Leveraging Weblate’s Translation Memory and Fuzzy Matching for Consistent Translations
Weblate’s translation memory automatically suggests fuzzy matches for repetitive strings, cutting translator effort while preserving consistency.
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Weblate’s translation memory automatically suggests fuzzy matches for repetitive strings, cutting translator effort while preserving consistency.
Guide on choosing between Weblate's built-in Whoosh index and external TMX files for large-scale localization, focusing on performance, Celery memory management, and index maintenance.
Learn how Weblate’s component linking and shared translation memory let teams translate common UI strings once and propagate them across multiple projects, reducing duplicate work while preserving per‑component controls.
Learn how to turn on Weblate’s Translation Memory, tune its similarity threshold, and reuse approved translations to reduce repetitive work and improve consistency.
Learn how to enable Weblate's shared translation memory to reuse approved strings across components, cut translation effort, and avoid common pitfalls.
Goal is to keep editor save latency predictable when multiple users edit the same project via Weblate UI or API. Weblate stores translation units with Django ORM transactions. Background work for commits, translation memory indexing and machine translation suggestions runs via Celery on the same database. With default queues, UI requests can contend for I/O