Target est l’un des sites de commerce électronique les plus difficiles à pirater aujourd’hui. Entre les sélecteurs CSS dynamiques, le contenu chargé paresseusement et un puissant système de blocage, cela peut sembler impossible. À la fin de ce guide, vous serez capable de scraper Target comme un pro. Nous allons couvrir deux façons différentes d’extraire les listes de produits.
- Comment récupérer Target avec Python et Scraping Browser
- Comment gratter Target avec Claude et le serveur MCP de Bright Data
Comment récupérer des cibles avec Python
Nous allons passer en revue le processus de récupération manuelle des listes Target à l’aide de Python. Le contenu de Target est chargé dynamiquement, et les résultats sont donc souvent incomplets, au mieux, sans un navigateur sans tête. Tout d’abord, nous allons utiliser Requests et BeautifulSoup. Ensuite, nous extrairons le contenu avec Selenium.
Inspection du site
Avant de commencer à coder, nous devons inspecter la page de résultats de Target. Si vous inspectez la page, vous devriez remarquer que toutes les fiches produits ont une valeur data-test de @web/site-top-of-funnel/ProductCardWrapper. Nous utiliserons cette valeur comme sélecteur CSS lors de l’extraction de nos données.
Les requêtes Python et BeautifulSoup ne fonctionnent pas
Si vous n’avez pas Requests et BeautifulSoup, vous pouvez les installer via pip.
pip install requests beautifulsoup4Le code ci-dessous décrit un scraper de base que nous pouvons utiliser. Nous définissons nos en-têtes en utilisant notre clé API Bright Data et application/json. Nos données contiennent notre configuration actuelle, comme le nom de la zone, l’URL cible et le format. Après avoir trouvé les fiches produit, nous les parcourons et extrayons le titre, le lien et le prix de chaque produit.
Tous les produits extraits sont stockés dans un tableau, puis nous écrivons le tableau dans un fichier JSON lorsque le scrape est terminé. Remarquez les instructions ” continue" lorsque des éléments ne sont pas trouvés. Si un produit se trouve sur la page sans ces éléments, son chargement n’est pas terminé. Sans navigateur, nous ne pouvons pas rendre la page en attendant que le contenu se charge.
import requests
from bs4 import BeautifulSoup
import json
#headers to send to the web unlocker api
headers = {
"Authorization": "your-bright-data-api-key",
"Content-Type": "application/json"
}
#our configuration
data = {
"zone": "web_unlocker1",
"url": "https://www.target.com/s?searchTerm=laptop",
"format": "raw",
}
#send the request to the api
response = requests.post(
"https://api.brightdata.com/request",
json=data,
headers=headers
)
#array for scraped products
scraped_products = []
card_selector = "@web/site-top-of-funnel/ProductCardWrapper"
#parse them with beautifulsoup
soup = BeautifulSoup(response.text, "html.parser")
cards = soup.select(f"div[data-test='{card_selector}']")
#log the amount of cards found for debugging purposes
print("products found", len(cards))
#iterate through the cards
for card in cards:
#find the product data
#if a product hasn't loaded yet, drop it from the list
listing_text = card.text
link_element = card.select_one("a[data-test='product-title']")
if not link_element:
continue
title = link_element.get("aria-label").replace("\"")
link = link_element.get("href")
price = card.select_one("span[data-test='current-price'] span")
if not price:
continue
product_info = {
"title": title,
"link": f"https://www.target.com{link}",
"price": price.text
}
#add the extracted product to our scraped data
scraped_products.append(product_info)
#write our extracted data to a JSON file
with open("output.json", "w", encoding="utf-8") as file:
json.dump(scraped_products, file, indent=4)Le fait d’ignorer les objets non rendus limite considérablement les données extraites. Comme vous pouvez le voir dans les résultats ci-dessous, nous n’avons pu extraire que quatre résultats complets.
