@linaria/core vs goober

@linaria/core excels as a zero-runtime CSS-in-JS solution, prioritizing compile-time transformations to generate static CSS files. This approach is ideal for developers and teams aiming for maximal performance by eliminating any runtime overhead associated with style injection or processing in the browser. Its core philosophy centers on extracting distinct, static CSS, making it a powerful choice for applications where bundle size and runtime performance are paramount, especially in React environments.

Goober, on the other hand, champions extreme performance and a minimal footprint, clocking in at less than 1KB. It offers a complete CSS-in-JS experience with a focus on simplicity and flexibility. Its target audience includes developers who need a highly efficient, yet functional, CSS-in-JS library that can be easily integrated into various JavaScript projects, including those using Preact and React.

A significant architectural divergence lies in their runtime behavior. @linaria/core is designed to be zero-runtime, meaning all styling logic is processed during the build phase. This results in plain CSS files that are served directly to the browser, offering unparalleled runtime efficiency. Goober, while incredibly small, does involve some runtime processing for its dynamic styling capabilities, though its minuscule size makes this overhead negligible for most applications.

Regarding their extension and customization models, @linaria/core integrates deeply with build tools like Webpack and Babel, allowing for advanced code analysis and transformations at build time. This enables features like static analysis of styles and automatic critical CSS extraction. Goober has a more straightforward API, focusing on simplicity and ease of use, without requiring extensive build tool configuration for its core functionality.

From a developer experience perspective, @linaria/core demands a build tool setup and potentially a steeper learning curve due to its compile-time-centric nature. However, it offers excellent TypeScript support and a robust development experience once configured. Goober provides a more immediate and low-friction entry point, being very easy to learn and integrate, especially for those familiar with styled-components syntax, offering a smooth transition and positive DX without complex build configurations.

Performance and bundle size are where both libraries shine, albeit in different ways. @linaria/core's zero-runtime nature ensures exceptional runtime performance, and its generated CSS is highly optimized. Its bundle size contribution is effectively zero at runtime. Goober's main selling point is its incredibly small on-disk and gzipped size (1.3 kB gzip), making it one of the leanest CSS-in-JS solutions available, though it does have a small runtime component.

For practical recommendations, choose @linaria/core if your absolute top priority is runtime performance, offline applications, or projects where every millisecond of JavaScript execution matters. It's excellent for large-scale React applications needing maximum optimization. Select goober when you need a tiny, feature-rich CSS-in-JS library that is easy to pick up and integrate quickly, particularly for smaller projects, performance-sensitive micro-frontends, or when working with libraries like Preact where minimal dependencies are key.

Considering ecosystem and long-term maintenance, both @linaria/core and goober are well-maintained projects with active communities. @linaria/core leverages the broader Babel and Webpack ecosystems, offering extensibility through build tools. Goober maintains a focus on its core promise of extreme minimalism and performance, with a clear and stable API that suggests good long-term maintainability without being tied to complex build toolchains.

For niche use cases, @linaria/core's static CSS generation makes it suitable for server-side rendering scenarios where pre-rendered static HTML with associated styles is critical for performance and SEO. Goober's tiny footprint and flexibility also allow it to be used in unconventional JavaScript environments where even minimal overhead is a concern, or for rapid prototyping where quick iteration and small builds are beneficial.