"""
SonarQube-Daten analysieren: Coverage und Smells pro Service/Team.
Filtert auf master/main Branches und ordnet Services den Teams zu.
"""
import csv
from collections import defaultdict

CSV_PATH = "project-audit/data/sonarqube/sonarqube-metrics.csv"

# Team-Zuordnung der Services
TEAM_MAP = {
    "portal-ui": "404",
    "portal-middleware": "404",
    "portal-mw": "404",
    "steuerung-vertrieb": "CIB",
    "sv-": "CIB",
    "auftrags-verwaltung": "CIB",
    "av-": "CIB",
    "auftrag-service": "CIB",
    "archivierungsservice": "CIB",
    "common-interface": "Zero",
    "ci-": "Zero",
    "tadef": "Zero",
    "stammdaten": "Zero",
    "stb-": "Zero",
    "acat": "Zero",
    "vertragsdaten": "Zero",
    "vdv": "Zero",
    "ifp": "CIB",
    "kundendaten": "CIB",
    "kdv": "CIB",
    "rabatt": "CIB",
    "core-component": "Shared",
    "signature": "Shared",
    "logging": "Shared",
}

def get_team(name):
    name_lower = name.lower()
    for pattern, team in TEAM_MAP.items():
        if pattern in name_lower:
            return team
    return "Andere"

# Daten laden (nur master/main)
data = []
with open(CSV_PATH, "r", encoding="utf-8") as f:
    reader = csv.DictReader(f, delimiter=";", quotechar='"')
    for row in reader:
        name = row.get("Name", "")
        if name.endswith("-master") or name.endswith("-main"):
            lines = int(row.get("Lines", "0") or "0")
            if lines > 0:  # Nur Projekte mit Code
                data.append({
                    "name": name.replace("-master", "").replace("-main", ""),
                    "lines": lines,
                    "bugs": int(row.get("Bugs", "0") or "0"),
                    "smells": int(row.get("CodeSmells", "0") or "0"),
                    "coverage": float(row.get("Coverage", "0") or "0"),
                    "duplications": float(row.get("Duplications", "0") or "0"),
                    "qgate": row.get("QualityGate", "?"),
                    "team": get_team(name),
                })

# Sortiert nach Lines
data.sort(key=lambda x: x["lines"], reverse=True)

print(f"=== SonarQube Analyse (nur master/main, {len(data)} Projekte mit Code) ===")
print()

# Top 20 nach Groesse
print("--- Top 20 Projekte nach Groesse ---")
print(f"{'Projekt':<40} {'Lines':>7} {'Bugs':>5} {'Smells':>7} {'Cov%':>6} {'QGate':>6} {'Team':<8}")
print("-" * 85)
for row in data[:20]:
    cov_str = f"{row['coverage']:.1f}" if row['coverage'] > 0 else "-"
    print(f"{row['name']:<40} {row['lines']:>7} {row['bugs']:>5} {row['smells']:>7} {cov_str:>6} {row['qgate']:>6} {row['team']:<8}")

# Team-Aggregation
print()
print("--- Aggregation pro Team ---")
teams = defaultdict(lambda: {"lines": 0, "bugs": 0, "smells": 0, "cov_weighted": 0, "projects": 0, "qgate_ok": 0, "qgate_err": 0})
for row in data:
    t = teams[row["team"]]
    t["lines"] += row["lines"]
    t["bugs"] += row["bugs"]
    t["smells"] += row["smells"]
    t["cov_weighted"] += row["coverage"] * row["lines"]
    t["projects"] += 1
    if row["qgate"] == "OK":
        t["qgate_ok"] += 1
    else:
        t["qgate_err"] += 1

print(f"{'Team':<10} {'Projekte':>8} {'Lines':>8} {'Bugs':>5} {'Smells':>7} {'Smells/1K':>9} {'Cov%':>6} {'QGate OK':>8}")
print("-" * 75)
for team in ["404", "CIB", "Zero", "Shared", "Andere"]:
    if team in teams:
        t = teams[team]
        smells_per_k = (t["smells"] / t["lines"] * 1000) if t["lines"] > 0 else 0
        avg_cov = (t["cov_weighted"] / t["lines"]) if t["lines"] > 0 else 0
        qgate_str = f"{t['qgate_ok']}/{t['projects']}"
        print(f"{team:<10} {t['projects']:>8} {t['lines']:>8} {t['bugs']:>5} {t['smells']:>7} {smells_per_k:>9.1f} {avg_cov:>6.1f} {qgate_str:>8}")

# Projekte ohne Coverage
print()
print("--- Projekte OHNE Coverage (0% oder keine Daten) ---")
no_cov = [r for r in data if r["coverage"] == 0 and r["lines"] > 500]
no_cov.sort(key=lambda x: x["lines"], reverse=True)
for row in no_cov:
    print(f"  {row['name']:<40} {row['lines']:>7} Lines  {row['team']:<8}")

# Quality Gate Failures
print()
print("--- Quality Gate FAILED (ERROR) ---")
failed = [r for r in data if r["qgate"] == "ERROR"]
failed.sort(key=lambda x: x["lines"], reverse=True)
for row in failed[:15]:
    cov_str = f"{row['coverage']:.1f}%" if row['coverage'] > 0 else "0%"
    print(f"  {row['name']:<40} {row['lines']:>7} Lines  Bugs={row['bugs']} Smells={row['smells']} Cov={cov_str}  {row['team']}")