknown"-*- C++ -*-":"C Header","other":"Java"

There is also the--remap-all parameter which will remap all files.

Note that in all cases if the remap rule does not apply normal #! rules will apply.

By defaultscc will output to the console. However, you can produce output in other formats if you require.

The different options aretabular, wide, json, csv, csv-stream, cloc-yaml, html, html-table, sql, sql-insert, openmetrics.

Note that you can writescc output to disk using the-o, --output option. This allows you to specify a file towrite your output to. For examplescc -f html -o output.html will runscc against the current directory, and outputthe results in html to the fileoutput.html.

You can also write to multiple output files, or multiple types to stdout if you want using the--format-multi option. This ismost useful when working in CI/CD systems where you want HTML reports as an artifact while also displaying the counts in stdout.

scc --format-multi"tabular:stdout,html:output.html,csv:output.csv"

The above will run against the current directory, outputting to standard output the default output, as well as writingto output.html and output.csv with the appropriate formats.

This is the default output format when scc is run.

Wide produces some additional information which is the complexity/lines metric. This can be useful when trying toidentify the most complex file inside a project based on the complexity estimate.

JSON produces JSON output. Mostly designed to allowscc to feed into other programs.

Note that this format will give you the byte size of every filescc reads allowing you to get a breakdown of thenumber of bytes processed.

CSV as an option is good for importing into a spreadsheet for analysis.

Note that this format will give you the byte size of every filescc reads allowing you to get a breakdown of thenumber of bytes processed. Also note that CSV respects--by-file and as such will return a summary by default.

csv-stream is an option useful for processing very large repositories where you are likely to run into memory issues. It's output format is 100% the same as CSV.

Note that you should not use this with theformat-multi option as it will always print to standard output, and because of how it works will negate the memory saving it normally gains.savings that this option provides. Note that there is no sort applied with this option.

Is a drop in replacement for cloc using its yaml output option. This is quite often used for passing into otherbuild systems and can help with replacing cloc if required.

$ scc -f cloc-yml processor# https://github.com/boyter/scc/header:  url: https://github.com/boyter/scc/  version: 2.11.0  elapsed_seconds: 0.008  n_files: 21  n_lines: 6562  files_per_second: 2625  lines_per_second: 820250Go:  name: Go  code: 5186  comment: 273  blank: 1103  nFiles: 21SUM:  code: 5186  comment: 273  blank: 1103  nFiles: 21$ cloc --yaml processor      21 text files.      21 unique files.       0 files ignored.---# http://cloc.sourceforge.netheader :  cloc_url           : http://cloc.sourceforge.net  cloc_version       : 1.60  elapsed_seconds    : 0.196972846984863  n_files            : 21  n_lines            : 6562  files_per_second   : 106.613679608407  lines_per_second   : 33314.2364566841Go:  nFiles: 21  blank: 1137  comment: 606  code: 4819SUM:  blank: 1137  code: 4819  comment: 606  nFiles: 21

The HTML output options produce a minimal html report using a table that is either standalonehtml or as just a tablehtml-tablewhich can be injected into your own HTML pages. The only difference between the two is that thehtml option includeshtml head and body tags with minimal styling.

The markup is designed to allow your own custom styles to be applied. An example reportis here to view.

Note that the HTML options follow the command line options, so you can usescc --by-file -f html to produce a report with everyfile and not just the summary.

Note that this format if it has the--by-file option will give you the byte size of every filescc reads allowing you to get a breakdown of thenumber of bytes processed.

The SQL output format "mostly" compatible with cloc's SQL output formathttps://github.com/AlDanial/cloc#sql-

While all queries on the cloc documentation should work as expected, you will not be able to append output fromscc andcloc into the same database. This is because the table format is slightly differentto account for scc including complexity counts and bytes.

The difference betweensql andsql-insert is thatsql will include table creation while the latter will only have the insert commands.

Usage is 100% the same as any otherscc command but sql output will always contain per file details. You can compute totals yourself using SQL, however COCOMO calculations will appear against the metadata table as the columnsestimated_costestimated_schedule_months andestimated_people.

The below will run scc against the current directory, name the output as the project scc and then pipe the output to sqlite to put into the database code.db

scc --format sql --sql-project scc.| sqlite3 code.db

Assuming you then wanted to append another project

scc --format sql-insert --sql-project redis.| sqlite3 code.db

You could then run SQL against the database,

sqlite3 code.db'select project,file,max(nCode) as nL from t                         group by project order by nL desc;'

See the cloc documentation for more examples.

