data▌

Data structure for annotated matrices in single-cell analysis, facilitating efficient storage, manipulation, and analysis of large datasets.

Aeon is a scikit-learn compatible Python toolkit for time series machine learning, providing algorithms for classification, regression, clustering, and more.

Hardens code against vulnerabilities. Use when handling user input, authentication, data storage, or external integrations.

Safe read-only PostgreSQL audit workflow using https://postgresaudit.com/ for least-privilege setup, report interpretation, and remediation planning.

Related Skills:

Provides patterns for data fetching in Next.js App Router: server-side fetching, SWR/React Query integration, ISR, revalidation, error boundaries, and loading states.

When this skill does NOT apply: For concurrent access to data structures (mutexes, atomic operations), see go-concurrency. For defensive copying at API boundaries, see go-defensive. For pre-sizing capacity for performance, see go-performance.

Systematic methodology for profiling datasets, assessing data quality, discovering patterns, and understanding schemas.

Expert Core Data guidance for iOS/macOS stack setup, migrations, threading, and CloudKit sync. \n \n Covers stack initialization, fetch requests, NSFetchedResultsController, saving patterns, and merge conflict resolution across all Core Data store types \n Provides threading best practices for both traditional perform/performAndWait patterns and Swift Concurrency with actors and Sendable types \n Includes batch operations, persistent history tracking, lightweight and staged migrations, and perfo

Category: service