725 lines
31 KiB
Python
725 lines
31 KiB
Python
from json import load, loads
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from os.path import abspath
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from bs4 import BeautifulSoup
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from lxml import etree
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from re import split
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import re
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import json
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import os
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def extract_components_zarahome(parts):
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composition = []
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for part in parts:
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if part.get("areas") and part.get("description"):
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if len(parts) != 1:
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composition.append(part["description"])
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for area in part["areas"]:
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area_name = area["description"]
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percentage_area = area["percentageArea"]
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composition.append(f"{area_name} ({percentage_area})")
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for component in area["components"]:
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material = component["material"]
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percentage = component["percentage"]
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composition.append(f"{percentage} {material}")
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elif part.get("components") and part.get("description"):
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if len(parts) != 1:
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composition.append(part["description"])
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for component in part["components"]:
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material = component["material"]
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percentage = component["percentage"]
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composition.append(f"{percentage} {material}")
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return composition
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# класс для извлечения нужных данных
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class Extractor:
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def __init__(self, json_data):
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self.methods = {
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"": (self.default_extract_method, []),
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"zarahome": (self.zarahome_extract_method, [
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"Краткое описание",
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"Артикул",
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"Название товара или услуги",
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"Полное описание",
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"Образец цвета",
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"Свойство: Цвет",
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"Свойство: Размер",
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"Цена закупки",
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"Свойство: Вес(г)",
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"Изображения",
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"Изображения варианта",
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"Параметр: Состав",
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"Параметр: Уход",
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"Параметр: Происхождение",
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"Размещение на сайте",
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"Свойство: Бренд"
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]),
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"eobuwie": (self.eobuwie_extract_method, [
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"Краткое описание",
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"Артикул",
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"Свойство: Размер",
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"Полное описание(Таблица)",
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"Название товара или услуги",
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"Изображения",
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"Размещение на сайте",
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"Цена",
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"Наличие"
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]),
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"decathlon": (self.decathlon_extract_method, [
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"Краткое описание",
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"Артикул",
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"Название товара или услуги",
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"Полное описание",
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"Наличие",
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"Свойство: Цвет",
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"Свойство: Размер",
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"Цена закупки",
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"Параметр: Вес(г)",
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"Изображения варианта",
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"Размещение на сайте"
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])
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}
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self.method = json_data["method"]
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self.tags = json_data["tags"]
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self.headers = self.methods[self.method][1]
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for tag in self.tags:
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self.headers.insert(tag["column_number"], tag["column_name"])
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def extract(self, parser, recorder, categories):
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self.methods[self.method][0](parser, recorder, categories)
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def default_extract_method(self):
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pass
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def tags_extract(self, soup, row):
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dom_tree = etree.HTML(str(soup))
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for tag in self.tags:
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xpath_result = dom_tree.xpath(tag["xpath"])
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column_data = ""
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if len(xpath_result):
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for element in xpath_result:
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column_data = ''.join(element.itertext()).strip() + "\n"
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row.insert(tag["column_number"], column_data)
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def decathlon_extract_method(self, parser, recorder, categories):
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BASE_URL = "https://www.decathlon.pl"
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for i, category in enumerate(categories):
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csv_name = "_".join(category.split("/")[4:]).replace(":", "-").replace("?", "_").replace("=", "_")
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filepath = os.path.join(recorder.record_folder, f"{csv_name}.xlsx")
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# Проверяем наличие файла, и если он есть — пропускаем парсинг категории
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if os.path.isfile(filepath):
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print(f"Файл {csv_name}.xlsx уже существует. Пропускаем категорию: {category}")
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continue
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table = [self.headers]
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print(f"Categories: {i + 1} / {len(categories)}", category)
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continue_loop = True
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category_from = 0
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while continue_loop:
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# Дальше без изменений твой текущий код
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category_page = parser.parse(f"{category}?from={category_from}")
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category_soup = BeautifulSoup(category_page, "html.parser")
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dom_tree = etree.HTML(str(category_soup))
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offers_count_element = dom_tree.xpath('//*[@id="start-of-listing"]/div[2]/div/span[1]')
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if offers_count_element:
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offers_count = int(offers_count_element[0].text.strip())
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else:
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print("Не найдено количество товаров")
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offers_count = 0
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break # если не нашли количество товаров, нет смысла продолжать
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products_links = category_soup.select('a.dpb-product-link')
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products_links_count = len(products_links)
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for e, product_link in enumerate(products_links):
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product_url = BASE_URL + product_link.get("href")
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print(f"Products: {e + 1 + category_from} / {offers_count}", product_url)
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product_page = parser.parse(product_url)
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if product_page == None:
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continue
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soup = BeautifulSoup(product_page, "html.parser")
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meta_script_tags = soup.select("[type=\"application/ld+json\"]")
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if len(meta_script_tags) <= 1:
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continue
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meta_data = loads(meta_script_tags[1].text)
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path_steps = []
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for step in meta_data["itemListElement"]:
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path_steps.append(step["item"]["name"])
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product_path = "decathlon/" + "/".join(path_steps)
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script_json = soup.select("#__dkt")[0].text
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# Находим начало JSON
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json_start_match = re.search(r'__DKT\s*=\s*({)', script_json)
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if json_start_match:
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# Индекс начала JSON-объекта
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start = json_start_match.start(1)
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# Считаем баланс фигурных скобок, чтобы извлечь точный JSON
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bracket_count = 0
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for i in range(start, len(script_json)):
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if script_json[i] == '{':
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bracket_count += 1
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elif script_json[i] == '}':
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bracket_count -= 1
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if bracket_count == 0:
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# JSON найден полностью
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json_text = script_json[start:i+1]
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break
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else:
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print("Ошибка: JSON не сбалансирован.")