OpenMetrics is a metric reporting format specification extending the Prometheus exposition text format.

The produced output is natively supported byPrometheus andGitLab CI

Note that OpenMetrics respects--by-file and as such will return a summary by default.

The output includes a metadata header containing definitions of the returned metrics:

# TYPE scc_files count# HELP scc_files Number of sourcecode files.# TYPE scc_lines count# UNIT scc_lines lines# HELP scc_lines Number of lines.# TYPE scc_code count# HELP scc_code Number of lines of actual code.# TYPE scc_comments count# HELP scc_comments Number of comments.# TYPE scc_blanks count# HELP scc_blanks Number of blank lines.# TYPE scc_complexity count# HELP scc_complexity Code complexity.# TYPE scc_bytes count# UNIT scc_bytes bytes# HELP scc_bytes Size in bytes.

The header is followed by the metric data in either language summary form:

scc_files{language="Go"} 1scc_lines{language="Go"} 1000scc_code{language="Go"} 1000scc_comments{language="Go"} 1000scc_blanks{language="Go"} 1000scc_complexity{language="Go"} 1000scc_bytes{language="Go"} 1000

or, if--by-file is present, in per file form:

scc_lines{language="Go",file="./bbbb.go"} 1000scc_code{language="Go",file="./bbbb.go"} 1000scc_comments{language="Go",file="./bbbb.go"} 1000scc_blanks{language="Go",file="./bbbb.go"} 1000scc_complexity{language="Go",file="./bbbb.go"} 1000scc_bytes{language="Go",file="./bbbb.go"} 1000

Generallyscc 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. SeeOther 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 LinuxGOGC=-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 48 Core CPU Optimised Digital Ocean Virtual Machine 2024/09/30 all done usinghyperfine.

Seehttps://github.com/boyter/scc/blob/master/benchmark.sh to see how the benchmarks are run.

Benchmark 1: scc valkey  Time (mean ± σ):      28.0 ms ±   1.6 ms    [User: 166.1 ms, System: 55.0 ms]  Range (min … max):    24.7 ms …  31.5 ms    114 runs Benchmark 2: scc -c valkey  Time (mean ± σ):      25.8 ms ±   1.7 ms    [User: 123.7 ms, System: 53.2 ms]  Range (min … max):    23.3 ms …  29.3 ms    114 runs Benchmark 3: tokei valkey  Time (mean ± σ):      63.0 ms ±   3.8 ms    [User: 433.8 ms, System: 244.3 ms]  Range (min … max):    46.7 ms …  67.6 ms    44 runs Benchmark 4: polyglot valkey  Time (mean ± σ):      27.4 ms ±   0.8 ms    [User: 46.5 ms, System: 79.0 ms]  Range (min … max):    25.7 ms …  29.5 ms    108 runs Summary  scc -c valkey ran    1.06 ± 0.08times faster than polyglot valkey    1.08 ± 0.09times faster than scc valkey    2.44 ± 0.22times faster than tokei valkey

Benchmark 1: scc cpython  Time (mean ± σ):      81.9 ms ±   4.2 ms    [User: 789.6 ms, System: 164.6 ms]  Range (min … max):    74.0 ms …  89.6 ms    36 runs Benchmark 2: scc -c cpython  Time (mean ± σ):      75.4 ms ±   4.6 ms    [User: 621.9 ms, System: 152.6 ms]  Range (min … max):    68.4 ms …  84.5 ms    37 runs Benchmark 3: tokei cpython  Time (mean ± σ):     162.1 ms ±   3.4 ms    [User: 1824.0 ms, System: 420.4 ms]  Range (min … max):   156.7 ms … 168.9 ms    18 runs Benchmark 4: polyglot cpython  Time (mean ± σ):      94.2 ms ±   3.0 ms    [User: 210.3 ms, System: 260.3 ms]  Range (min … max):    88.3 ms …  99.4 ms    30 runs Summary  scc -c cpython ran    1.09 ± 0.09times faster than scc cpython    1.25 ± 0.09times faster than polyglot cpython    2.15 ± 0.14times faster than tokei cpython

