Mac source code line counter

The --exclude flag has the same semantics as. By default tokei sorts alphabetically by language name, however using --sort tokei can also sort by any of the columns. By default tokei only outputs the total of the languages, and using --files flag tokei can also output individual file statistics. Tokei normally outputs into a nice human readable format designed for terminals.

Xcode: How to get total lines of code in your Swift project

There is also using the --output option various other formats that are more useful for bringing the data into another program. Note: This version of tokei was compiled without any serialization formats, to enable serialization, reinstall tokei with the features flag. Tokei can also take in the outputted formats added in the previous results to it's current run. Tokei can take either a path to a file, the format passed in as a value to the option, or from stdin.

Tokei has support for badges. For example. By default the badge will show the repo's LoC Lines of Code , you can also specify for it to show a different category, by using the? It can be either code , blanks , files , lines , comments , Example show total lines:. The server code hosted on tokei. If there is a language that you want added, feel free to submit a pull request with the following information.

If you're unsure have a look at languages.

Source Code Counter for Mac OS X

This is likely due to gcc generating. Until the D people decide on a different file extension, you can always exclude. The canonical source of this repo is hosted on GitHub. If you have a GitHub account, please make your issues, and pull requests there. Skip to content. Dismiss Join GitHub today GitHub is home to over 36 million developers working together to host and review code, manage projects, and build software together.

Sign up. A program that allows you to count your code, quickly.

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Feb 22, Updated v8. Aug 25, Today, the most commonly used computer languages allow a lot more leeway for formatting. Text lines are no longer limited to 80 or 96 columns, and one line of text no longer necessarily corresponds to one line of code. SLOC measures are somewhat controversial, particularly in the way that they are sometimes misused.

Experiments have repeatedly confirmed that effort is highly correlated with SLOC [ citation needed ] , that is, programs with larger SLOC values take more time to develop. Thus, SLOC can be effective in estimating effort. However, functionality is less well correlated with SLOC: skilled developers may be able to develop the same functionality with far less code, so one program with fewer SLOC may exhibit more functionality than another similar program. Counting SLOC as productivity measure has its caveats, since a developer can develop only a few lines and yet be far more productive in terms of functionality than a developer who ends up creating more lines and generally spending more effort.

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Good developers may merge multiple code modules into a single module, improving the system yet appearing to have negative productivity because they remove code. Also, especially skilled developers tend to be assigned the most difficult tasks, and thus may sometimes appear less "productive" than other developers on a task by this measure.

Furthermore, inexperienced developers often resort to code duplication , which is highly discouraged as it is more bug-prone and costly to maintain, but it results in higher SLOC. SLOC counting exhibits further accuracy issues at comparing programs written in different languages unless adjustment factors are applied to normalize languages.

Various computer languages balance brevity and clarity in different ways; as an extreme example, most assembly languages would require hundreds of lines of code to perform the same task as a few characters in APL. The following example shows a comparison of a "hello world" program written in C , and the same program written in COBOL - a language known for being particularly verbose. Another increasingly common problem in comparing SLOC metrics is the difference between auto-generated and hand-written code. Modern software tools often have the capability to auto-generate enormous amounts of code with a few clicks of a mouse.

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For instance, graphical user interface builders automatically generate all the source code for a graphical control elements simply by dragging an icon onto a workspace. The work involved in creating this code cannot reasonably be compared to the work necessary to write a device driver, for instance. By the same token, a hand-coded custom GUI class could easily be more demanding than a simple device driver; hence the shortcoming of this metric. While these models have shown good predictive power, they are only as good as the estimates particularly the SLOC estimates fed to them. Many [2] have advocated the use of function points instead of SLOC as a measure of functionality, but since function points are highly correlated to SLOC and cannot be automatically measured this is not a universally held view.

David A. Later runs of the tools used report that the following release of Debian had million SLOC, and as of year [update] , the newest release is going to include over million SLOC. How big a project is it? Oh, it's sort of a 10K-LOC project. This is a 20K-LOCer. And this is 50K-LOCs. And IBM wanted to sort of make it the religion about how we got paid. How many K-LOCs did you do?

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And we kept trying to convince them — hey, if we have — a developer's got a good idea and he can get something done in 4K-LOCs instead of 20K-LOCs, should we make less money? Because he's made something smaller and faster, less K-LOC. Anyway, that always makes my back just crinkle up at the thought of the whole thing. From Wikipedia, the free encyclopedia. This article has multiple issues. Please help improve it or discuss these issues on the talk page. Learn how and when to remove these template messages. This article's lead section does not adequately summarize key points of its contents.

Please consider expanding the lead to provide an accessible overview of all important aspects of the article. Please discuss this issue on the article's talk page.

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