A Weblate belső működése

Megjegyzés

Ez a fejezet áttekintést ad a Weblate belső felépítéséről.

A Weblate felépítése nagyrészt a Django keretrendszerre épül, annak kódszerkezetét követi.

Könyvtárstruktúra

Gyors áttekintés a Weblate fő tárolójának könyvtárfelépítéséről:

docs

A dokumentáció forráskódja, amely Sphinx segítségével építhető.

dev-docker

Docker-kód a fejlesztői szerver futtatásához – lásd: Weblate futtatása helyileg Dockerben.

weblate

A Weblate forráskódja mint Django alkalmazás – lásd: A Weblate belső működése.

weblate/static

Kliensfájlok (CSS, JavaScript és képek) – lásd: Weblate felhasználói felület.

Modulok

A Weblate több Django-alkalmazásból áll (egyesek opcionálisak – lásd: Opcionális Weblate modulok):

accounts

Felhasználói fiókok, profilok és értesítések kezelése.

addons

Kiegészítők a Weblate működésének testreszabásához – lásd: Kiegészítők.

api

API a Django REST framework alapján.

auth

Hitelesítés és jogosultságkezelés.

billing

Az opcionális Számlázás modul.

checks

Fordítási szöveg ellenőrzések modul.

fonts

Betűkészlet-megjelenítési ellenőrző modul.

formats

Fájlformátum absztrakciós réteg a translate-toolkit alapján.

gitexport

Az opcionális Git exportáló modul.

lang

A nyelvi és többes számú formák modelljeit definiáló modul.

legal

Az opcionális Jogi modul modul.

machinery

Gépi fordítási szolgáltatások integrációja.

memory

Beépített fordítási memória – lásd: Fordítási memória.

screenshots

Képernyőképek kezelése és OCR modul.

trans

A fordításokat kezelő főmodul.

utils

Különféle segédprogramok.

vcs

Verziókezelő rendszer absztrakció (réteg).

wladmin

A Django admin felület testreszabása.

Translation sources

A unit has a canonical file source and may have a translation from another language as its effective source. Keep Unit.source and Unit.source_unit canonical: repository synchronization and file formats depend on this. Use effective_source and its language and plural accessors for content shown to translators. Do not replace source on a copied unit to simulate an effective source; other fields and related objects still describe the canonical source.

Use Unit.source_snapshot when an operation needs to preserve the source text, language, plural rules, and terminology metadata together. Its identity defines source changes for dependency reconciliation, editor conflict detection, and AI diagnostics. For historical rendering and reports, read the snapshot recorded on the change, rather than reconstructing it from the current unit.

A missing configured parent remains a custom source: its text is empty, its language is retained, and its child is blocked. effective_source_unit is then None. Only removing the workflow or selecting the canonical language restores the canonical source.

Text-only accessors do not load language or plural metadata. For batch consumers that need the complete effective source, use UnitQuerySet.prefetch_translation_parent() alongside their existing unit prefetches. prefetch_source() already includes this. Ordinary searches keep the canonical query path and ordinary units retain their existing content hashes.

Source-dependent writes enter source_operation() before locking unit rows. The outer operation takes a shared project gate and reads its workflow mapping in one database round trip, including for projects without custom workflows. Workflow changes take source_project_gate(..., exclusive=True) before validation or persistence. Configuration changes affecting several projects acquire their gates in ascending project ID order. Never upgrade a shared gate to an exclusive one inside an operation.

The database gate function locks first and reads workflows in a separate statement, so a waiter sees configuration committed while it waited. Write paths use this transaction-scoped view rather than cached model settings. Nested operations reuse it; rolled-back savepoints discard their dependency work. Queued dependencies are reconciled before commit and external memory updates are scheduled after commit. Source-change history is written in bulk, preserving individual records while batching their notification dispatch.

Acquire any required repository locks before project gates, then component and unit row locks. Reconciliation itself only changes database state and does not acquire repository locks. Apply this boundary to bulk imports, automatic translation, file-save failures, deletion, and restoration as well as editor writes. Language and plural-rule changes require exclusive gates before their updates. Historical migrations use historical models without these runtime helpers.

Machinery source selection happens before mapping language codes to a provider. Use get_unit_source_language() for translation and uses_custom_source() for workflow-specific glossary handling. Provider codes can merge distinct language variants, so code equality cannot determine whether a workflow source was selected. Explicit component or secondary source selection takes precedence over the workflow source.

Background tasks internals

Tipp

This section describes Celery task internals. Háttérfeladatok Celery használatával describes how to configure Celery to run the tasks.

Weblate uses Celery to execute tasks in the background. Some tasks are event-triggered, and some tasks are schedule-triggered.

The Celery Beat is used for scheduling tasks, and django-celery-beat is used to store the periodic task schedule in the database. The tasks schedule is configured in tasks.py in each of the Django apps.

The tasks are consumed using several queues; the routing is configured in settings.py. The queues were designed to separate different types of workload:

celery

The default queue where background tasks are processed.

notify

Delivers notification e-mails, both for events within Weblate and for authentication or registration. This is a separate queue to make e-mail delivery smooth even if there is a backlog of other tasks.

memory

Updates translation memory entries. The updating queue can be long when importing new strings, and long processing does not matter much here, so having a separate queue avoids blocking other tasks.

backup

The backup tasks cannot be executed in parallel, and a single dedicated worker makes this easier.

translate

Automatic translation tasks are known to take long because they hit external services.