Benchmark 1: scc linux  Time (mean ± σ):      1.070 s ±  0.036 s    [User: 15.253 s, System: 1.962 s]  Range (min … max):    1.011 s …  1.133 s    10 runs Benchmark 2: scc -c linux  Time (mean ± σ):      1.007 s ±  0.039 s    [User: 9.822 s, System: 1.937 s]  Range (min … max):    0.915 s …  1.043 s    10 runs Benchmark 3: tokei linux  Time (mean ± σ):      1.094 s ±  0.019 s    [User: 19.416 s, System: 11.085 s]  Range (min … max):    1.067 s …  1.135 s    10 runs Benchmark 4: polyglot linux  Time (mean ± σ):      1.387 s ±  0.028 s    [User: 3.775 s, System: 3.212 s]  Range (min … max):    1.359 s …  1.433 s    10 runs Summary  scc -c linux ran    1.06 ± 0.05times faster than scc linux    1.09 ± 0.05times faster than tokei linux    1.38 ± 0.06times faster than polyglot linux

Sourcegraph has gone dark since I last ran these benchmarks hence using a clone taken before this occured.The reason for this is to track what appears to be a performance regression in tokei.

Benchmark 1: scc sourcegraph  Time (mean ± σ):     125.1 ms ±   8.0 ms    [User: 638.1 ms, System: 218.0 ms]  Range (min … max):   116.7 ms … 141.3 ms    24 runs Benchmark 2: scc -c sourcegraph  Time (mean ± σ):     119.8 ms ±   8.3 ms    [User: 554.8 ms, System: 208.6 ms]  Range (min … max):   111.9 ms … 138.4 ms    22 runs Benchmark 3: tokei sourcegraph  Time (mean ± σ):     23.888 s ±  1.416 s    [User: 73.858 s, System: 630.906 s]  Range (min … max):   22.292 s … 27.010 s    10 runs Benchmark 4: polyglot sourcegraph  Time (mean ± σ):     113.3 ms ±   4.1 ms    [User: 237.7 ms, System: 791.8 ms]  Range (min … max):   107.9 ms … 124.3 ms    26 runs Summary  polyglot sourcegraph ran    1.06 ± 0.08times faster than scc -c sourcegraph    1.10 ± 0.08times faster than scc sourcegraph  210.86 ± 14.66times faster than tokei sourcegraph

If you enable duplicate detection expect performance to fall by about 20% inscc.

Performance is tracked for some releases and presented below.

[]The decrease in performance from the 3.3.0 release was due to accurate .gitignore, .ignore and .gitmodule support.Current work is focussed on resolving this.

https://jsfiddle.net/mw21h9va/

Some CI/CD systems which will remain nameless do not work very well with the box-lines used byscc. To support those systems better there is an option--ci which will change the default output to ASCII only.

$ scc --ci main.go-------------------------------------------------------------------------------Language                 Files     Lines   Blanks  Comments     Code Complexity-------------------------------------------------------------------------------Go                           1       272        7         6      259          4-------------------------------------------------------------------------------Total                        1       272        7         6      259          4-------------------------------------------------------------------------------Estimated Cost to Develop $6,539Estimated Schedule Effort 2.268839 monthsEstimated People Required 0.341437-------------------------------------------------------------------------------Processed 5674 bytes, 0.006 megabytes (SI)-------------------------------------------------------------------------------

The--format-multi option is especially useful in CI/CD where you want to get multiple output formats useful for storage or reporting.

If you want to hack away feel free! PR's are accepted. Some things to keep in mind. If you want to change a language definition you need to updatelanguages.json and then rungo generate which will convert it into theprocessor/constants.go file.

For all other changes ensure you run all tests before submitting. You can do so usinggo test ./.... However, for maximum coverage please runtest-all.sh which will rungofmt, unit tests, race detector and then all of the integration tests. All of those must pass to ensure a stable release.

The core part ofscc which is the counting engine is exposed publicly to be integrated into other Go applications. Seehttps://github.com/pinpt/ripsrc for an example of how to do this.

It also powers all of the code calculations displayed inhttps://searchcode.com/ such ashttps://searchcode.com/file/169350674/main.go/ making it one of the more used code counters in the world.