[
{
"title": "Lenovo LOQ 15 15.6\" 1920 x 1080 FHD 144Hz Gaming Laptop Intel Core i5-12450HX 12GB RAM DDR5 512GB SSD NVIDIA GeForce RTX 3050 6GB Luna Grey",
"link": "https://www.target.com/p/lenovo-loq-15-15-6-1920-x-1080-fhd-144hz-gaming-laptop-intel-core-i5-12450hx-12gb-ram-ddr5-512gb-ssd-nvidia-geforce-rtx-3050-6gb-luna-grey/-/A-93972673#lnk=sametab",
"price": "$569.99"
},
{
"title": "Lenovo Flex 5i 14\" WUXGA 2-in-1 Touchscreen Laptop, Intel Core i5-1235U, 8GB RAM, 512GB SSD, Intel Iris Xe Graphics, Windows 11 Home",
"link": "https://www.target.com/p/lenovo-flex-5i-14-wuxga-2-in-1-touchscreen-laptop-intel-core-i5-1235u-8gb-ram-512gb-ssd-intel-iris-xe-graphics-windows-11-home/-/A-91620960#lnk=sametab",
"price": "$469.99"
},
{
"title": "HP Envy x360 14\" Full HD 2-in-1 Touchscreen Laptop, Intel Core 5 120U, 8GB RAM, 512GB SSD, Windows 11 Home",
"link": "https://www.target.com/p/hp-envy-x360-14-full-hd-2-in-1-touchscreen-laptop-intel-core-5-120u-8gb-ram-512gb-ssd-windows-11-home/-/A-92708401#lnk=sametab",
"price": "$569.99"
},
{
"title": "HP Inc. Essential Laptop Computer 17.3\" HD+ Intel Core 8 GB memory; 256 GB SSD",
"link": "https://www.target.com/p/hp-inc-essential-laptop-computer-17-3-hd-intel-core-8-gb-memory-256-gb-ssd/-/A-92469343#lnk=sametab",
"price": "$419.99"
}
]Avec Requests et BeautifulSoup, nous pouvons accéder à la page mais nous ne pouvons pas charger tous les résultats.
Scraping avec Python Selenium
Nous avons besoin d’un navigateur pour rendre la page. C’est là que Selenium entre en jeu. Exécutez la commande ci-dessous pour installer Selenium.
pip install seleniumDans le code ci-dessous, nous nous connectons à une instance distante de Selenium en utilisant Scraping Browser. Prêtez attention au code réel ici. Notre logique est en grande partie la même que celle de l’exemple précédent. La plupart du code supplémentaire que vous voyez ci-dessous concerne la gestion des erreurs et des attentes préprogrammées pour le chargement du contenu de la page.
from selenium.webdriver import Remote, ChromeOptions
from selenium.webdriver.chromium.remote_connection import ChromiumRemoteConnection
from selenium.webdriver.common.by import By
from selenium.webdriver.support.ui import WebDriverWait
from selenium.webdriver.support import expected_conditions as EC
from selenium.common.exceptions import NoSuchElementException, TimeoutException
import json
import time
import sys
AUTH = 'brd-customer-<your-username>-zone-<your-zone-name>:<your-password>'
SBR_WEBDRIVER = f'https://{AUTH}@brd.superproxy.io:9515'
def safe_print(*args):
#force safe ascii-only output on windows terminals
text = " ".join(str(arg) for arg in args)
try:
sys.stdout.write(text + '\n')
except UnicodeEncodeError:
sys.stdout.write(text.encode('ascii', errors='replace').decode() + '\n')
#our actual runtime
def main():
#array for scraped products
scraped_products = []
card_selector = "@web/site-top-of-funnel/ProductCardWrapper"
safe_print('Connecting to Bright Data SBR Browser API...')
#remote connection config to scraping browser
sbr_connection = ChromiumRemoteConnection(SBR_WEBDRIVER, 'goog', 'chrome')
#launch scraping browser
with Remote(sbr_connection, options=ChromeOptions()) as driver:
safe_print('Connected! Navigating...')
driver.get("https://www.target.com/s?searchTerm=laptop")
#set a 30 second timeout for items to load
wait = WebDriverWait(driver, 30)
safe_print('Waiting for initial product cards...')
try:
wait.until(
EC.presence_of_element_located((By.CSS_SELECTOR, f"div[data-test='{card_selector}']"))
)
except TimeoutException:
safe_print("No product cards loaded at all — possible block or site structure change.")
return
#get the document height for some scrolling math
safe_print('Starting pixel-step scroll loop...')
last_height = driver.execute_script("return document.body.scrollHeight")
scroll_attempt = 0
max_scroll_attempts = 10
#gently scroll down the page
while scroll_attempt < max_scroll_attempts:
driver.execute_script("window.scrollBy(0, window.innerHeight);")
time.sleep(1.5)
new_height = driver.execute_script("return document.body.scrollHeight")
if new_height == last_height:
safe_print("Reached page bottom.")
