Sprint 1 : scaffolding complet de Glibredecision

Plateforme de decisions collectives pour Duniter/G1.
Backend FastAPI async + PostgreSQL (14 tables, 8 routers, 6 services,
moteur de vote avec formule d'inertie WoT/Smith/TechComm).
Frontend Nuxt 4 + Nuxt UI v3 + Pinia (9 pages, 5 stores).
Infrastructure Docker + Woodpecker CI + Traefik.
Documentation technique et utilisateur (15 fichiers).
Seed : Licence G1, Engagement Forgeron v2.0.0, 4 protocoles de vote.
30 tests unitaires (formules, mode params, vote nuance) -- tous verts.

Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>

backend/app/tests/test_nuanced.py

@@ -0,0 +1,120 @@
+"""Tests for six-level nuanced vote evaluation.
+
+Levels: 0-CONTRE, 1-PAS DU TOUT, 2-PAS D'ACCORD, 3-NEUTRE, 4-D'ACCORD, 5-TOUT A FAIT
+Positive = levels 3 + 4 + 5
+Adoption requires: positive_pct >= threshold (80%) AND total >= min_participants (59).
+"""
+
+import pytest
+
+from app.engine.nuanced_vote import evaluate_nuanced
+
+
+class TestNuancedVoteAdoption:
+    """Cases where the vote should be adopted."""
+
+    def test_59_positive_10_negative_adopted(self):
+        """59 positive (levels 3-5) + 10 negative = 69 total.
+        positive_pct = 59/69 ~ 85.5% >= 80% and 69 >= 59 => adopted.
+        """
+        votes = [5] * 20 + [4] * 20 + [3] * 19 + [2] * 5 + [1] * 3 + [0] * 2
+        result = evaluate_nuanced(votes, threshold_pct=80, min_participants=59)
+
+        assert result["total"] == 69
+        assert result["positive_count"] == 59
+        assert result["positive_pct"] == pytest.approx(85.51, abs=0.1)
+        assert result["threshold_met"] is True
+        assert result["min_participants_met"] is True
+        assert result["adopted"] is True
+
+    def test_all_tout_a_fait_adopted(self):
+        """All 59 voters at level 5 => 100% positive, adopted."""
+        votes = [5] * 59
+        result = evaluate_nuanced(votes, threshold_pct=80, min_participants=59)
+
+        assert result["total"] == 59
+        assert result["positive_count"] == 59
+        assert result["positive_pct"] == 100.0
+        assert result["adopted"] is True
+
+
+class TestNuancedVoteRejection:
+    """Cases where the vote should be rejected."""
+
+    def test_40_positive_30_negative_rejected(self):
+        """40 positive + 30 negative = 70 total.
+        positive_pct = 40/70 ~ 57.14% < 80% => threshold not met.
+        """
+        votes = [5] * 15 + [4] * 15 + [3] * 10 + [2] * 10 + [1] * 10 + [0] * 10
+        result = evaluate_nuanced(votes, threshold_pct=80, min_participants=59)
+
+        assert result["total"] == 70
+        assert result["positive_count"] == 40
+        assert result["positive_pct"] == pytest.approx(57.14, abs=0.1)
+        assert result["threshold_met"] is False
+        assert result["min_participants_met"] is True  # 70 >= 59
+        assert result["adopted"] is False
+
+    def test_min_participants_not_met(self):
+        """50 positive + 5 negative = 55 total < 59 min_participants.
+        Even though 50/55 ~ 90.9% > 80%, adoption fails on min_participants.
+        """
+        votes = [5] * 30 + [4] * 10 + [3] * 10 + [1] * 3 + [0] * 2
+        result = evaluate_nuanced(votes, threshold_pct=80, min_participants=59)
+
+        assert result["total"] == 55
+        assert result["positive_count"] == 50
+        assert result["positive_pct"] > 80
+        assert result["threshold_met"] is True
+        assert result["min_participants_met"] is False
+        assert result["adopted"] is False
+
+
+class TestNuancedVoteEdgeCases:
+    """Edge cases and exact boundary conditions."""
+
+    def test_exact_threshold_80_percent(self):
+        """Exactly 80% positive votes should pass the threshold."""
+        # 80 positive out of 100 = exactly 80%
+        votes = [5] * 40 + [4] * 20 + [3] * 20 + [2] * 10 + [1] * 5 + [0] * 5
+        result = evaluate_nuanced(votes, threshold_pct=80, min_participants=59)
+
+        assert result["total"] == 100
+        assert result["positive_count"] == 80
+        assert result["positive_pct"] == 80.0
+        assert result["threshold_met"] is True
+        assert result["min_participants_met"] is True
+        assert result["adopted"] is True
+
+    def test_just_below_threshold(self):
+        """79 positive out of 100 = 79% < 80% => rejected."""
+        votes = [5] * 39 + [4] * 20 + [3] * 20 + [2] * 11 + [1] * 5 + [0] * 5
+        result = evaluate_nuanced(votes, threshold_pct=80, min_participants=59)
+
+        assert result["total"] == 100
+        assert result["positive_count"] == 79
+        assert result["positive_pct"] == 79.0
+        assert result["threshold_met"] is False
+        assert result["adopted"] is False
+
+    def test_empty_votes(self):
+        """Zero votes => not adopted."""
+        result = evaluate_nuanced([], threshold_pct=80, min_participants=59)
+        assert result["total"] == 0
+        assert result["positive_count"] == 0
+        assert result["positive_pct"] == 0.0
+        assert result["adopted"] is False
+
+    def test_invalid_vote_level(self):
+        """Vote level outside 0-5 raises ValueError."""
+        with pytest.raises(ValueError, match="invalide"):
+            evaluate_nuanced([5, 3, 6])
+
+    def test_per_level_counts(self):
+        """Verify per-level breakdown is correct."""
+        votes = [0, 1, 2, 3, 4, 5, 5, 4, 3]
+        result = evaluate_nuanced(votes, threshold_pct=50, min_participants=1)
+
+        assert result["per_level_counts"] == {0: 1, 1: 1, 2: 1, 3: 2, 4: 2, 5: 2}
+        assert result["positive_count"] == 6  # 2+2+2
+        assert result["total"] == 9