Convert Markdown to PDF via Open Source Node.js Library
Open Source Node.js API to Convert Markdown File to PDF Format. It Offers a Range of Customization Options & Multiple Platforms Support.
What is Markdown to PDF ?
Markdown’s simplicity and readability have made it a favorite for documentation, note-taking, and content creation, but sharing these materials often requires converting them into universally accessible PDFs. md-to-pdf is an open source PDF API that makes it easy to convert Markdown file to PDF in a Node.js environment with just a few lines of code. Designed for straightforward PDF processing in Node.js application, it supports CommonMark syntax and is ideal for users seeking a quick, reliable way to generate polished PDFs without complex setup. Its clean design also makes it easy to format text in PDF while keeping the process efficient.
The library offers powerful features like PDF style customization, multi-platform compatibility, LaTeX integration, and advanced configuration, allowing software developers to apply custom styles to PDF for professional results. Its extensible architecture lets you enhance existing functionality or integrate it into larger workflows, whether you need to convert PDF file in Node.js, customize layouts, or automate document generation. Perfect for developers, writers, researchers, and students, md-to-pdf provides a flexible, productivity-boosting toolkit for transforming Markdown into high-quality, styled PDFs.
Getting Started with Markdown to PDF
Markdown to PDF is available at npm, You can easily download it and install it on your machine. Please use the following command for smooth installation.
Install Markdown to PDF Library via npm
npm i -g md-to-pdf Install Markdown to PDF Library via GibHub
git clone "https://github.com/simonhaenisch/md-to-pdf"
cd md-to-pdf
npm link # or npm i -g
Convert Markdown to PDF in Node.js Apps
The open source Markdown to PDF API, stands out as a comprehensive solution for effortlessly converting Markdown documents into polished PDFs inside Node.js applications. Software developers can easily customize the conversion process, and can easily specify custom CSS styles to control various aspects such as fonts, colors, margins, and many more. For users requiring advanced customization, the library offers a wide range of configuration options. You can specify settings such as page size, orientation, header and footer content, and more. The following code snippet demonstrates how to convert a Markdown file named input.md into a PDF named output.pdf using Markdown to PDF Node.js Library.
How to Convert a Markdown File to PDF Document inside Node.js Apps?
const mdToPdf = require('md-to-pdf');
mdToPdf().from('input.md').to('output.pdf', (err) => {
if (err) {
console.error(err);
process.exit(1);
}
console.log('Conversion successful!');
});
Customizable Styling Support
One of the standout features of the open source Markdown to PDF Node.js Library is its robust support for customizable styling, empowering software developers to tailor the appearance of the generated PDFs according to their specific requirements. You can define custom styles using CSS, which will be applied to the rendered PDF. The following example shows how to define custom styles for the body text and heading elements, specifying font-family and color properties.
How to Apply Custom Styles for the Body Text and Heading via Node.js Apps?
const options = {
stylesheet: `
body {
font-family: Arial, sans-serif;
}
h1 {
color: #007bff;
}
`,
};
mdToPdf('Hello, Markdown to PDF!
', options)
.then((pdfBuffer) => {
// Handle the generated PDF buffer
})
.catch((error) => {
// Handle errors
});
Cross-Platform Compatibility
Markdown to PDF Node.js Library is designed to be compatible with multiple platforms, ensuring consistent performance across different environments. The Library offers seamless cross-platform compatibility with Windows, macOS, and Linux operating systems. This cross-platform compatibility increases accessibility and flexibility by enabling users to take advantage of the library's features regardless of their preferred computing environment.