How to use the command 'scc' (with examples)

scc is a powerful tool written in Go, designed primarily for counting lines of code in a directory or set of directories. Unlike simple line counters, scc offers a nuanced breakdown of lines into logical, blank, and comment categories, displays code complexity, supports a myriad of programming languages, and allows for customization of output formats. This makes it an invaluable asset for developers and teams aiming to assess the scale, composition, and complexity of their codebases efficiently.

Print lines of code in the current directory

Code:

scc

Motivation:

By running scc without any additional arguments, users quickly obtain a summary of the number of lines in code, including code, comments, and blank lines, within the current working directory. This offers an immediate snapshot of the codebase’s size in the current project, a crucial aspect for understanding project scale or comparing it across different time points or projects.

Explanation:

• The command scc examines all the files within the current directory and its subdirectories, tallying lines while distinguishing between code, comments, and blank lines. Its default behavior is to show a summarized scorecard, facilitating an understanding of the project metrics at a glance.

Example output:

──────────────────────────────────────────────────────────
 Language      Files    Lines    Blank   Comment      Code
──────────────────────────────────────────────────────────
 Go               12     2904      300       145      2459
 JavaScript        9     2220      180       200      1840
 Markdown          2      500      100         0       400
──────────────────────────────────────────────────────────
 Total            23     5624      580       345      4699
──────────────────────────────────────────────────────────

Print lines of code in the target directory

Code:

scc path/to/directory

Motivation:

When working with multiple projects, each situated in distinct directories, developers often need code metrics for a specific target directory rather than their present working directory. This command facilitates that by allowing the user to specify the path to any directory of interest, computing its code metrics efficiently.

Explanation:

• By appending path/to/directory, the user directs scc to process this specific directory rather than the current directory. This provides flexibility in monitoring various parts of one’s filesystem, beneficial for managing larger codebases split across multiple folders.

Example output:

──────────────────────────────────────────────────────────
 Language      Files    Lines    Blank   Comment      Code
──────────────────────────────────────────────────────────
 Python            5     4300      500       300      3500
 YAML              2      150       30        10       110
 Dockerfile        1       50        5         5        40
──────────────────────────────────────────────────────────
 Total             8     4500      535       315      3650
──────────────────────────────────────────────────────────

Display output for every file

Code:

scc --by-file

Motivation:

In some scenarios, especially while trying to identify problem files—for example, files that may need refactoring due to their size or complexity—it’s advantageous to see metrics per file rather than just summarized data. This feature allows developers to drill down to the line-by-line statistics of each file individually.

Explanation:

• The --by-file argument instructs scc to list each file separately rather than aggregating data by language. This detailed output helps in locating large or complex files within the codebase, enabling more informed decision-making regarding code maintenance.

Example output:

────────────────────────────────────────────────────────────
 Language      File                          Lines    Blank  Comment  Code
────────────────────────────────────────────────────────────
 Go           main.go                          300       30        5   265
 Go           utils.go                         150       15        3   132
 JavaScript   app.js                           500       50       60   390
 JavaScript   config.js                        220       20       40   160
────────────────────────────────────────────────────────────

Display output using a specific output format

Code:

scc --format json

Motivation:

Different stakeholders may require data in different formats, especially when integrating scc with other tools. To automate reporting or for ease of parsing, output formats such as json or csv are quite useful. This command specifies the desired format, enhancing interoperability with other data processing tools or reporting systems.

Explanation:

• --format json directs scc to output its findings in JSON format, which is easily digestible by many programming languages and third-party tools. This is especially practical when integrating scc analytics into dashboards or when performing automated processing in scripts.

Example output:

[
  {
    "Language": "Go",
    "Files": 12,
    "Lines": 2904,
    "Blank": 300,
    "Comment": 145,
    "Code": 2459
  },
  {
    "Language": "JavaScript",
    "Files": 9,
    "Lines": 2220,
    "Blank": 180,
    "Comment": 200,
    "Code": 1840
  }
]

Only count files with specific file extensions

Code:

scc --include-ext go,java,js

Motivation:

During specialized code audits or for analysis purposes, developers or teams may be interested only in particular programming languages, perhaps for a focused refactor or to assess productivity across different languages used in a project. This command enables filtering of files by their extensions, focusing on the relevant parts of the codebase.

Explanation:

• The --include-ext go,java,js argument filters the files scc analyzes to only those with the specified extensions. This allows users to hone in on particular segments of the codebase, ensuring analysis is targeted and relevant.

Example output:

────────────────────────────────────────────────────────────
 Language      Files    Lines    Blank   Comment      Code
────────────────────────────────────────────────────────────
 Go               12     2904      300       145      2459
 Java              8     1700      170       120      1410
 JavaScript        7     1800      150       175      1475
────────────────────────────────────────────────────────────
 Total            27     6404      620       440      5344
────────────────────────────────────────────────────────────

Exclude directories from being counted

Code:

scc --exclude-dir .git,.hg

Motivation:

Large projects often contain directory structures, such as version control directories, which introduce noise in code analysis. Counting these might inflate the perceived size of a codebase or distort the understanding of code layout and complexity. This command is essential for obtaining a more accurate representation of only the relevant code content.

Explanation:

• The --exclude-dir .git,.hg argument instructs scc to ignore directories that are typically hidden system files or version control repositories. By excluding such directories, the user ensures that only the pertinent aspects of the codebase are included in the analysis.

Example output:

────────────────────────────────────────────────────────────
 Language      Files    Lines    Blank   Comment      Code
────────────────────────────────────────────────────────────
 Go               12     2780      290       142      2348
 Python           10     3200      400       320      2480
────────────────────────────────────────────────────────────
 Total            22     5980      690       462      4828
────────────────────────────────────────────────────────────

Display output and sort by column

Code:

scc --sort code

Motivation:

When code metrics are obtained, sorting criteria can be crucial for data interpretation. For instance, sorting by code lines can highlight the largest sources of code directly. This command makes it easier for users to prioritize certain analyses or operations based on their immediate needs.

Explanation:

• The --sort code argument reorganizes the scc output so that it orders entries in terms of code lines. It facilitates easy identification and comparison of the segments of the codebase contributing most significantly to its overall lines of code.

Example output:

────────────────────────────────────────────────────────────
 Language      Files    Lines    Blank   Comment      Code
────────────────────────────────────────────────────────────
 Go               12     2904      300       145      2459
 JavaScript        9     2220      180       200      1840
 TypeScript        4     1150      100        85       965
────────────────────────────────────────────────────────────

Display help

Code:

scc -h

Motivation:

Tools like scc come with a vast array of options and configurations. New users or those needing a quick refresher can greatly benefit from an accessible help prompt that succinctly documents all available options and basic usage patterns, essential for maximizing the tool’s capabilities.

Explanation:

• The -h flag opens the help documentation directly within the terminal. It encapsulates a summary of commands and options, and is an efficient starting point for learning how to utilize scc thoroughly.

Example output:

Usage of scc:
  -by-file
    Display output for every file
  -format string
    Output format: tabular|wide|json|csv|cloc-yaml|html|html-table (default "tabular")
  ...

Conclusion:

The scc command is a versatile tool that significantly empowers developers and development teams to analyze and understand their codebases at both macro and micro levels. Through its diverse functionalities, such as targeted path analysis, file extension filtering, output customization, and directory exclusion, scc provides comprehensive insights tailored to specific project needs. Whether for high-level project overviews or digging into individual files, scc offers the features needed to maintain and elevate code development practices.