Socket
Socket
Sign inDemoInstall

@vscode/vscode-languagedetection

Package Overview
Dependencies
0
Maintainers
11
Versions
22
Alerts
File Explorer

Advanced tools

Install Socket

Detect and block malicious and high-risk dependencies

Install

    @vscode/vscode-languagedetection

An npm package that uses guesslang's ML model to detect source code languages


Version published
Maintainers
11
Created

Readme

Source

vscode-languagedetection

An npm package that uses machine learning to detect source code languages. Powered by @yoeo's guesslang model!

Usage:

First install it in your project:

npm install --save @vscode/vscode-languagedetection
# or using yarn
yarn add @vscode/vscode-languagedetection

Then instantiate a ModuleOperations and pass it in the model.json and weights file content:

NOTE: This is only for VS Code. In the future, you shouldn't have to do this.

import { ModelJSON, ModelOperations } from "@vscode/vscode-languagedetection";

const modulOperations = new ModelOperations(async () => {
    return JSON.parse(readFileSync(join(__dirname, '..', '..', 'model', 'model.json')).toString()) as ModelJSON;
}, async () => {
    return readFileSync(join(__dirname, '..', '..', 'model', 'group1-shard1of1.bin')).buffer;
});

const result = await modulOperations.runModel(`
function makeThing(): Thing {
    let size = 0;
    return {
        get size(): number {
        return size;
        },
        set size(value: string | number | boolean) {
        let num = Number(value);
        // Don't allow NaN and stuff.
        if (!Number.isFinite(num)) {
            size = 0;
            return;
        }
        size = num;
        },
    };
}
`);

which will give you the following in order of confidence:

[
  { languageId: 'ts', confidence: 0.48307517170906067 },
  { languageId: 'rs', confidence: 0.10045434534549713 },
  { languageId: 'js', confidence: 0.07833506911993027 },
  { languageId: 'c', confidence: 0.045049071311950684 },
  { languageId: 'lua', confidence: 0.044198162853717804 },
  { languageId: 'cpp', confidence: 0.03847603127360344 },
  { languageId: 'cs', confidence: 0.03298814222216606 },
  { languageId: 'mm', confidence: 0.02999635599553585 },
  { languageId: 'html', confidence: 0.01874217577278614 },
  { languageId: 'sql', confidence: 0.01811739057302475 },
  { languageId: 'swift', confidence: 0.01418407540768385 },
  { languageId: 'pl', confidence: 0.014126052148640156 },
  { languageId: 'md', confidence: 0.01112559624016285 },
  { languageId: 'java', confidence: 0.009976979345083237 },
  { languageId: 'ps1', confidence: 0.009242385625839233 },
  { languageId: 'php', confidence: 0.008150739595293999 },
  { languageId: 'go', confidence: 0.0069260732270777225 },
  { languageId: 'tex', confidence: 0.006594990845769644 },
  { languageId: 'scala', confidence: 0.00619362760335207 },
  { languageId: 'py', confidence: 0.004240741487592459 },
  { languageId: 'r', confidence: 0.0033439004328101873 },
  { languageId: 'matlab', confidence: 0.0030552551615983248 },
  { languageId: 'css', confidence: 0.0026798006147146225 },
  { languageId: 'sh', confidence: 0.0023688252549618483 },
  { languageId: 'ipynb', confidence: 0.002114647999405861 },
  { languageId: 'bat', confidence: 0.0018151027616113424 },
  { languageId: 'hs', confidence: 0.001677449094131589 },
  { languageId: 'erl', confidence: 0.0014191442169249058 },
  { languageId: 'coffee', confidence: 0.000696933304425329 },
  { languageId: 'rb', confidence: 0.0006357143283821642 }
]

Local development

To build from source, follow these steps:

  1. Clone the repository
  2. Run npm install
  3. Run npm run watch

To run the tests, simply run npm test.

To build a production package:

  1. Run npm run build
  2. Run npm pack

To publish this package, run npm publish.

Contributing

This project welcomes contributions and suggestions. Most contributions require you to agree to a Contributor License Agreement (CLA) declaring that you have the right to, and actually do, grant us the rights to use your contribution. For details, visit https://cla.opensource.microsoft.com.

When you submit a pull request, a CLA bot will automatically determine whether you need to provide a CLA and decorate the PR appropriately (e.g., status check, comment). Simply follow the instructions provided by the bot. You will only need to do this once across all repos using our CLA.

This project has adopted the Microsoft Open Source Code of Conduct. For more information see the Code of Conduct FAQ or contact opencode@microsoft.com with any additional questions or comments.

Trademarks

This project may contain trademarks or logos for projects, products, or services. Authorized use of Microsoft trademarks or logos is subject to and must follow Microsoft's Trademark & Brand Guidelines. Use of Microsoft trademarks or logos in modified versions of this project must not cause confusion or imply Microsoft sponsorship. Any use of third-party trademarks or logos are subject to those third-party's policies.

FAQs

Last updated on 28 Jul 2021

Did you know?

Socket for GitHub automatically highlights issues in each pull request and monitors the health of all your open source dependencies. Discover the contents of your packages and block harmful activity before you install or update your dependencies.

Install

Related posts

SocketSocket SOC 2 Logo

Product

  • Package Alerts
  • Integrations
  • Docs
  • Pricing
  • FAQ
  • Roadmap

Stay in touch

Get open source security insights delivered straight into your inbox.


  • Terms
  • Privacy
  • Security

Made with ⚡️ by Socket Inc