@alextanhongpin/stringcase v1.3.0

@alextanhongpin/stringcase

A package to auto-detect lettercase, and converts to different format.

Installation

$ npm i @alextanhongpin/stringcase

Usage

const assert = require("assert");
const {
  stringCase,
  StringCase,
  CamelCase
} = require("@alextanhongpin/stringcase");

// Factory method, produces a class instance that extends StringCase.
// Can be either CamelCase, SnakeCase, PascalCase, KebabCase,
// UpperCase, LowerCase or UnknownCase.
const greeting = stringCase("helloWorld");

assert(greeting instanceof StringCase);
assert(greeting instanceof CamelCase);
assert.equal("helloWorld", greeting.camel);
assert.equal("HelloWorld", greeting.pascal);
assert.equal("hello-world", greeting.kebab);
assert.equal("hello_world", greeting.snake);

Use Cases

• detecting the difference type of cases allows you to predict what language is being used, e.g. snake case is most likely SQL or Python
• converting between different cases, useful for code generation, where a user just provide a file name,e E.g. user-service, and UserService can be generated
• counting occurances of a particular case to detect trends, if a lot of text has underscore, the text is most likely related to tech article, if camel case then JS code snippets
• finding wrong case, e.g. if the code snippet case should only be snake case, but a camel case is detected
• normalizing cases, say we are extracting headers from CSV and we want to dynamically generate field names (or compare to existing ones for validation), we can convert all to camel case
• slugifying string, creating enums out of strings dynamically. There are better libraries for this, but if all you need is to generate enums from dynamic fields, e.g. When user provide an input string for status order delivered, we can convert it to snake case and upper case it, so that it becomes ORDER_DELIVERED before storing it in the database. Note: you can write a postgres user defined function to achieve the same. Note that this approach assumes that the language used is only English, and there are no localisation involved.