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continue
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# Теперь парсим
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try:
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__dkt = json.loads(json_text)
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except json.JSONDecodeError as e:
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print(f"Ошибка парсинга JSON: {e}")
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continue
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else:
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print("Ошибка: не найдено начало JSON (__DKT).")
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continue
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#__dkt = loads(script_json.text.replace("__DKT = ", ""))
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#try:
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# __dkt = json.loads(json_text)
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#except json.JSONDecodeError as e:
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# print(f"Ошибка парсинга JSON: {e}")
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# continue
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# Отладочный вывод структуры данных
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#print(json.dumps(__dkt["_ctx"]["data"], indent=2)[:2000])
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#if __dkt["_ctx"]["page"]["id"] != "product":
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# continue
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########было вот так models_data = __dkt["_ctx"]["data"][4]["data"]["models"]
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# Новый правильный путь
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model_info = __dkt["_ctx"]["data"][2]["data"]
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if "models" not in model_info or not model_info["models"]:
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print(f"Ошибка: нет 'models' для товара {product_url}")
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continue
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model = model_info["models"][0]
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# print(json.dumps(model_info, indent=2)) #### Отадка посмотреть что в json
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color = ""
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colors = []
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# проверь есть ли сейчас colors в новой структуре, возможно нужно будет адаптировать и это
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if model.get("colors"):
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for color_info in model["colors"]:
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# Берём label, если нет — name, если и этого нет — id
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label = color_info.get("label") or color_info.get("name") or color_info.get("title") or color_info.get("id") or ""
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if label:
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colors.append(label.strip())
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color = " / ".join(colors)
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else:
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color = ""
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images = []
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if model.get("images"):
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for image_info in model["images"]["product"]:
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images.append(image_info["url"].replace("/250x250", ""))
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image_lines = "\n".join(images)
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product_name = model["webLabel"]
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#product_description = soup.select("[id^=\"ProductFunctionalities\"]") ТАК БЫЛО
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description_parts = []
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description_set = set() # Для проверки уникальности
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def add_unique_description(text):
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text_cleaned = text.strip()
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if text_cleaned and text_cleaned not in description_set:
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description_parts.append(text_cleaned)
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description_set.add(text_cleaned)
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# 1. MarketplaceProductDescription
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description_data = next((item for item in __dkt["_ctx"]["data"] if item["type"] == "MarketplaceProductDescription"), None)
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if description_data and "data" in description_data and "description" in description_data["data"]:
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add_unique_description(description_data["data"]["description"])
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# 2. ProductConception
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description_data = next((item for item in __dkt["_ctx"]["data"] if item["type"] == "ProductConception"), None)
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if description_data and "data" in description_data and "conception" in description_data["data"]:
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conception = description_data["data"]["conception"]
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if isinstance(conception, list) and conception:
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conception_text = conception[0].get("description", "")
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add_unique_description(conception_text)
