'data loading' 검색 결과

Kotlin Coroutines와 Flow로 Android 및 Kotlin Multiplatform의 비동기 작업과 데이터 갱신을 구현하고 병렬 실행, 화면 상태, 취소, 오류 처리와 테스트를 다룹니다.

• 여러 데이터를 병렬로 불러옵니다
• StateFlow로 화면 상태를 관리합니다
• 검색 입력을 조절하고 통신을 재시도합니다

FAISS로 대규모 벡터에서 유사한 데이터를 검색하도록 돕습니다. 인덱스 선택과 저장, GPU 사용을 안내하고 검색 속도·정확도·메모리 사용량을 조정합니다.

• 대규모 벡터 유사도 검색 구현
• 속도·정확도·메모리에 맞는 인덱스 선택
• GPU를 이용한 일괄 검색

Notion 페이지와 데이터베이스를 검색하고 수정하며 Markdown 읽기와 쓰기, 파일 업로드를 수행합니다. 외부 데이터 정기 동기화와 이벤트 연동용 Workers도 만듭니다.

• 회의 메모를 Notion에 저장합니다
• 지정한 상태의 데이터를 찾습니다
• 이미지와 자료를 업로드합니다

Audit page loading and choose resource hints, browser instructions for fetching files or preparing connections early. Use measurements to identify delays, then suggest preload, preconnect, prefetch, or dns-prefetch for critical assets, external services, and likely next-page resources.

한국어 요약은 준비 중입니다. 영어 요약을 표시하고 있습니다.

• Reviewing early loading of key images and fonts
• Preparing connections to external services
• Prefetching resources for likely next pages

Measure how Google Tag Manager affects page loading and rendering. Identify costly tags, triggers, and requests, then guide cleanup, asynchronous loading, or a move to server-side processing based on observed performance problems.

한국어 요약은 준비 중입니다. 영어 요약을 표시하고 있습니다.

• Investigate slow pages using GTM
• Review unused tags and triggers
• Check asynchronous script loading

Write, review, and refactor React and Next.js code using performance guidelines from Vercel. Prioritized rules help identify sequential data requests, oversized JavaScript bundles, unnecessary re-renders, and other opportunities to improve loading and responsiveness.

한국어 요약은 준비 중입니다. 영어 요약을 표시하고 있습니다.

• Reviewing React components for performance issues
• Improving data fetching in Next.js pages
• Reducing JavaScript bundle size

Analyze Neuropixels neural recordings with SpikeInterface, from loading and preprocessing to motion correction and spike sorting, which separates signals by neuron. Calculate quality metrics, review candidate units, and export plots and data for further inspection.

한국어 요약은 준비 중입니다. 영어 요약을 표시하고 있습니다.

• Inspect and preprocess SpikeGLX, Open Ephys, or NWB recordings
• Check and correct movement-related drift before spike sorting
• Evaluate and select units using quality metrics

Write, review, or refactor React and Next.js code using prioritized performance guidelines. Address sequential data requests, large bundles of browser code, server work, and unnecessary rendering, with explanations and code examples for each rule.

한국어 요약은 준비 중입니다. 영어 요약을 표시하고 있습니다.

• Writing React components with performance in mind
• Reviewing Next.js data fetching
• Reducing browser code size and loading time

Implement .NET workflows for Azure AI Foundry projects, including agent creation, resource connections, dataset uploads, model deployment inspection, search index management, and evaluations. Examples also cover authentication, asynchronous operations, and resource cleanup.

한국어 요약은 준비 중입니다. 영어 요약을 표시하고 있습니다.

• Creating and running agents from a .NET application
• Inspecting resource connections and model deployments
• Uploading datasets and managing search indexes

Build systems that use Pinecone to find documents for AI answers or retain agent memories across sessions. Guides index setup, data loading, meaning-based and keyword search, memory separation, and end-to-end checks.

한국어 요약은 준비 중입니다. 영어 요약을 표시하고 있습니다.

• Build an AI assistant that answers from documents
• Keep agent facts and decisions across sessions
• Combine meaning-based search with exact terminology

Plan website improvements for organic search traffic through keyword research, content structure, page metadata, and technical checks. Get guidance on internal links, structured data that describes page content, loading speed, and ongoing performance monitoring.

한국어 요약은 준비 중입니다. 영어 요약을 표시하고 있습니다.

• Choosing keywords and planning related articles
• Reviewing titles, descriptions, and headings
• Checking structured data and indexing settings

Write, review, and refactor React and Next.js code using performance guidelines ranked by impact. Covers sequential data requests, downloaded code size, server work, and unnecessary rendering to guide concrete implementation improvements.

한국어 요약은 준비 중입니다. 영어 요약을 표시하고 있습니다.

