Your First WebAssembly Program and Web App (Written, Tested, and Deployed Entirely in the Web Browser)

· Source: Towards Data Science · Field: Technology & Digital — Software Development & Engineering, Cloud Computing & IT Infrastructure, Emerging Technologies & Innovation · Depth: Novice, long

Summary

This article details a step-by-step tutorial on building WebAssembly (WASM) applications entirely within a web browser, leveraging GitHub Codespaces. It explains how WASM enables compiled languages like C, C++, and Rust to execute at near-native speeds in browsers, transforming them into powerful computational platforms. The tutorial guides users through creating a GitHub repository, launching GitHub Codespaces, writing a simple C program, and compiling it into WASM using Emscripten. It then demonstrates how to serve the WASM application locally with a Python HTTP server and how to integrate WASM functions with HTML and JavaScript for interactive web apps. The process concludes with instructions on downloading the generated HTML, JS, and WASM files and deploying them to a web server, all without requiring any local software installations.

Key takeaway

For web developers and data scientists aiming to deploy high-performance applications without user installations, embracing WebAssembly is crucial. This approach allows you to port existing C/C++/Rust code directly to the browser, significantly enhancing web application capabilities for tasks like scientific computing or data analysis. Consider using cloud-based development environments like GitHub Codespaces to streamline the entire WASM development and deployment workflow, making your tools accessible via a simple URL.

Key insights

WebAssembly allows high-performance code to run directly in browsers, transforming web apps into powerful computational platforms.

Principles

Method

Develop C code in GitHub Codespaces, compile to WASM using Emscripten, serve with a Python HTTP server, and integrate with HTML/JavaScript for browser execution.

In practice

Topics

Code references

Best for: Software Engineer, Data Scientist, DevOps Engineer

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Editorial summary, takeaway, and curation by AIssential. Original article published by Towards Data Science.