break
last_height = new_height
scroll_attempt += 1
safe_print("Scrolling done — doing final settle nudges to keep session alive...")
try:
for _ in range(5):
driver.execute_script("window.scrollBy(0, -50); window.scrollBy(0, 50);")
time.sleep(1)
except Exception as e:
safe_print(f"Connection closed during final settle: {type(e).__name__} — {e}")
return
#now that everything's loaded, find the product cards
safe_print("Scraping product cards...")
try:
product_cards = driver.find_elements(By.CSS_SELECTOR, f"div[data-test='{card_selector}']")
safe_print(f"Found {len(product_cards)} cards.")
except Exception as e:
safe_print(f"Failed to find product cards: {type(e).__name__} — {e}")
return
#drop empty cards and extract data from the rest
for card in product_cards:
inner_html = card.get_attribute("innerHTML").strip()
if not inner_html or len(inner_html) < 50:
continue
safe_print("\n--- CARD HTML (truncated) ---\n", inner_html[:200])
try:
link_element = card.find_element(By.CSS_SELECTOR, "a[data-test='product-title']")
title = link_element.get_attribute("aria-label") or link_element.text.strip()
link = link_element.get_attribute("href")
except NoSuchElementException:
safe_print("Link element not found in card, skipping.")
continue
try:
price_element = card.find_element(By.CSS_SELECTOR, "span[data-test='current-price'] span")
price = price_element.text.strip()
except NoSuchElementException:
price = "N/A"
product_info = {
"title": title,
"link": f"https://www.target.com{link}" if link and link.startswith("/") else link,
"price": price
}
scraped_products.append(product_info)
#write the extracted products to a json file
if scraped_products:
with open("scraped-products.json", "w", encoding="utf-8") as file:
json.dump(scraped_products, file, indent=2)
safe_print(f"Done! Saved {len(scraped_products)} products to scraped-products.json")
else:
safe_print("No products scraped — nothing to save.")
if __name__ == '__main__':
main()Comme vous pouvez le constater, nous obtenons des résultats plus complets avec Selenium. Au lieu de quatre listes, nous pouvons en extraire huit. C’est beaucoup mieux que notre première tentative.
[
{
"title": "Lenovo LOQ 15 15.6\" 1920 x 1080 FHD 144Hz Gaming Laptop Intel Core i5-12450HX 12GB RAM DDR5 512GB SSD NVIDIA GeForce RTX 3050 6GB Luna Grey",
"link": "https://www.target.com/p/lenovo-loq-15-15-6-1920-x-1080-fhd-144hz-gaming-laptop-intel-core-i5-12450hx-12gb-ram-ddr5-512gb-ssd-nvidia-geforce-rtx-3050-6gb-luna-grey/-/A-93972673#lnk=sametab",
"price": "$569.99"
},
{
"title": "Lenovo Flex 5i 14\" WUXGA 2-in-1 Touchscreen Laptop, Intel Core i5-1235U, 8GB RAM, 512GB SSD, Intel Iris Xe Graphics, Windows 11 Home",
"link": "https://www.target.com/p/lenovo-flex-5i-14-wuxga-2-in-1-touchscreen-laptop-intel-core-i5-1235u-8gb-ram-512gb-ssd-intel-iris-xe-graphics-windows-11-home/-/A-91620960#lnk=sametab",
"price": "$469.99"
},
{
"title": "HP Inc. Essential Laptop Computer 15.6\" HD Intel Core i5 8 GB memory; 256 GB SSD",
"link": "https://www.target.com/p/hp-inc-essential-laptop-computer-15-6-hd-intel-core-i5-8-gb-memory-256-gb-ssd/-/A-1002589475#lnk=sametab",
"price": "$819.99"
},
{
"title": "HP Envy x360 14\" Full HD 2-in-1 Touchscreen Laptop, Intel Core 5 120U, 8GB RAM, 512GB SSD, Windows 11 Home",
"link": "https://www.target.com/p/hp-envy-x360-14-full-hd-2-in-1-touchscreen-laptop-intel-core-5-120u-8gb-ram-512gb-ssd-windows-11-home/-/A-92708401#lnk=sametab",
"price": "$569.99"
},
{
