languagedetect vs franc vs cld
Language Detection Libraries Comparison
Search packages..
1 Year
languagedetectfranccld
What's Language Detection Libraries?

Language detection libraries are tools designed to identify the language of a given text input. They utilize various algorithms and datasets to analyze the text and provide a probable language match. These libraries are essential for applications that need to process multilingual content, enhance user experience through localization, or filter content based on language. Each library has its own strengths, weaknesses, and specific use cases, making it important to choose the right one based on project requirements.

Package Weekly Downloads Trend
Github Stars Ranking
Stat Detail
Package
Downloads
Stars
Size
Issues
Publish
License
languagedetect38,097400-35 years ago-
franc34,4344,205272 kB5a year agoMIT
cld12,125322109 MB156 months ago-
Feature Comparison: languagedetect vs franc vs cld

Accuracy

  • languagedetect:

    LanguageDetect is relatively accurate but may not perform as well as CLD or Franc in certain scenarios. It is best suited for longer texts, as shorter inputs can lead to less reliable results. Its simplicity makes it easy to use, but accuracy can vary depending on the text.

  • franc:

    Franc offers a high level of accuracy across a wide range of languages, making it suitable for applications that require precise language identification. It uses statistical models and can detect languages even in short snippets of text, providing reliable results in most cases.

  • cld:

    CLD (Compact Language Detector) is known for its high accuracy in detecting languages, especially for short texts. It uses n-gram analysis and has been trained on a diverse dataset, making it effective for a variety of languages, though it may struggle with very short or ambiguous texts.

Performance

  • languagedetect:

    LanguageDetect is lightweight and performs well for basic tasks, but it may not be as fast as CLD in high-load scenarios. Its performance is adequate for small projects but might lag behind in larger applications.

  • franc:

    Franc is generally slower than CLD but offers a more thorough analysis, which can be beneficial for applications where accuracy is prioritized over speed. It may not be the best choice for real-time applications due to its performance overhead.

  • cld:

    CLD is optimized for performance, making it one of the fastest language detection libraries available. It is designed to handle real-time applications and can process text quickly, which is essential for web applications that require immediate feedback.

Language Support

  • languagedetect:

    LanguageDetect supports a decent number of languages but is not as extensive as Franc. It is suitable for basic use cases but may not cover all languages required for more complex applications.

  • franc:

    Franc supports over 400 languages, making it one of the most comprehensive libraries available. This extensive language support is beneficial for applications that need to handle diverse linguistic content.

  • cld:

    CLD supports a wide range of languages, including many less commonly spoken ones. It is particularly effective for detecting languages in the Latin script, but its performance may vary with languages that have different scripts.

Ease of Use

  • languagedetect:

    LanguageDetect is very easy to use, with a simple API that allows for quick integration into projects. Its lightweight nature makes it an appealing choice for developers looking for a straightforward solution.

  • franc:

    Franc has a slightly steeper learning curve due to its more complex configuration options, but it is still user-friendly. Developers may need to spend some time understanding its API to fully leverage its capabilities.

  • cld:

    CLD is straightforward to integrate and use, with a simple API that allows developers to quickly implement language detection in their applications. Its performance and accuracy make it a popular choice for many developers.

Community and Maintenance

  • languagedetect:

    LanguageDetect has a smaller community compared to CLD and Franc, which may affect its long-term maintenance and support. While it is functional, developers should consider the potential for slower updates and community engagement.

  • franc:

    Franc is also well-maintained, with a growing community of users contributing to its development. Regular updates help keep the library relevant and effective in detecting new languages and dialects.

  • cld:

    CLD is actively maintained and has a strong community backing, which ensures regular updates and improvements. This active support is crucial for developers who rely on the library for ongoing projects.

How to Choose: languagedetect vs franc vs cld
  • languagedetect:

    Choose LanguageDetect if you prefer a lightweight library that is easy to integrate and use, especially for smaller projects or when you need a simple solution for basic language detection tasks.

  • franc:

    Choose Franc if you require a more comprehensive language detection solution that supports a large number of languages and provides a high level of accuracy. It is suitable for applications where precision is critical, such as content management systems or data analysis tools.

  • cld:

    Choose CLD if you need a fast and efficient language detection library that is optimized for performance and can handle a wide range of languages. It is particularly useful for applications requiring quick responses, such as web applications or real-time systems.

Similar Npm Packages to languagedetect

languagedetect is a JavaScript library designed for language detection in text. It utilizes a statistical approach to identify the language of a given string based on a predefined set of languages. This library is particularly useful for applications that require language identification, such as chat applications, content management systems, or any platform that supports multiple languages. Its lightweight nature and ease of use make it a popular choice among developers looking to implement language detection features quickly.

