{"categories":[{"label":"Libraries","url":"https://skillfed.io/packages/category/software-development-libraries/3"}],"enrichment":{"capability":"Batches and caches concurrent data requests in asyncio applications, coalescing multiple loads into single batch operations to reduce backend round-trips.","skillfed_tags":["graphql","async-batching","request-caching"],"use_cases":["Implementing GraphQL resolvers that fetch related entities without triggering N+1 queries against a database","Batching API calls to external services when handling concurrent requests in a web framework","Deduplicating redundant data fetches within a single request lifecycle in async web applications","Building data access layers that transparently batch individual load calls into efficient bulk operations","Caching computed or fetched values for the duration of a single request to reduce memory churn"],"what_it_does":"Aiodataloader is a Python port of Facebook's original DataLoader pattern, designed to optimize data fetching in asyncio applications by batching and caching. It solves the N+1 query problem by automatically coalescing multiple individual load requests that occur within a single event-loop tick into a single batch operation sent to your data source. You provide a batch loading function that accepts a list of keys and returns a list of values; the loader handles deduplication, caching, and scheduling.\n\nThe package is commonly used in GraphQL servers but applies broadly to any scenario where you fetch data from a backend (database, API, service) and want to minimize round-trips. It maintains a per-request in-memory cache, so the same key loaded multiple times within one request returns the same future without re-fetching. Caching is request-scoped by design\u2014you typically create a new loader instance per request to avoid cross-user data leakage.","worth_installing":"Yes, if you are building an asyncio application (GraphQL service, async web framework, etc.) that fetches data from a backend and you want to eliminate N+1 query patterns. The package is production-stable, has no known vulnerabilities, and carries permissive licensing. The aging maintenance status is a minor concern but not a blocker\u2014the core pattern is mature and the codebase is not archived. Install if batching and per-request caching solve a real problem in your data layer."},"id":"aiodataloader","links":{"html":"https://skillfed.io/packages/aiodataloader","md":"https://skillfed.io/packages/aiodataloader.md","pypi":"https://pypi.org/project/aiodataloader/"},"maintenance":{"status":"aging"},"meta":{"latest_release":"2025-11-29","license_spdx":null,"license_treatment":"permissive","name":"aiodataloader","python_support":"supports_current","summary":"Asyncio DataLoader implementation for Python"},"popularity":{"monthly_downloads":1735516,"position":3607,"tier":"top_5000"},"security":{"n_vulnerabilities":0},"version":"0.4.3"}