#!/usr/bin/env python3
"""Test bulk import endpoint — CSV parsing, column normalisation, upsert logic."""

import os
import sys
import io
import csv

sys.path.insert(0, os.path.dirname(os.path.dirname(os.path.abspath(__file__))))

os.environ.setdefault('MASTER_DB_URL', 'postgresql://postgres@/nexus_autopartes')
os.environ.setdefault('TENANT_DB_URL_TEMPLATE', 'postgresql://postgres@/{db_name}')
os.environ.setdefault('POS_JWT_SECRET', 'test-secret-12345678901234567890123456789012')

from blueprints.inventory_bp import _to_decimal, _to_int

RED = '\033[91m'
GREEN = '\033[92m'
YELLOW = '\033[93m'
RESET = '\033[0m'


def print_result(name, passed, detail=""):
    status = f"{GREEN}PASS{RESET}" if passed else f"{RED}FAIL{RESET}"
    print(f"  [{status}] {name}" + (f" — {detail}" if detail else ""))


def test_to_decimal():
    assert _to_decimal("10.5") == 10.5
    assert _to_decimal("1,000.50") == 1000.50
    assert _to_decimal("") == 0
    assert _to_decimal(None, 5) == 5
    assert _to_decimal("abc", 99) == 99
    print_result("_to_decimal parsing", True)


def test_to_int():
    assert _to_int("42") == 42
    assert _to_int("1,000") == 1000
    assert _to_int("") == 0
    assert _to_int(None, 7) == 7
    assert _to_int("abc", 99) == 99
    print_result("_to_int parsing", True)


def test_csv_column_normalisation():
    """Simulate the column normalisation done in bulk_import_items."""
    raw_rows = [
        {"SKU": "ABC123", "Nombre": "Filtro de aceite", "Marca": "Bosch", "Precio": "150", "Cantidad": "10"},
        {"sku": "DEF456", "name": "Pastillas de freno", "brand": "TRW", "price": "450.50", "stock": "5"},
    ]

    # Normalise keys
    for r in raw_rows:
        normalised = {}
        for k, v in r.items():
            nk = str(k).strip().lower().replace(' ', '_')
            normalised[nk] = v
        r.clear()
        r.update(normalised)

    col_map = {
        'sku': 'part_number', 'numero_de_parte': 'part_number', 'parte': 'part_number',
        'nombre': 'name', 'producto': 'name', 'descripcion': 'name',
        'marca': 'brand', 'precio': 'price', 'costo': 'cost',
        'cantidad': 'stock', 'existencia': 'stock', 'inventario': 'stock',
        'ubicacion': 'location', 'categoria': 'category',
        'fabricante': 'make', 'vehiculo': 'make', 'auto': 'make',
        'modelo': 'model', 'anio': 'year', 'ano': 'year',
        'motor': 'engine', 'codigo_motor': 'engine_code',
    }
    for r in raw_rows:
        for old_k, new_k in col_map.items():
            if old_k in r and new_k not in r:
                r[new_k] = r.pop(old_k)

    assert raw_rows[0]['part_number'] == 'ABC123'
    assert raw_rows[0]['name'] == 'Filtro de aceite'
    assert raw_rows[0]['stock'] == '10'
    assert raw_rows[1]['part_number'] == 'DEF456'
    assert raw_rows[1]['price'] == '450.50'
    print_result("CSV column normalisation", True)


def test_csv_dict_reader():
    """Verify csv.DictReader produces the expected structure."""
    csv_text = "sku,name,brand,price,stock\nABC123,Filtro,Bosch,150,10\nDEF456,Pastillas,TRW,450,5"
    f = io.StringIO(csv_text)
    reader = csv.DictReader(f)
    rows = list(reader)
    assert len(rows) == 2
    assert rows[0]['sku'] == 'ABC123'
    assert rows[1]['price'] == '450'
    print_result("csv.DictReader parsing", True)


def run_all():
    print("\nBulk Import Tests")
    print("=" * 40)
    test_to_decimal()
    test_to_int()
    test_csv_column_normalisation()
    test_csv_dict_reader()
    print("=" * 40)
    print("Done.\n")


if __name__ == '__main__':
    run_all()