mirror of
https://github.com/deunix-educ/aventuriers-des-mots.git
synced 2026-10-13 02:11:58 +02:00
Denis Defolie
493a8617d7
Wires every autoload up to a real UI: boot -> profile select/create -> world map (three mission markers, positioned from data, not hardcoded pixels) -> mission intro (narrative from data/missions/, a new data type with its own schema) -> rule panel -> exercise host -> one of the three exercise type scenes -> feedback panel -> reward screen -> back to the map. exercise_host is the only piece with real orchestration logic: picks exercises via ExerciseEngine (now fully implemented, validating at load like make validate-data does), validates answers through the pure AnswerValidator/DictationAnalyzer, escalates aid over 3 attempts via AttemptFlow, feeds DifficultyManager so adaptive difficulty is actually wired in rather than dead code, and records every attempt through ProgressManager. Every exercise-type scene (multiple_choice, sentence_correction, dictation) only emits its answer by signal, per the architecture invariant. All child-facing text now comes from data/localization/fr.json via UIText, not hardcoded in scripts or scenes. Getting that right required extending SchemaValidator to support "additionalProperties" as a schema (dynamic keys), which also closed a real gap: save.skills was previously unvalidated against SkillState's actual shape. 16 new headless tests, including two integration tests that instance exercise_host.tscn directly and drive it by emitting child-scene signals, stopping short of the final scene transition (which would tear down the test runner's own tree). Everything that needs a screen -- layout at different sizes, touch, virtual keyboard, actual audio playback (no .ogg files exist yet) -- is listed in the new docs/testing/manual-checklist.md instead of claimed as verified. Co-Authored-By: Claude Sonnet 5 <noreply@anthropic.com>
67 lines
2.2 KiB
GDScript
67 lines
2.2 KiB
GDScript
extends Node
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## Competences, missions debloquees et planification des revisions du profil
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## selectionne. Delegue les calculs a ProgressUpdates (scripts/profiles/), qui
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## s'appuie sur ReviewScheduler et DifficultyManager (scripts/pedagogy/).
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## L'ecriture sur disque reste groupee : save_now() est appele en fin de
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## mission, pas a chaque tentative (docs/specs/decisions.md, point 7).
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var _current_save: Dictionary = {}
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var _current_profile_id: String = ""
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## Charge la sauvegarde existante d'un profil et demarre une nouvelle seance
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## (voir ProgressUpdates.start_session). Faux si le profil n'a pas de
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## sauvegarde lisible.
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func load_profile(profile_id: String) -> bool:
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var data: Variant = SaveManager.load(profile_id)
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if data == null:
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return false
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_current_profile_id = profile_id
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_current_save = ProgressUpdates.start_session(data)
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return true
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func record_attempt(
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skill_id: String, success: bool, hint_used: bool, exercise_type: String
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) -> void:
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var attempt := {
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"skill": skill_id,
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"success": success,
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"hint_used": hint_used,
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"exercise_type": exercise_type,
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}
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_current_save = ProgressUpdates.record_attempt(_current_save, attempt)
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func unlock_region(region_id: String) -> void:
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_current_save = ProgressUpdates.unlock_region(_current_save, region_id)
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func add_stars(amount: int) -> void:
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_current_save = ProgressUpdates.add_stars(_current_save, amount)
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func stars() -> int:
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return _current_save.get("rewards", {}).get("stars", 0)
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func next_difficulty_for_skill(skill_id: String, current_difficulty: int) -> int:
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return ProgressUpdates.next_difficulty_for_skill(_current_save, skill_id, current_difficulty)
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func get_skill_state(skill_id: String) -> Dictionary:
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var skills: Dictionary = _current_save.get("skills", {})
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return skills.get(skill_id, ReviewScheduler.initial_state())
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func current_save() -> Dictionary:
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return _current_save
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## A appeler en fin de mission (pas apres chaque tentative) pour persister la
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## progression du profil courant.
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func save_now() -> bool:
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if _current_profile_id.is_empty():
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return false
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return SaveManager.save(_current_profile_id, _current_save)
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