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# 3. ProductFunctionalities
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description_data = next((item for item in __dkt["_ctx"]["data"] if item["type"] == "ProductFunctionalities"), None)
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if description_data and "data" in description_data and "functionalities" in description_data["data"]:
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functionalities = description_data["data"]["functionalities"]
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if isinstance(functionalities, list):
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func_text = "\n".join(f"{func.get('title', '')}: {func.get('value', '')}" for func in functionalities)
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add_unique_description(func_text)
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# 4. MarketplaceProductTechnicalInformations
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tech_info = next((item for item in __dkt["_ctx"]["data"] if item["type"] == "MarketplaceProductTechnicalInformations"), None)
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if tech_info and "data" in tech_info and "information" in tech_info["data"]:
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information = tech_info["data"]["information"]
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if isinstance(information, list):
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info_text = "\n".join(f"{info.get('key', '')}: {info.get('value', '')}" for info in information)
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add_unique_description(info_text)
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# 5. ProductGuarantee
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# guarantee_data = next((item for item in __dkt["_ctx"]["data"] if item["type"] == "ProductGuarantee"), None)
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# if guarantee_data and "data" in guarantee_data and "guarantee" in guarantee_data["data"]:
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# guarantee_text = f"Gwarancja: {guarantee_data['data']['guarantee']} lat"
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# add_unique_description(guarantee_text)
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# 6. ProductBenefits
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benefits_data = next((item for item in __dkt["_ctx"]["data"] if item["type"] == "ProductBenefits"), None)
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if benefits_data and "data" in benefits_data and "benefits" in benefits_data["data"]:
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benefits = benefits_data["data"]["benefits"]
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if isinstance(benefits, list):
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benefits_text = "\n".join(f"{benefit.get('label', '')}: {benefit.get('value', '')}" for benefit in benefits)
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add_unique_description(benefits_text)
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# Соединяем все уникальные описания через двойной перевод строки
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product_description = "\n\n".join(description_parts)
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# Проверочный вывод (первые 500 символов)
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#print("Полное описание продукта:", product_description[:500])
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# Дальше извлекаем данные о SKU и т.д., аналогично проверяя новые структуры
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skus_data = model["skus"]
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sku_ids = []
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for sku in skus_data:
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sku_ids.append(sku["skuId"])
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sku_ids = ",".join(sku_ids)
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stocks = parser.parse(f"https://www.decathlon.pl/pl/ajax/nfs/stocks/online?skuIds={sku_ids}", return_type="json")
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for sku in skus_data:
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try:
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sku_id = sku["skuId"]
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sku_id1 = model["modelId"]
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stock = stocks[sku_id]["stockOnline"] if stocks.get(sku_id) else "unknown"
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table_data = []
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# Старый метод - не хорошо для существующих товаров на ОЗОН
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#article = f'{sku_id1}-{sku_id}'
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#article = sku_id1.split("-")[-1]
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# Извлекаем article из product_url
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article = ""
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try:
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base_part = product_url.split("?")[0] # убираем всё после ?
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article_part = base_part.split("-")[-1]
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article = f"{article_part}_Decathlon" # берём часть после последнего дефиса
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except Exception:
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article = ""
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size = ""
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if sku.get("size"):
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size = sku["size"]
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price = ""
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if sku.get("price"):
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price = sku["price"]