"title": "Lenovo Legion Pro 7i 16\" WQXGA OLED 240Hz Gaming Notebook Intel Core Ultra 9 275HX 32GB RAM 1TB SSD NVIDIA GeForce RTX 5070Ti Eclipse Black",
"link": "https://www.target.com/p/lenovo-legion-pro-7i-16-wqxga-oled-240hz-gaming-notebook-intel-core-ultra-9-275hx-32gb-ram-1tb-ssd-nvidia-geforce-rtx-5070ti-eclipse-black/-/A-1002300555#lnk=sametab",
"price": "$2,349.99"
},
{
"title": "Lenovo LOQ 15.6\" 1920 x 1080 FHD 144Hz Gaming Notebook Intel Core i5-12450HX 12GB DDR5 512GB SSD NVIDIA GeForce 2050 4GB DDR6 Luna Grey",
"link": "https://www.target.com/p/lenovo-loq-15-6-1920-x-1080-fhd-144hz-gaming-notebook-intel-core-i5-12450hx-12gb-ddr5-512gb-ssd-nvidia-geforce-2050-4gb-ddr6-luna-grey/-/A-1000574845#lnk=sametab",
"price": "$519.99"
},
{
"title": "HP Envy x360 14\u201d WUXGA 2-in-1 Touchscreen Laptop, AMD Ryzen 5 8640HS, 16GB RAM, 512GB SSD, Windows 11 Home",
"link": "https://www.target.com/p/hp-envy-x360-14-wuxga-2-in-1-touchscreen-laptop-amd-ryzen-5-8640hs-16gb-ram-512gb-ssd-windows-11-home/-/A-92918585#lnk=sametab",
"price": "$669.99"
},
{
"title": "Acer Aspire 3 - 15.6\" Touchscreen Laptop AMD Ryzen 5 7520U 2.80GHz 16GB RAM 1TB SSD W11H - Manufacturer Refurbished",
"link": "https://www.target.com/p/acer-aspire-3-15-6-touchscreen-laptop-amd-ryzen-5-7520u-2-80ghz-16gb-1tb-w11h-manufacturer-refurbished/-/A-93221896#lnk=sametab",
"price": "$299.99"
}
]Nos résultats sont meilleurs, mais nous pouvons encore les améliorer – avec moins de travail et zéro code.
Comment gratter des cibles avec Claude
Ensuite, nous allons effectuer la même tâche en utilisant Claude avec le serveur MCP de Bright Data. Vous pouvez commencer par ouvrir Claude Desktop. Assurez-vous que les zones Web Unlocker et Scraping Browser sont actives. Scraping Browser n’est pas nécessaire pour le serveur MCP, mais Target nécessite un navigateur.
Configuration de la connexion MCP
Depuis le bureau de Claude, cliquez sur “Fichier” et choisissez “Paramètres”. Cliquez sur “Developer” et choisissez “Edit Config”. Copiez et collez le code ci-dessous dans votre fichier de configuration. Veillez à remplacer la clé API et les noms de zone par les vôtres.
{
"mcpServers": {
"Bright Data": {
"command": "npx",
"args": ["@brightdata/mcp"],
"env": {
"API_TOKEN": "<your-brightdata-api-token>",
"WEB_UNLOCKER_ZONE": "<optional—override default zone name 'mcp_unlocker'>",
"BROWSER_AUTH": "<optional—enable full browser control via Scraping Browser>"
}
}
}
}Après avoir sauvegardé la configuration et redémarré Claude, vous pouvez ouvrir vos paramètres de développement et vous devriez voir Bright Data comme une option. Si vous cliquez sur Bright Data pour inspecter votre configuration, elle devrait ressembler à ce que vous voyez dans l’image ci-dessous.
Une fois connecté, vérifiez avec Claude qu’il a accès au serveur MCP. L’invite ci-dessous devrait suffire.
Êtes-vous connecté au MCP de Bright Data ?
Si tout est connecté, Claude devrait répondre comme dans l’image ci-dessous. Claude reconnaît la connexion et explique ce qu’elle peut faire.
Exécution de la recherche proprement dite
A partir de là, le travail est facile. Donnez à Claude l’URL de votre liste cible et laissez-le travailler. L’invite ci-dessous devrait fonctionner parfaitement.
Please extract laptops from https://www.target.com/s?searchTerm=laptop
Au cours de ce processus, ne soyez pas surpris si des fenêtres contextuelles vous demandent si Claude peut utiliser certains outils. Il s’agit d’une fonction de sécurité intéressante. Claude n’utilisera pas ces outils à moins que vous ne lui en donniez explicitement la permission.
