Transforms casing and spacing of a string
npm install transform-case
Here is the case and separation transformer that
transliterates diacriticals and ligatures
when your texts are in any Latin script.
Install the package as npm package. Provided are
a umd-formatted file in the dist folder to require or just read
and an es-module in the module folder to import.
A human text can be transformed to a systematic phrase like this:
``js`
transformCase('A sentence, text for humans.').camelCase()
These will render:
`js
const textIntake = transformCase('A sentence, text for humans.')
textIntake.camelCase() // ==> 'aSentenceTextForHumans'
textIntake.pascalCase() // ==> 'ASentenceTextForHumans'
textIntake.dotCase() // ==> 'a.sentence.text.for.humans'
textIntake.paramCase() // ==> 'a-sentence-text-for-humans'
textIntake.pathCase() // ==> 'a/sentence/text/for/humans'
textIntake.searchCase() // ==> 'a+sentence+text+for+humans'
textIntake.snakeCase() // ==> 'a_sentence_text_for_humans'
textIntake.spaceCase() // ==> 'a sentence text for humans'
textIntake.constantCase()// ==> 'THIS_SENTENCE_TEXT_FOR_HUMANS'
textIntake.headerCase() // ==> 'This-Sentence-Text-For-Humans'
`
A systematic text can be transformed to a human phrase like this:
`js
const textIntake = transformCase('camelCasedInput')
textIntake.humanSentence() // ==> 'Camel cased input'
const textIntake2 = transformCase(
'snake_cased_input', {delimitInput: '_'}
)
textIntake2.humanTitle() // ==> 'Snake Cased Input'
`
With a second argument, an options object can be passed:
{
delimit: [word-or-regex1, word-or-regex2, ...],
preserve: [word-or-regex1, word-or-regex2, ...],
}
delimit: {Array}
keeps a letter-combination or a regular expression match
as a delimited word,
the word will be processed according to the pattern
preserve: {Array}
keeps a letter-combination or a regular expression match
as a delimited word and protects the case
Options for pure alphanumeric input
delimitLetterNumber: {Boolean}
delimit when a letter is followed by a number (default: true)
delimitLowerUpper: {Boolean}
delimit when a lowercase is followed by a uppercase (default: true)
delimitNumberLetter: {Boolean}
delimit when a number is followed by a letter (default: true)
delimitUpperLower: {Boolean}
delimit when a uppercase is followed by a lowercase (default: false)
delimitUpperUpperLower: {Boolean}
delimit when a uppercase is followed by a uppercase plus lowercase (default: true)
.../transform-case/demo/demo.html
.../transform-case/demo/play.html
This module has two steps, an intake and a render step.
The intake step
deduplicates whitespace in a space character,
removes control characters,
finds a delimiter,
isolates delimit and preserve options
and ends with an array of words.
We then have an object with collected data and a number of transform patterns to choose from.
`js``
{
_orgin {
input (string),
isAlphaNumeric (boolean),
normalised (string),
revised (string)
}
options {
(see above)
}
_phrase (delimited string),
words (string[]),
...the transformation functions
}
The render step is merely choosing a pattern to apply to the array of words.
There are three groups of similar patterns:
* Cap-marked words (camelCase, pascalCase)
* Human, linguistic (humanSentence, humanTitle)
* Delimited lowercase (dotCase, paramCase, etcetera)
Apart from the human group, in all patterns
punctuation is stripped,
diacritics are stripped,
ligatures are decomposed