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weight = ""
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if sku.get("grossWeight"):
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weight = float(sku["grossWeight"])
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table_data.append([
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product_url,
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article,
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product_name,
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product_description,
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stock,
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color,
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size,
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price,
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weight,
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image_lines,
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product_path
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])
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self.tags_extract(soup, table_data[-1])
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table += table_data.copy()
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except Exception as error:
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print(f"Extractor Error: {error}")
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if offers_count == products_links_count + category_from:
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continue_loop = False
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else:
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category_from += products_links_count
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csv_name = "_".join(category.split("/")[4:]).replace(":", "-").replace("?", "_").replace("=", "_")
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recorder.record(csv_name, table)
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def eobuwie_extract_method(self, parser, recorder, categories):
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for i, category in enumerate(categories):
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table = [self.headers]
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print(f"Categories: {i + 1} / {len(categories)}", category)
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category_page = 1
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category_marka = category.split(":")[2].split("?")[0]
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category_type = category.split("/")[4]
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while True:
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category_products_data = parser.parse(f"https://eobuwie.com.pl/t-api/rest/search/eobuwie/v5/search?channel=eobuwie¤cy=PLN&locale=pl_PL&limit=100&page={category_page}&filters[marka][in][]={category_marka}&categories[]={category_type}&select[]=url_key&select[]=product_group_associated&select[]=images&select[]=final_price&select[]=footwear_size&select_locales[]=pl_PL", return_type="json")
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total = category_products_data["total"]
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products = category_products_data["products"]
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for e, product in enumerate(products):
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short_url = product["values"]["url_key"]["value"]["pl_PL"]
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product_url = f"https://eobuwie.com.pl/p/{short_url}"
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print(f"Products: {e + 1 + ((category_page - 1) * 100)} / {total}", product_url)
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product_page = parser.parse(product_url)
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if product_page == None:
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continue
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soup = BeautifulSoup(product_page, "html.parser")
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links = soup.select(".breadcrumb-list .text-link")[2:]
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product_location = "/".join(list(map(lambda x: x.text, links)))
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product_group = ""
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if product["values"].get("product_group_associated") and product["values"]["product_group_associated"].get("value"):
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product_group = product["values"]["product_group_associated"]["value"]
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product_name = soup.select("[data-test-id=\"product-name\"]")[0].text.strip()
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product_name = split(r"\d", product_name)[0]
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product_name = f"{product_name} - {product_group}"
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images_list = []
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if product["values"].get("images") and product["values"]["images"].get("value"):
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for image in product["values"]["images"]["value"]:
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if image.get("url"):
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images_list.append(f'https://img.modivo.cloud/productcard({image["url"]},jpg)')
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images_list = "\n".join(images_list)
|
||
|
||
for i, variant in enumerate(product["variants"].values()):
|
||
try:
|
||
table_data = []
|
||
|
||
size_url = variant["size"]
|
||
|
||
variant_url = f"{product_url}?size={size_url}"
|
||
|
||
article = variant["id"]
|
||
|
||
size_name = ""
|
||
|
||
if variant["values"].get("footwear_size"):
|
||
|
||
size_name = variant["values"]["footwear_size"]["value"]["label"]
|
||
|
||
description = ""
|
||
|
||
location = f"Каталог/Обувь и аксессуары/{product_location}"
