npm package discovery and stats viewer.

Discover Tips

  • General search

    [free text search, go nuts!]

  • Package details

    pkg:[package-name]

  • User packages

    @[username]

Sponsor

Optimize Toolset

I’ve always been into building performant and accessible sites, but lately I’ve been taking it extremely seriously. So much so that I’ve been building a tool to help me optimize and monitor the sites that I build to make sure that I’m making an attempt to offer the best experience to those who visit them. If you’re into performant, accessible and SEO friendly sites, you might like it too! You can check it out at Optimize Toolset.

About

Hi, 👋, I’m Ryan Hefner  and I built this site for me, and you! The goal of this site was to provide an easy way for me to check the stats on my npm packages, both for prioritizing issues and updates, and to give me a little kick in the pants to keep up on stuff.

As I was building it, I realized that I was actually using the tool to build the tool, and figured I might as well put this out there and hopefully others will find it to be a fast and useful way to search and browse npm packages as I have.

If you’re interested in other things I’m working on, follow me on Twitter or check out the open source projects I’ve been publishing on GitHub.

I am also working on a Twitter bot for this site to tweet the most popular, newest, random packages from npm. Please follow that account now and it will start sending out packages soon–ish.

Open Software & Tools

This site wouldn’t be possible without the immense generosity and tireless efforts from the people who make contributions to the world and share their work via open source initiatives. Thank you 🙏

© 2025 – Pkg Stats / Ryan Hefner

@gmr-fms/word-extractor

v0.3.0

Published

Node.js package to read Word .doc files

Readme

Forked from morungos/node-word-extractor

What's different?
I needed buffer support but didn't want to deal with coffeescript so I modified the repo a bit. The main public change is the module is now an object with two methods fromFile and fromBuffer. I also removed 'bluebird' so the returned promises are native.

word-extractor

Read data from a Word document using node.js

Why use this module?

There are a fair number of npm components which can extract text from Word .doc files, but they all appear to require some external helper program, and involve either spawning a process or communicating with a persistent one. That raises the installation and deployment burden as well as the runtime one.

This module is intended to provide a much faster way of reading the text from a Word file, without leaving the node.js environment.

How do I install this module?

yarn add @gmr-fms/word-extractor

# Or using npm...
npm install @gmr-fms/word-extractor

How do I use this module?

const extract = require('word-extractor');
extract.fromFile('file.doc').then(doc => {
  console.log(doc.getBody());
});

The object returned from the extract() method is a promise that resolves to a document object, which then provides several views onto different parts of the document contents.

Methods

extract#fromFile(filePath) => Promise<Document>
extract#fromBuffer(buf) => Promise<Document>

Document#getBody()

Retrieves the content text from a Word document. This will handle UNICODE characters correctly, so if there are accented or non-Latin-1 characters present in the document, they'll show as is in the returned string.

Document#getFootnotes()

Retrieves the footnote text from a Word document. This will handle UNICODE characters correctly, so if there are accented or non-Latin-1 characters present in the document, they'll show as is in the returned string.

Document#getHeaders()

Retrieves the header and footer text from a Word document. This will handle UNICODE characters correctly, so if there are accented or non-Latin-1 characters present in the document, they'll show as is in the returned string.

Document#getAnnotations()

Retrieves the comment bubble text from a Word document. This will handle UNICODE characters correctly, so if there are accented or non-Latin-1 characters present in the document, they'll show as is in the returned string.

License

Copyright (c) 2016-2017. Stuart Watt.

Licensed under the MIT License.