cld vs franc
Language Detection Libraries
cldfranc

Language Detection Libraries

Language detection libraries are essential tools in web development that enable applications to automatically identify the language of a given text. This functionality is crucial for creating multilingual applications, enhancing user experience by providing content in the user's preferred language, and improving accessibility. Both 'cld' and 'franc' serve this purpose but differ in their methodologies, accuracy, and use cases, making them suitable for different scenarios in language processing.

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cld0338109 MB13a year ago-
franc04,401272 kB52 years agoMIT

Feature Comparison: cld vs franc

Accuracy

  • cld:

    'cld' is known for its high accuracy in detecting languages, especially for short snippets of text. It utilizes advanced algorithms and a large dataset, making it reliable for applications that require precise language identification.

  • franc:

    While 'franc' is also accurate, it shines particularly with longer texts. Its detection algorithm is designed to analyze text patterns, which can sometimes lead to better results with more substantial content.

Performance

  • cld:

    'cld' is optimized for speed, making it ideal for applications that require real-time language detection without significant delays. Its performance is particularly beneficial in high-traffic environments where quick responses are necessary.

  • franc:

    'franc' is lightweight and also performs well, but it may not be as fast as 'cld' in scenarios with very short texts. However, it compensates with a more straightforward implementation and ease of use.

Language Support

  • cld:

    'cld' supports a wide variety of languages, including many dialects, which makes it suitable for global applications that need to cater to diverse user bases.

  • franc:

    'franc' supports a comprehensive list of languages as well, but it may not cover as many dialects as 'cld'. It is still a solid choice for most common languages.

Ease of Use

  • cld:

    'cld' has a more complex setup process due to its extensive features, which may require additional configuration for optimal performance.

  • franc:

    'franc' is designed to be user-friendly with a simple API, making it easy to integrate into projects without extensive setup.

Customization

  • cld:

    'cld' offers limited customization options, focusing more on out-of-the-box accuracy and performance rather than user-defined parameters.

  • franc:

    'franc' allows for more customization, enabling developers to tweak the detection process according to specific project needs, which can be beneficial in specialized applications.

How to Choose: cld vs franc

  • cld:

    Choose 'cld' if you need a library that is highly accurate and supports a wide range of languages, particularly for short texts. It is based on Google's Compact Language Detector and is optimized for performance, making it suitable for applications that require fast language detection in real-time.

  • franc:

    Choose 'franc' if you prefer a library that is lightweight and offers a straightforward API for language detection. It is particularly effective for longer texts and provides a broader range of language support. 'franc' is also more customizable, allowing for easier integration into various projects.

README for cld

node-cld

*NIX Build Status Windows Build Status Dependencies NPM version

Stand With Ukraine

Language detection for Javascript. Based on the CLD2 (Compact Language Detector) library from Google.

Highly optimized for space and speed. Runs about 10x faster than other libraries. Detects over 160 languages. Full test coverage. Runs on Linux, OS X, and Windows.

Installation

$ npm install cld

Linux users, make sure you have g++ >= 4.8. If this is not an option, you should be able to install node-cld 2.4.4 even with an older g++ build.

Examples

Simple

const cld = require('cld');

// As a promise
cld.detect('This is a language recognition example').then((result) => {
  console.log(result);
});

// In an async function
async function testCld() {
  const result = await cld.detect('This is a language recognition example');
  console.log(result);
}

Advanced

const cld = require('cld');
const text     = 'Това е пример за разпознаване на Български език';
const options  = {
  isHTML       : false,
  languageHint : 'BULGARIAN',
  encodingHint : 'ISO_8859_5',
  tldHint      : 'bg',
  httpHint     : 'bg'
};

// As a promise
cld.detect(text, options).then((result) => {
  console.log(result);
});

// In an async function
async function testCld() {
  const result = await cld.detect(text, options);
  console.log(result);
}

Legacy

Detect can be called leveraging the node callback pattern. If options are provided, the third parameter should be the callback.

const cld = require('cld');

cld.detect('This is a language recognition example', (err, result) => {
  console.log(result);
});

Options

isHTML

Set to true if the string contains HTML tags

languageHint

Pass a LANGUAGES key or value as a hint

encodingHint

Pass an ENCODINGS value as a hint

tldHint

Pass top level domain as a hint

httpHint

Pass an HTTP "Content-Encoding" value as a hint

bestEffort

Set to true to give best-effort answer, instead of UNKNOWN_LANGUAGE. May be useful for short text if the caller prefers an approximate answer over none.

Warning

Once the module has been installed, the underlying C sources will remain in the deps/cld folder and continue to occupy considerable space. This is because they will be required if you ever need to run npm rebuild. If you are under severe constraints you can delete this folder and reclam >100M

Copyright

Copyright 2011-2015, Blagovest Dachev.

License

Apache 2