• Review React and Next.js code for performance issues
• Improve data fetching that waits on sequential requests
• Reduce downloaded code size and loading time

Create Vitest tests for Mastra playground features using MSW to simulate network responses. Exercise the real client SDK, React Query cache, and components with typed sample data to check loading, access conditions, redirects, and errors.

한국어 요약은 준비 중입니다. 영어 요약을 표시하고 있습니다.

• Test loading, empty, and error states
• Check requests controlled by permissions or feature flags
• Verify pagination and query parameters

Build Next.js applications with App Router, the app directory routing system. Get guidance on server rendering, data fetching, caching, API endpoints, and deployment settings, including loading states and image optimization for responsive page experiences.

한국어 요약은 준비 중입니다. 영어 요약을 표시하고 있습니다.

• Designing pages and shared layouts with App Router
• Configuring data caching and revalidation
• Implementing forms and API endpoints

Build charts with TradingView's lightweight-charts, including candlesticks, lines, live updates, scales, and annotations. Guidance checks installed types and v5 APIs to support chart integration, framework lifecycle handling, and troubleshooting of common data and display issues.

한국어 요약은 준비 중입니다. 영어 요약을 표시하고 있습니다.

• Build candlestick charts with a separate volume pane
• Add live updates and historical data
• Fix v4-to-v5 API migration issues

Add PyTorch FSDP2 to training scripts so model state can be split across GPUs. Covers distributed initialization, mixed precision, CPU offloading, and checkpoint saving and loading for models that exceed a single GPU's memory.

한국어 요약은 준비 중입니다. 영어 요약을 표시하고 있습니다.

• Training a model that exceeds one GPU's memory
• Adding FSDP2 to an existing training script
• Configuring mixed precision and CPU offloading

Create dashboard panels in plain TypeScript using the browser’s page-building API. Follow a shared base class to add titles, counts, loading indicators, error messages, manual retry buttons, and periodically refreshed content.

한국어 요약은 준비 중입니다. 영어 요약을 표시하고 있습니다.

• Add a stock price panel to a dashboard
• Show loading indicators and retry buttons on failure
• Standardize titles and item counts across panels

Build dashboard panels in plain TypeScript with titles, counts, loading states, and retry controls. Includes patterns for escaping external text before HTML insertion to address XSS, where untrusted content can run scripts in a page.

한국어 요약은 준비 중입니다. 영어 요약을 표시하고 있습니다.

• Adding stock or calendar panels to a dashboard
• Escaping external API text before HTML insertion
• Adding loading, error, and retry states

Build dashboard panels in plain TypeScript with saved sizes and expanded or collapsed states. The pattern includes data fetching retries with increasing delays, loading indicators, error messages, and a shared base class for consistent panel behavior.

한국어 요약은 준비 중입니다. 영어 요약을 표시하고 있습니다.

• Restoring panel sizes and expanded or collapsed states
• Adding automatic retries when data fetching fails
• Standardizing loading and error displays across panels

Build TypeScript interface panels with badges, thumbnails, and colors driven by data. Organize shared behavior in a base class, including fetch retries, error recovery, and saved panel size and expansion state.

한국어 요약은 준비 중입니다. 영어 요약을 표시하고 있습니다.

• Building a news panel with thumbnails
• Adding badges colored by data source
• Preserving panel size and expansion state

Create editable FigJam diagrams for workflows, system architecture, data relationships, and schedules. The skill selects a suitable diagram type and guides Mermaid, a text format for diagrams, while accounting for rendering limits.

한국어 요약은 준비 중입니다. 영어 요약을 표시하고 있습니다.

• Visualizing a workflow or decision tree
• Mapping services and data stores
• Showing API interactions over time

Integrate charts and architecture diagrams into React or Next.js apps. Plan which parts run in the browser, separate rendering from application state, and address loading performance, mobile layouts, accessibility, and shareable views.

한국어 요약은 준비 중입니다. 영어 요약을 표시하고 있습니다.

• Integrating D3 charts into React components
• Choosing browser or server rendering in Next.js
• Sharing chart filters and selections through URLs

Apply Vercel Engineering’s performance guidelines when writing, reviewing, or refactoring React and Next.js code. Prioritize improvements to data fetching, downloaded code size, server processing, and unnecessary rendering using rules with explanations and code examples.

한국어 요약은 준비 중입니다. 영어 요약을 표시하고 있습니다.

• Review React components for performance issues
• Improve data fetching in Next.js pages
• Reduce downloaded code and loading time

Create editable FigJam diagrams for workflows, system architecture, data relationships, and schedules. The skill selects a suitable diagram type and guides Mermaid, a text format for diagrams, while accounting for rendering limits.

한국어 요약은 준비 중입니다. 영어 요약을 표시하고 있습니다.

• Visualizing a workflow or decision tree
• Mapping services and data stores
• Showing API interactions over time