However as a quick start consider the following,

Note that you must pass in the number of bytes in the content in order to ensure it is counted!

package mainimport ("fmt""io/ioutil""github.com/boyter/scc/v3/processor")typestatsProcessorstruct{}func (p*statsProcessor)ProcessLine(job*processor.FileJob,currentLineint64,lineType processor.LineType)bool {switchlineType {caseprocessor.LINE_BLANK:fmt.Println(currentLine,"lineType","BLANK")caseprocessor.LINE_CODE:fmt.Println(currentLine,"lineType","CODE")caseprocessor.LINE_COMMENT:fmt.Println(currentLine,"lineType","COMMENT")  }returntrue}funcmain() {bts,_:=ioutil.ReadFile("somefile.go")t:=&statsProcessor{}filejob:=&processor.FileJob{Filename:"test.go",Language:"Go",Content:bts,Callback:t,Bytes:int64(len(bts)),  }processor.ProcessConstants()// Required to load the language information and need only be done onceprocessor.CountStats(filejob)}

To add or modify a language you will need to edit thelanguages.json file in the root of the project, and then rungo generate to build it into the application. You can thengo install orgo build as normal to produce the binary with your modifications.

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 soscc -v . and look for the messagetoo many open files in the output. If it is there you can rectify it by setting your ulimit to a higher value.

If you are runningscc in a low memory environment < 512 MB of RAM you may need to set--file-gc-count to a lower value such as0 to force the garbage collector to be on at all times.

A sign that this is required will bescc crashing with panic errors.

scc is pretty well tested with many unit, integration and benchmarks to ensure that it is fast and complete.

Packaging as of version v3.1.0 is done throughhttps://goreleaser.com/

Note if you plan to runscc in Alpine containers you will need to build with CGO_ENABLED=0.

See the below Dockerfile as an example on how to achieve this based on this issue#208

FROM golang as scc-getENV GOOS=linux \GOARCH=amd64 \CGO_ENABLED=0ARG VERSIONRUN git clone --branch $VERSION --depth 1 https://github.com/boyter/sccWORKDIR /go/sccRUN go build -ldflags="-s -w"FROM alpineCOPY --from=scc-get /go/scc/scc /bin/ENTRYPOINT ["scc"]

You can usescc to provide badges on your github/bitbucket/gitlab/sr.ht open repositories. For example,The format to do so is,

https://sloc.xyz/PROVIDER/USER/REPO

An example of the badge forscc is included below, and is used on this page.

[![Scc Count Badge](https://sloc.xyz/github/boyter/scc/)](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 includecode, blanks, lines, comments, cocomo, effort and examples of the appearance are included below.

Forcocomo you can also set theavg-wage value similar toscc itself. For example,

https://sloc.xyz/github/boyter/scc/?category=cocomo&avg-wage=1https://sloc.xyz/github/boyter/scc/?category=cocomo&avg-wage=100000

Note that the avg-wage value must be a positive integer otherwise it will revert back to the default value of 56286.

You can also configure the look and feel of the bad using the following parameters,

• ?lower=true will lower the title text, so "Total lines" would be "total lines"he below can control the colours of shadows, fonts and badges
• ?font-color=fff
• ?font-shadow-color=010101
• ?top-shadow-accent-color=bbb
• ?title-bg-color=555
• ?badge-bg-color=4c1

An example of using some of these parameters to produce an admittedly ugly result

NB it may not work for VERY large repositories (has been tested on Apache hadoop/spark without issue).

You can find the source code for badges in the repository athttps://github.com/boyter/scc/blob/master/cmd/badges/main.go

• Github -https://sloc.xyz/github/boyter/scc/
• sr.ht -https://sloc.xyz/sr.ht/~nektro/magnolia-desktop/
• Bitbucket -https://sloc.xyz/bitbucket/boyter/decodingcaptchas
• Gitlab -https://sloc.xyz/gitlab/esr/loccount

List of supported languages. The master version ofscc supports 322 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 ofscc supports runscc --languages

Click here to view all languages supported by master

Please use the following bibtex entry to cite scc in a publication:

@software{scc,  author       = {Ben Boyter},  title        = {scc: v3.5.0},  month        = ...,  year         = ...,  publisher    = {...},  version      = {v3.5.0},  doi          = {...},  url          = {...}}

You may need to check the release pagehttps://github.com/boyter/scc/releases to find the correct year and month for the release you are using.

• Update version
• Push code with release number
• Tag off
• Release via goreleaser
• Update dockerfile