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#!/usr/bin/env python3
import requests
import xml.etree.ElementTree as ET
def get_warehouse_stock(product_name):
"""B2B API'den mağaza stok bilgilerini çek - İyileştirilmiş versiyon"""
try:
import re
warehouse_url = 'https://video.trek-turkey.com/bizimhesap-warehouse-xml.php'
response = requests.get(warehouse_url, verify=False, timeout=15)
if response.status_code != 200:
return None
root = ET.fromstring(response.content)
# Turkish character normalization function
turkish_map = {'ı': 'i', 'ğ': 'g', 'ü': 'u', 'ş': 's', 'ö': 'o', 'ç': 'c', 'İ': 'i', 'I': 'i'}
def normalize_turkish(text):
import unicodedata
text = unicodedata.normalize('NFD', text)
text = ''.join(char for char in text if unicodedata.category(char) != 'Mn')
for tr_char, en_char in turkish_map.items():
text = text.replace(tr_char, en_char)
return text
# Normalize search product name
search_name = normalize_turkish(product_name.lower().strip())
search_name = search_name.replace('(2026)', '').replace('(2025)', '').replace(' gen 3', '').replace(' gen', '').strip()
search_words = search_name.split()
print(f"DEBUG: Aranan ürün: '{product_name}' -> normalize: '{search_name}' -> kelimeler: {search_words}")
best_matches = []
exact_matches = []
color_size_matches = [] # For size/color specific searches
# Check if this is a size/color query (like "M Turuncu")
is_size_color_query = len(search_words) <= 2 and any(word in ['s', 'm', 'l', 'xl', 'xs', 'small', 'medium', 'large', 'turuncu', 'siyah', 'beyaz', 'mavi', 'kirmizi', 'yesil'] for word in search_words)
if is_size_color_query:
print(f"DEBUG: Beden/renk araması algılandı: {search_words}")
# For size/color queries, look for products containing these terms
for product in root.findall('Product'):
product_name_elem = product.find('ProductName')
if product_name_elem is not None and product_name_elem.text:
xml_product_name = product_name_elem.text.strip()
normalized_xml = normalize_turkish(xml_product_name.lower())
# Check if all search words appear in the product name
if all(word in normalized_xml for word in search_words):
color_size_matches.append((product, xml_product_name, normalized_xml))
print(f"DEBUG: BEDEN/RENK EŞLEŞME: '{xml_product_name}'")
candidates = color_size_matches
else:
# Normal product search logic
# İlk geçiş: Tam eşleşmeleri bul
for product in root.findall('Product'):
product_name_elem = product.find('ProductName')
if product_name_elem is not None and product_name_elem.text:
xml_product_name = product_name_elem.text.strip()
normalized_xml = normalize_turkish(xml_product_name.lower())
normalized_xml = normalized_xml.replace('(2026)', '').replace('(2025)', '').replace(' gen 3', '').replace(' gen', '').strip()
xml_words = normalized_xml.split()
# Tam eşleşme kontrolü - ilk iki kelime tam aynı olmalı
if len(search_words) >= 2 and len(xml_words) >= 2:
search_key = f"{search_words[0]} {search_words[1]}"
xml_key = f"{xml_words[0]} {xml_words[1]}"
if search_key == xml_key:
exact_matches.append((product, xml_product_name, normalized_xml))
print(f"DEBUG: TAM EŞLEŞME: '{xml_product_name}'")
# Eğer tam eşleşme varsa, sadece onları kullan
candidates = exact_matches if exact_matches else []
# Eğer tam eşleşme yoksa, fuzzy matching yap
if not candidates:
print("DEBUG: Tam eşleşme yok, fuzzy matching yapılıyor...")
for product in root.findall('Product'):
product_name_elem = product.find('ProductName')
if product_name_elem is not None and product_name_elem.text:
xml_product_name = product_name_elem.text.strip()
normalized_xml = normalize_turkish(xml_product_name.lower())
normalized_xml = normalized_xml.replace('(2026)', '').replace('(2025)', '').replace(' gen 3', '').replace(' gen', '').strip()
xml_words = normalized_xml.split()
# Ortak kelime sayısını hesapla
common_words = set(search_words) & set(xml_words)
# En az 2 ortak kelime olmalı VE ilk kelime aynı olmalı (marka kontrolü)
if (len(common_words) >= 2 and
len(search_words) > 0 and len(xml_words) > 0 and
search_words[0] == xml_words[0]):
best_matches.append((product, xml_product_name, normalized_xml, len(common_words)))
print(f"DEBUG: FUZZY EŞLEŞME: '{xml_product_name}' (ortak: {len(common_words)})")
# En çok ortak kelimeye sahip olanları seç
if best_matches:
max_common = max(match[3] for match in best_matches)
candidates = [(match[0], match[1], match[2]) for match in best_matches if match[3] == max_common]
print(f"DEBUG: Toplam {len(candidates)} aday ürün bulundu")
# Stok bilgilerini topla ve tekrarları önle
warehouse_stock_map = {} # warehouse_name -> total_stock
for product, xml_name, _ in candidates:
warehouses = product.find('Warehouses')
if warehouses is not None:
for warehouse in warehouses.findall('Warehouse'):
name_elem = warehouse.find('Name')
stock_elem = warehouse.find('Stock')
if name_elem is not None and stock_elem is not None:
warehouse_name = name_elem.text if name_elem.text else "Bilinmeyen"
try:
stock_count = int(stock_elem.text) if stock_elem.text else 0
if stock_count > 0:
# Aynı mağaza için stokları topla
if warehouse_name in warehouse_stock_map:
warehouse_stock_map[warehouse_name] += stock_count
else:
warehouse_stock_map[warehouse_name] = stock_count
print(f"DEBUG: STOK BULUNDU - {warehouse_name}: {stock_count} adet ({xml_name})")
except (ValueError, TypeError):
pass
if warehouse_stock_map:
# Mağaza stoklarını liste halinde döndür
all_warehouse_info = []
for warehouse_name, total_stock in warehouse_stock_map.items():
all_warehouse_info.append(f"{warehouse_name}: {total_stock} adet")
return all_warehouse_info
else:
print("DEBUG: Hiçbir mağazada stok bulunamadı")
return ["Hiçbir mağazada stokta bulunmuyor"]
except Exception as e:
print(f"Mağaza stok bilgisi çekme hatası: {e}")
return None
if __name__ == "__main__":
# Test the function with different M Turuncu variations
test_cases = [
"M Turuncu",
"m turuncu",
"M TURUNCU",
"Medium Turuncu",
"Marlin 6 M Turuncu"
]
for test_case in test_cases:
print(f"=== Testing: {test_case} ===")
result = get_warehouse_stock(test_case)
print(f"Result: {result}")
print() |