mirror of
https://github.com/deunix-educ/aventuriers-des-mots.git
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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>
151 lines
5.1 KiB
GDScript
151 lines
5.1 KiB
GDScript
extends Control
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## Hote d'exercice : charge la regle, enchaine les exercices d'une mission,
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## valide chaque reponse via les validateurs purs (AnswerValidator /
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## DictationAnalyzer), applique l'aide graduee (AttemptFlow) et enregistre
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## chaque tentative dans ProgressManager (docs/specs/decisions.md, point 7).
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## Ne charge et ne sauvegarde rien lui-meme sur disque : ProgressManager et
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## SaveManager restent seuls responsables de la persistance.
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const MISSION_LENGTH := 3
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const TYPE_SCENES := {
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"multiple_choice": "res://scenes/exercises/multiple_choice.tscn",
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"sentence_correction": "res://scenes/exercises/sentence_correction.tscn",
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"dictation": "res://scenes/exercises/dictation.tscn",
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}
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var _mission: Dictionary = {}
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var _rule: Dictionary = {}
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var _skill_id: String = ""
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var _current_exercise: Dictionary = {}
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var _current_exercise_scene: Control = null
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var _current_difficulty := 1
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var _attempt_number := 1
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var _completed_count := 0
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var _last_exercise_id := ""
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@onready var _exercise_container: Control = %ExerciseContainer
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@onready var _overlay_container: Control = %OverlayContainer
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## Accesseurs reserves aux tests d'integration (scenes/exercises/
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## exercise_host.tscn n'expose pas de script "ami" en GDScript).
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func get_current_exercise() -> Dictionary:
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return _current_exercise
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func get_attempt_number() -> int:
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return _attempt_number
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func get_completed_count() -> int:
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return _completed_count
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func _ready() -> void:
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_mission = ExerciseEngine.get_mission(GameManager.pending_mission_id)
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_rule = ExerciseEngine.get_rule(_mission["rule_id"])
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_skill_id = _rule.get("skill", "")
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_current_difficulty = ProgressManager.next_difficulty_for_skill(_skill_id, 1)
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_show_rule_panel()
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func _show_rule_panel() -> void:
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var rule_panel: Control = preload("res://scenes/ui/rule_panel.tscn").instantiate()
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_overlay_container.add_child(rule_panel)
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rule_panel.show_rule(_rule)
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rule_panel.continued.connect(_on_rule_panel_continued.bind(rule_panel))
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func _on_rule_panel_continued(rule_panel: Control) -> void:
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rule_panel.queue_free()
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_load_next_exercise()
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func _load_next_exercise() -> void:
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_current_exercise = ExerciseEngine.pick_exercise_for_mission(
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_mission, _last_exercise_id, _current_difficulty
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)
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_attempt_number = 1
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if _current_exercise_scene != null:
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_current_exercise_scene.queue_free()
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var scene_path: String = TYPE_SCENES[_mission["exercise_type"]]
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_current_exercise_scene = load(scene_path).instantiate()
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_exercise_container.add_child(_current_exercise_scene)
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_current_exercise_scene.load_exercise(_current_exercise)
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_connect_answer_signal()
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func _connect_answer_signal() -> void:
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match _mission["exercise_type"]:
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"multiple_choice":
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_current_exercise_scene.answer_submitted.connect(_on_multiple_choice_submitted)
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"sentence_correction":
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_current_exercise_scene.answer_submitted.connect(_on_sentence_correction_submitted)
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"dictation":
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_current_exercise_scene.answer_submitted.connect(_on_dictation_submitted)
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func _on_multiple_choice_submitted(selected_index: int) -> void:
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_handle_result(AnswerValidator.validate_multiple_choice(_current_exercise, selected_index))
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func _on_sentence_correction_submitted(selected_indices: Array, corrections: Dictionary) -> void:
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var typed_indices: Array[int] = []
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for index: int in selected_indices:
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typed_indices.append(index)
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_handle_result(
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AnswerValidator.validate_sentence_correction(
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_current_exercise, typed_indices, corrections
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)
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)
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func _on_dictation_submitted(submitted_text: String) -> void:
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_handle_result(DictationAnalyzer.analyze(_current_exercise, submitted_text))
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func _handle_result(result: CorrectionResult) -> void:
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var support_level := AttemptFlow.SupportLevel.EXPLANATION
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var is_terminal := result.is_correct
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if not result.is_correct:
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support_level = AttemptFlow.support_level_for_attempt(_attempt_number)
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is_terminal = AttemptFlow.should_end_exercise(_attempt_number)
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ProgressManager.record_attempt(
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_skill_id, result.is_correct, _attempt_number > 1, _mission["exercise_type"]
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)
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_show_feedback(result, support_level, is_terminal)
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func _show_feedback(
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result: CorrectionResult, support_level: AttemptFlow.SupportLevel, is_terminal: bool
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) -> void:
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var feedback: Control = preload("res://scenes/ui/feedback_panel.tscn").instantiate()
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_overlay_container.add_child(feedback)
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feedback.show_result(result, support_level)
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feedback.continue_pressed.connect(_on_feedback_continued.bind(feedback, is_terminal))
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func _on_feedback_continued(feedback: Control, is_terminal: bool) -> void:
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feedback.queue_free()
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if not is_terminal:
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_attempt_number += 1
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return
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_current_difficulty = ProgressManager.next_difficulty_for_skill(
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_skill_id, _current_difficulty
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)
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_last_exercise_id = _current_exercise.get("id", "")
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_completed_count += 1
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if _completed_count >= MISSION_LENGTH:
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GameManager.goto(GameManager.SCENE_REWARD)
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else:
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_load_next_exercise()
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