Claude vous demandera probablement la permission d’utiliser des outils tels que scrape_as_markdown, extract et probablement quelques autres. Veillez à donner l’autorisation d’utiliser ces outils. Sans cette autorisation, Claude ne pourra pas extraire les résultats.
Stockage des résultats
Ensuite, demandez à Claude de stocker les résultats dans un fichier JSON. En quelques secondes, Claude écrira tous les résultats extraits dans un fichier JSON très détaillé et bien structuré.
Si vous choisissez d’afficher le fichier, il devrait ressembler à la capture d’écran ci-dessous. Claude extrait beaucoup plus de détails sur chaque produit que nous ne l’avions fait initialement.
{
"source": "Target.com",
"search_term": "laptop",
"extraction_date": "2025-07-09",
"total_results": 834,
"current_page": 1,
"total_pages": 35,
"special_offers": "Up to 50% off select laptops during Target Circle week (ends 7/12)",
"laptops": [
{
"id": 1,
"name": "Lenovo IdeaPad 1i Laptop",
"brand": "Lenovo",
"price": {
"current": 279.00,
"regular": 399.00,
"discount_percentage": 30
},
"specifications": {
"screen_size": "15.6\"",
"display_type": "FHD Display",
"processor": "Intel Celeron N4500",
"graphics": "Intel UHD Graphics",
"memory": "4GB RAM",
"storage": "128GB eMMC",
"operating_system": "Windows 11 Home",
"connectivity": "Wi-Fi 6"
},
"color": "Grey",
"rating": {
"stars": 4.4,
"total_reviews": 22
},
"availability": {
"shipping": "Arrives Fri, Jul 11",
"free_shipping": true
},
"sponsored": true
},
{
"id": 2,
"name": "HP Essential Laptop",
"brand": "HP Inc.",
"price": {
"current": 489.00,
"regular": 599.00,
"discount_percentage": 18
},
"specifications": {
"screen_size": "17.3\"",
"display_type": "HD+ 1600×900 Touchscreen 60Hz",
"processor": "Intel Core i3-N305",
"graphics": "Intel UHD Graphics",
"memory": "4GB RAM",
"storage": "128GB SSD",
"operating_system": "Windows 11 Home",
"connectivity": "Wi-Fi 6"
},
"color": "Silver",
"rating": {
"stars": null,
"total_reviews": 0
},
"availability": {
"shipping": "Arrives Fri, Jul 11",
"free_shipping": true
},
"sponsored": true
},
{
"id": 3,
"name": "HP 15.6\" FHD IPS Notebook",
"brand": "HP Inc.",
"price": {
"current": 399.99,
"regular": 669.99,
"discount_percentage": 40
},
"specifications": {
"screen_size": "15.6\"",
"display_type": "FHD IPS",
"processor": "Intel Core i5-1334U",
"graphics": null,
"memory": "12GB RAM",
"storage": "512GB SSD",
"operating_system": null,
"connectivity": null
},
"color": "Natural Silver",
"rating": {
"stars": 5.0,
"total_reviews": 2
},
"availability": {
"shipping": "Arrives Sat, Jul 12",
"free_shipping": true
},
"bestseller": true,
"sponsored": false
},
{
"id": 4,
"name": "Lenovo Flex 5i 14\" WUXGA 2-in-1 Touchscreen Laptop",
"brand": "Lenovo",
"price": {
"current": 469.99,
"regular": 679.99,
"discount_percentage": 31
},
"specifications": {
"screen_size": "14\"",
"display_type": "WUXGA 2-in-1 Touchscreen",
"processor": "Intel Core i5-1235U",
"graphics": "Intel Iris Xe Graphics",
"memory": "8GB RAM",
"storage": "512GB SSD",
"operating_system": "Windows 11 Home",
"connectivity": null
},
"color": null,
"rating": {
"stars": 4.3,
"total_reviews": 3
},
"availability": {
"shipping": "Arrives Fri, Jul 11",
"free_shipping": true
},
"sponsored": false
},
{
"id": 5,
"name": "HP Envy x360 14\" Full HD 2-in-1 Touchscreen Laptop",
"brand": "HP Inc.",
"price": {
"current": 569.99,
"regular": 799.99,
"discount_percentage": 29
},
