Skill UI

A library providing type-safe monadic abstractions for Go, including Option, Result, and Either. It allows developers to eliminate nil pointer risks and manage complex error handling using composable, functional pipelines, significantly improving code robustness and readability in Go applications.

samber/oops is a robust library that transforms standard Go error handling by adding crucial structured context. Instead of generic error messages, it allows developers to attach key-value attributes, stack traces, error codes, and user-facing messages directly to the error object. This is essential for modern microservices, allowing APM tools (Datadog, Sentry) and on-call engineers to diagnose failures accurately by understanding the full context of the failure, such as the domain, user ID, and specific query that failed.

A type-safe, declarative implementation of ReactiveX in Go. This library enables robust handling of infinite, asynchronous event streams (like WebSockets or tickers) by providing composable operators, automatic backpressure management, and error propagation. It is designed to replace complex, error-prone manual channel and goroutine wiring, allowing developers to build predictable, real-time, event-driven pipelines.

Provides a comprehensive guide to the `stretchr/testify` library for Go testing. It covers essential features like readable assertions (assert/require), mocking dependencies, setting up test suites, and advanced patterns (e.g., JSONEq, Eventually). Use this when writing robust unit tests, ensuring failures are self-explanatory, and managing complex test lifecycles in Go projects.

This comprehensive guide outlines best practices for writing robust JavaScript and TypeScript unit tests using the Jest framework. It covers essential topics including proper test structure, effective dependency mocking strategies (using jest.mock and jest.spyOn), handling asynchronous code, implementing snapshot testing, and modern techniques for testing React components with React Testing Library. It also provides a detailed reference of common Jest matchers.

This guide details the process of implementing internationalization (i18n) in a Next.js application using the next-intl library. It provides step-by-step instructions on adding new languages, covering translation updates, configuring routing, modifying middleware, and updating UI components to ensure complete multi-language support.

This library provides a complete and verified set of grep command patterns designed for auditing existing React codebases. It is essential for developers preparing for major React upgrades, specifically migration audits for React 18.3.1 or React 19. It detects deprecated APIs, removed features, unsafe lifecycle methods, batching vulnerabilities, and dependency conflicts, ensuring a smooth transition.

This guide provides comprehensive patterns for migrating Enzyme unit tests to React Testing Library (RTL), especially when upgrading to React 18. It emphasizes the crucial philosophical shift from testing internal implementation details (like state or props) to asserting visible user behavior. Learn best practices for rewriting shallow/mount/simulate calls into modern, accessible, and resilient RTL queries, ensuring your tests reflect how a user genuinely interacts with the component.

A lightweight, standalone library for programmatically interacting with Google Calendar. It supports full CRUD operations (list, create, update, delete) on events, finding free time slots for multiple attendees, and managing event invitations (accept/decline). It uses standalone OAuth authentication and requires a Google Workspace account for operation.

A comprehensive guide for writing and managing Python code specifically within n8n Code nodes. Learn how to perform complex data transformations, handle different execution modes (batch vs. item-by-item), and master various data access patterns (_input.all(), _input.item, _node). Note the critical limitations, such as relying only on the standard Python library and the general recommendation to use JavaScript for most n8n use cases.

Core Python library for astronomy and astrophysics workflows, covering units, coordinates, FITS I/O, tables, time systems, WCS, and cosmology. Use when implementing or debugging astronomical data analysis code with Astropy.

COBRApy is a Python library for constraint-based reconstruction and analysis (COBRA) of genome-scale metabolic models. It supports FBA, FVA, gene knockouts, flux sampling, and SBML I/O for systems biology and metabolic engineering.