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De Lorenzo","email":"michael@delorenzodesign.com"},"homepage":"https://github.com/michaeldelorenzo/keyword-extractor","keywords":["text","keyword","search","extract"],"repository":{"url":"git+https://github.com/michaeldelorenzo/keyword-extractor.git","type":"git"},"description":"Module for creating a keyword array from a string and excluding stop words.","contributors":[{"url":"http://www.mistersanz.com","name":"Marcos Sanz","email":"marcossanzlatorre@gmail.com"},{"url":"https://github.com/d-oliveros","name":"d-oliveros"},{"url":"https://github.com/ajduke","name":"Abhijeet Sutar","email":"ajduke@about.me"},{"url":"https://github.com/janvde","name":"janvde"},{"url":"https://github.com/AlexGustafsson","name":"Alex Gustafsson"},{"url":"https://github.com/circlehddev","name":"CircleHD Devs"},{"url":"https://github.com/otacke","name":"Oliver Tacke"}],"maintainers":[{"name":"mikedelorenzo","email":"michael@delorenzodesign.com"}],"readme":"# Keyword Extractor\n\n[![Tests Status](https://github.com/michaeldelorenzo/keyword-extractor/workflows/test/badge.svg)](https://github.com/michaeldelorenzo/keyword-extractor/actions)\n\nA simple [NPM package](https://npmjs.org/package/keyword-extractor) for extracting _keywords_ from a string by\nremoving stopwords.\n\n## Installation\n\n```sh\n$ npm install keyword-extractor\n```\n\n## Running tests\n\nTo run the test suite, first install the development dependencies by running the following command within the package's\ndirectory.\n\n```sh\n$ npm install\n```\n\nTo execute the package's tests, run:\n\n``` sh\n$ make test\n```\n\n## Usage of the Module\n\n```javascript\n//  include the Keyword Extractor\nconst keyword_extractor = require(\"keyword-extractor\");\n\n//  Opening sentence to NY Times Article at\n/*\nhttp://www.nytimes.com/2013/09/10/world/middleeast/\nsurprise-russian-proposal-catches-obama-between-putin-and-house-republicans.html\n*/\nconst sentence =\n\"President Obama woke up Monday facing a Congressional defeat that many in both parties believed could hobble his presidency.\"\n\n//  Extract the keywords\nconst extraction_result =\nkeyword_extractor.extract(sentence,{\n    language:\"english\",\n    remove_digits: true,\n    return_changed_case:true,\n    remove_duplicates: false\n\n});\n\n/*\n  extraction result is:\n\n  [\n        \"president\",\n        \"obama\",\n        \"woke\",\n        \"monday\",\n        \"facing\",\n        \"congressional\",\n        \"defeat\",\n        \"parties\",\n        \"believed\",\n        \"hobble\",\n        \"presidency\"\n    ]\n*/\n```\n\nThe module can also be imported with ES module syntax, e.g. in Next.js apps or other ESM-based projects:\n\n```javascript\nimport keyword_extractor from \"keyword-extractor\";\n// or, using named imports:\n// import { extract, getStopwords, supported_language_codes } from \"keyword-extractor\";\n\nconst extraction_result = keyword_extractor.extract(sentence, {\n    language: \"english\",\n    remove_digits: true,\n    return_changed_case: true,\n    remove_duplicates: false\n});\n```\n\n### TypeScript\n\nThis package ships its own type declarations, so no `@types` package is needed. Usage is the same, but with\n`import`/typed options:\n\n```typescript\nimport keyword_extractor from \"keyword-extractor\";\n\nconst sentence = \"President Obama woke up Monday facing a Congressional defeat.\";\n\nconst extraction_result: string[] = keyword_extractor.extract(sentence, {\n    language: \"english\",\n    remove_digits: true,\n    return_changed_case: true,\n    remove_duplicates: false\n});\n```\n\n### Options Parameters\n\nThe second argument of the _extract_ method is an Object of configuration/processing settings for the extraction.