While languagedetect is a solid option, there are alternatives available that also provide language detection capabilities. Here are a couple of notable alternatives:

  • cld (Compact Language Detector) is a library that offers language detection capabilities based on Google's language detection algorithm. It is designed to be fast and efficient, making it suitable for real-time applications. cld supports a wide range of languages and is known for its accuracy in detecting languages in short texts. If you need a robust solution that can handle various languages and provide reliable results, cld is a great choice.
  • franc is another language detection library that focuses on simplicity and accuracy. It uses a statistical approach to determine the language of a given text and supports a large number of languages. franc is particularly useful for applications that require language detection in larger texts, as it can provide reliable results even when the input is not perfectly clean. Its straightforward API makes it easy to integrate into any JavaScript application.

To see how languagedetect compares with cld and franc, check out the comparison: Comparing cld vs franc vs languagedetect.

Similar Npm Packages to cld

cld is a language detection library that utilizes Google's Compact Language Detector (CLD) to identify the language of a given text. It is designed to be lightweight and efficient, making it suitable for applications that require quick and accurate language detection. The library can handle a wide range of languages and is particularly useful for applications that involve multilingual content, such as chat applications, content management systems, or any platform that needs to tailor user experiences based on language.

While cld is a robust option for language detection, there are alternatives available in the ecosystem. One notable alternative is:

  • franc is another language detection library that focuses on providing accurate language identification for a wide variety of languages. It employs a statistical approach to determine the most likely language of a given text. franc is particularly useful for applications that need to support many languages and can handle short texts effectively. It is also known for its speed and efficiency, making it a solid choice for projects that require real-time language detection.

For a detailed comparison of cld and franc, you can visit the following link: Comparing cld vs franc.

README for languagedetect

Node Language Detect

Travis (.org) David npm npm node npm bundle size Get help on Codementor Twitter Follow

npm

LanguageDetect is a port of the PEAR::Text_LanguageDetect for node.js.

LanguageDetect can identify 52 human languages from text samples and return confidence scores for each.

Installation

This package can be installed via npm as follows

npm install languagedetect --save

Example

const LanguageDetect = require('languagedetect');
const lngDetector = new LanguageDetect();

// OR
// const lngDetector = new (require('languagedetect'));

console.log(lngDetector.detect('This is a test.'));

/*
  [ [ 'english', 0.5969230769230769 ],
  [ 'hungarian', 0.407948717948718 ],
  [ 'latin', 0.39205128205128204 ],
  [ 'french', 0.367948717948718 ],
  [ 'portuguese', 0.3669230769230769 ],
  [ 'estonian', 0.3507692307692307 ],
  [ 'latvian', 0.2615384615384615 ],
  [ 'spanish', 0.2597435897435898 ],
  [ 'slovak', 0.25051282051282053 ],
  [ 'dutch', 0.2482051282051282 ],
  [ 'lithuanian', 0.2466666666666667 ],
  ... ]
*/

// Only get the first 2 results
console.log(lngDetector.detect('This is a test.', 2));

/*
  [ [ 'english', 0.5969230769230769 ], [ 'hungarian', 0.407948717948718 ] ]
*/

API

  • detect(sample, limit) Detects the closeness of a sample of text to the known languages
  • getLanguages() Returns the list of detectable languages
  • getLanguageCount() Returns the number of languages that the lib can detect
  • setLanguageType(format) Sets the language format to be used. Suported values:
    • iso2, resulting in two letter language format
    • iso3, resulting in three letter language format
    • Any other value results in the full language name

Benchmark

  • node.js 1000 items processed in 1.277 secs (482 with a score > 0.2)
  • PHP 1000 items processed in 4.835 secs (535 with a score > 0.2)

Credits

Nicholas Pisarro for his work on PEAR::Text_LanguageDetect

License

Copyright (c) 2013, Francois-Guillaume Ribreau node@fgribreau.com, Ruslan Zavackiy ruslan@zavackiy.com

Permission is hereby granted, free of charge, to any person obtaining a copy of this software and associated documentation files (the "Software"), to deal in the Software without restriction, including without limitation the rights to use, copy, modify, merge, publish, distribute, sublicense, and/or sell copies of the Software, and to permit persons to whom the Software is furnished to do so, subject to the following conditions:

The above copyright notice and this permission notice shall be included in all copies or substantial portions of the Software.

THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY, FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM, OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE SOFTWARE.

npm-compare.com is an independent website designed to help developers choose the most suitable npm packages. We are not affiliated with npm, Inc or npmjs.com, the official website for the npm registry. Please note that npm is a registered trademark of npm, Inc. For more details, please refer to our Terms & Privacy.