|
||
|
||
availability = variant["stock_quantity"]
|
||
|
||
if variant["stock_quantity"]:
|
||
price = variant["offers"][0]["final_price"]["amount"]
|
||
else:
|
||
price = product["values"]["final_price"]["value"]["pl_PL"]["PLN"]["amount"]
|
||
|
||
table_data.append([
|
||
variant_url,
|
||
article,
|
||
size_name,
|
||
description,
|
||
product_name,
|
||
images_list,
|
||
location,
|
||
price,
|
||
availability
|
||
])
|
||
|
||
self.tags_extract(soup, table_data[-1])
|
||
|
||
table += table_data.copy()
|
||
|
||
except Exception as error:
|
||
print(f"Extractor Error: {error}")
|
||
|
||
|
||
if category_page * 100 >= total:
|
||
break
|
||
|
||
category_page += 1
|
||
|
||
|
||
csv_name = category.split("/")[-1].replace(":", "-").replace("?", "_").replace("=", "_")
|
||
recorder.record(csv_name, table)
|
||
|
||
def zarahome_extract_method(self, parser, recorder, categories):
|
||
|
||
for i, category in enumerate(categories):
|
||
table = [self.headers]
|
||
|
||
print(f"Categories: {i + 1} / {len(categories)}", category)
|
||
|
||
category_seo = parser.parse(f"{category}?itxSeo=true", return_type="json")
|
||
|
||
category_id = category_seo["categoryId"]
|
||
|
||
category_title = "/".join(category_seo["metaTitle"].split(" | ")[0].split(" - ")[::-1])
|
||
|
||
category_products_data = parser.parse(f"https://www.zarahome.com/itxrest/3/catalog/store/85009924/80290000/category/{category_id}/product?showProducts=true&languageId=-22&appId=1", return_type="json")
|
||
|
||
products = category_products_data["products"].values()
|
||
|
||
for e, product in enumerate(products):
|
||
|
||
if product.get("productUrlParam"):
|
||
continue
|
||
|
||
short_url = product.get("productUrl")
|
||
|
||
print(f"Products: {e + 1} / {len(products)}", f"https://www.zarahome.com/pl/{short_url}")
|
||
|
||
product_reference_id = product["detail"]["reference"].split("-")[0][1:9]
|
||
|
||
product_url = f"https://www.zarahome.com/itxrest/3/catalog/store/85009924/80290000/productsArray?languageId=-22&referenceIds={product_reference_id}&appId=1"
|
||
|
||
product_json = parser.parse(product_url, return_type="json")
|
||
|
||
if not product_json["products"][0].get("productUrl"):
|
||
continue
|
||
|
||
try:
|
||
table_data = []
|
||
|
||
category_path = f"Каталог/ZaraHome/{category_title}"
|
||
|
||
product_short_url = product_json["products"][0]["productUrl"]
|
||
|
||
url = f"https://www.zarahome.com/pl/{product_short_url}"
|
||
|
||
article = product_json["products"][0]["detail"]["displayReference"]
|
||
|
||
name = product_json["products"][0]["name"]
|
||
|
||
description = product_json["products"][0]["detail"]["longDescription"]
|
||
|
||
all_images = []
|
||
for location in product_json["products"][0]["detail"]["xmedia"]:
|
||
path = location["path"]
|
||
for media in location["xmediaItems"][0]["medias"]:
|
||
id_media = media["idMedia"]
|
||
|
||
all_images.append(f"https://static.zarahome.net/8/photos4{path}/{id_media}2.jpg")
|
||
|
||
all_images = "\n".join(all_images)
|
||
|
||
components = product_json["products"][0]["detail"]["compositionDetail"]
|
||
|
||
if components:
|
||
components = components["parts"]
|
||
else:
|
||
components = product_json["products"][0]["detail"]["colors"][0]["compositionDetail"]
|
||
if components:
|
||
components = components["parts"]
|
||
else:
|
||
components = {}
|
||
|
||
if components != {}:
|
||
composition = extract_components_zarahome(components)
|
||
|
||
composition = "\n".join(composition)
|
||
else:
|
||
composition = ""
|
||
|
||
care = []
|
||
for part in product_json["products"][0]["detail"]["care"]:
|
||
care_description = part["description"]
|
||
|
||
care.append(care_description)
|
||
|
||
care = "\n".join(care)
|
||
|
||
traceability = []
|
||
for part in product_json["products"][0]["detail"]["colors"][0]["traceability"].values():
|
||
if type(part) is dict and part.get("country") and part.get("name"):
|
||
traceability_name = part["name"]
|
||
traceability_country = "\n".join(part["country"])
|
||
|
||
traceability.append(f"{traceability_name}\n{traceability_country}")
|
||
|
||
traceability = "\n".join(traceability)
|
||
|
||
|
||
number = 0
|
||
|
||
for i, color in enumerate(product_json["products"][0]["detail"]["colors"]):
|
||
|
||
if color["image"] == None:
|
||
continue
|
||
color_code = color["id"]
|
||
|
||
current_images = []
|
||
for location in product_json["products"][0]["detail"]["xmedia"]:
|
||
if location["colorCode"] == color_code:
|
||
path = location["path"]
|
||
for media in location["xmediaItems"][0]["medias"]:
|
||
id_media = media["idMedia"]
|
||
|
||
current_images.append(
|
||
f"https://static.zarahome.net/8/photos4{path}/{id_media}2.jpg")
|
||
break
|
||
|
||
current_images = "\n".join(current_images)
|
||
|
||
color_url = color["image"]["url"]
|
||
color_image = f"https://static.zarahome.net/8/photos4{color_url}_3_1_5.jpg"
|
||
|
||
color_name = color["name"]
|
||
|
||
for e, size in enumerate(color["sizes"]):
|
||
|
||
if size["visibilityValue"] != "SHOW":
|
||
continue
|
||
|
||
article_number = "" if number == 0 else f"-{number}"
|
||
|
||
size_weight = size["weight"]
|
||
|
||
size_name = size["name"]
|
||
|
||
size_description = size["description"]
|
||
|
||
size_full_name = f"{size_description} ({size_name})" if size_description else size_name
|
||
|
||
size_buy_price = int(size["price"]) / 100
|
||
|
||
table_data.append([
|
||
url,
|
||
f"{article}{article_number}",
|
||
name,
|
||
description,
|
||
color_image,
|
||
color_name,
|
||
size_full_name,
|
||
size_buy_price,
|
||
size_weight,
|
||
all_images,
|
||
current_images,
|
||
composition,
|
||
care,
|
||
traceability,
|
||
category_path,
|
||
"ZARAHOME"
|
||
])
|
||
|
||
number += 1
|
||
|
||
table += table_data.copy()
|
||
except Exception as error:
|
||
print(f"Extractor Error: {error}")
|
||
|
||
|
||
csv_name = category.split("/")[-1]
|
||
recorder.record(csv_name, table)
|
||
|
||
def get_extractor():
|
||
with open(abspath("parse_settings.json"), "r", encoding="utf-8") as file:
|
||
return Extractor(load(file)) |