\n\nParameter Name | Description | Permitted Values\n---------------|-------------|-----------------\nlanguage       | The stopwords list to use. ISO 639-1 codes and verbose names | _ar_, _cs_, _da_, _de_, _en_, _es_, _fa_, _fr_, _gl_, _it_, _ko_, _nl_, _pl_, _pt_, _ro_, _ru_, _sv_, _tr_, _vi_, _arabic_, _czech_, _danish_, _dutch_, _english_, _french_, _galician_,_german_, _italian_, _korean_, _persian_, _polish_, _portuguese_, _romanian_, _russian_,_spanish_, _swedish_, _turkish_, _vietnam_\nremove_digits | Removes all digits from the results if set to true (can handle Arabic and Perisan digits too) | _true_ or _false_\nreturn_changed_case | The case of the extracted keywords. Setting the value to _true_ will return the results all lower-cased, if _false_ the results will be in the original case. | _true_ or _false_\nreturn_chained_words | Instead of returning each word separately, join the words that were originally together. Setting the value to _true_ will join the words, if _false_ the results will be splitted on each array element. | _true_ or _false_\nremove_duplicates | Removes the duplicate keywords | _true_ , _false_ (defaults to _false_ )\nreturn_max_ngrams | Returns keywords that are ngrams with size 0-_integer_ | _integer_ , _false_ (defaults to _false_ )\nstopwords_regex | Removes any word matching one of the given regular expressions, in addition to the language's stopwords list. Useful for filtering out patterns that aren't in a fixed word list, such as units (`10lbs`, `10Kg`), times (`6pm`), or ranges (`1-100`) | Array of `RegExp` (defaults to _[]_ )\n\nEach pattern is tested against both the lowercased and original-case forms of a word, so patterns work\nwhether or not they include the `i` flag.\n\n#### Removing words with `stopwords_regex`\n\n```javascript\nconst extraction_result = keyword_extractor.extract(\"He weighed 10lbs at birth and grew to 10Kg, waking at 6pm daily.\", {\n    language: \"english\",\n    stopwords_regex: [/^\\d+[a-z]+$/i]\n});\n\n//  extraction_result is [\"weighed\", \"birth\", \"grew\", \"waking\", \"daily\"]\n```\n\n\n## Releases\n\nThis package is released to npm automatically using [semantic-release](https://semantic-release.gitbook.io/semantic-release/).\nEvery merge to `main` is analyzed and, if it contains a releasable change, published under the appropriate version bump.\n\nVersioning is driven entirely by commit messages (and, by extension, pull request titles — PRs are typically squash-merged,\nso the PR title becomes the commit message on `main`). Pull request titles must follow the\n[Conventional Commits](https://www.conventionalcommits.org/) specification and are checked automatically by CI:\n\n```\n<type>[optional scope]: <description>\n```\n\nCommon types and the version bump they trigger:\n\nType       | Description                                | Release\n-----------|---------------------------------------------|--------\n`fix`, `perf`, `revert` | A bug fix, performance fix, or revert of a previous commit | Patch\n`feat`     | A new feature                                | Minor\n`refactor`, `docs`, `style`, `test`, `build`, `ci`, `chore` | No user-facing change | None\nAny type with a `BREAKING CHANGE:` footer or a `!` after the type/scope (e.g. `feat!:`) | Breaking API change | Major\n\nRelease notes for each version are published on the [GitHub Releases page](https://github.com/michaeldelorenzo/keyword-extractor/releases) —\nthere's no `CHANGELOG.md` committed to the repo, since `main` is a protected branch and the release automation can't push commits to it.\n\n## Credits\n\nThe initial stopwords lists are taken from the following sources:\n\n- English [http://www.ai.mit.edu/projects/jmlr/papers/volume5/lewis04a/a11-smart-stop-list/english.stop]\n- Spanish [https://stop-words.googlecode.com/svn/trunk/stop-words/stop-words/stop-words-spanish.txt]\n- Turkish [https://github.com/ahmetax/trstop]\n","readmeFilename":"README.md","users":{"ooj":true,"ajduke":true,"beytek":true,"cashsun":true,"nlokare":true,"tnoetzel":true,"christophera":true,"mikedelorenzo":true,"parkerproject":true}}