"specifications": {
"screen_size": "14\"",
"display_type": "Full HD 2-in-1 Touchscreen",
"processor": "Intel Core 5 120U",
"graphics": null,
"memory": "8GB RAM",
"storage": "512GB SSD",
"operating_system": "Windows 11 Home",
"connectivity": null
},
"color": null,
"rating": {
"stars": 4.3,
"total_reviews": 152
},
"availability": {
"shipping": "Arrives Fri, Jul 11",
"free_shipping": true
},
"sponsored": false
},
{
"id": 6,
"name": "HP Inc. Essential Laptop Computer",
"brand": "HP Inc.",
"price": {
"current": 419.99,
"regular": 649.99,
"discount_percentage": 35
},
"specifications": {
"screen_size": "17.3\"",
"display_type": "HD+",
"processor": "Intel Core",
"graphics": null,
"memory": "8GB RAM",
"storage": "256GB SSD",
"operating_system": null,
"connectivity": null
},
"color": null,
"rating": {
"stars": 4.4,
"total_reviews": 2222
},
"availability": {
"shipping": "Arrives Sat, Jul 12",
"free_shipping": true
},
"sponsored": false
},
{
"id": 7,
"name": "ASUS Vivobook 17.3\" FHD Daily Laptop",
"brand": "ASUS",
"price": {
"current": 429.00,
"regular": 579.00,
"discount_percentage": 26
},
"specifications": {
"screen_size": "17.3\"",
"display_type": "FHD",
"processor": "Intel Core i3",
"graphics": "Intel UHD",
"memory": "4GB RAM",
"storage": "128GB SSD",
"operating_system": "Windows 11 Home",
"connectivity": "Wi-Fi",
"features": ["HDMI", "Webcam"]
},
"color": "Blue",
"rating": {
"stars": null,
"total_reviews": 0
},
"availability": {
"shipping": "Arrives Fri, Jul 11",
"free_shipping": true
},
"sponsored": true
},
{
"id": 8,
"name": "Lenovo Legion Pro 7i 16\" WQXGA OLED 240Hz Gaming Notebook",
"brand": "Lenovo",
"price": {
"current": 2349.99,
"regular": 2649.99,
"discount_percentage": 11
},
"specifications": {
"screen_size": "16\"",
"display_type": "WQXGA OLED 240Hz",
"processor": "Intel Core Ultra 9 275HX",
"graphics": "NVIDIA GeForce RTX 5070Ti",
"memory": "32GB RAM",
"storage": "1TB SSD",
"operating_system": null,
"connectivity": null
},
"color": "Eclipse Black",
"rating": {
"stars": null,
"total_reviews": 0
},
"availability": {
"shipping": "Arrives Sat, Jul 12",
"free_shipping": true
},
"category": "Gaming",
"sponsored": false
},
{
"id": 9,
"name": "Acer 315 - 15.6\" 1920 x 1080 Chromebook",
"brand": "Acer",
"price": {
"current": 109.99,
"regular": 199.00,
"discount_percentage": 45,
"price_range": "109.99 - 219.99",
"regular_range": "199.00 - 404.99"
},
"specifications": {
"screen_size": "15.6\"",
"display_type": "1920 x 1080",
"processor": null,
"graphics": null,
"memory": null,
"storage": null,
"operating_system": "ChromeOS",
"connectivity": null
},
"color": null,
"rating": {
"stars": 3.8,
"total_reviews": 69
},
"availability": {
"shipping": null,
"free_shipping": null
},
"condition": "Manufacturer Refurbished",
"sponsored": false
},
{
"id": 10,
"name": "HP Chromebook 14\" HD Laptop",
"brand": "HP",
"price": {
"current": 219.00,
"regular": 299.00,
"discount_percentage": 27
},
"specifications": {
"screen_size": "14\"",
"display_type": "HD",
"processor": "Intel Celeron N4120",
"graphics": null,
"memory": "4GB RAM",
"storage": "64GB eMMC",
"operating_system": "Chrome OS",
"connectivity": null
},
"color": null,
"rating": {
"stars": 4.1,
"total_reviews": 40
},
"availability": {
"shipping": null,
"free_shipping": null
},
"sponsored": false
},
{
"id": 11,
"name": "HP 15.6\" Laptop - Intel Pentium N200",
"brand": "HP",
"price": {
"current": 419.99,
"regular": null,
"discount_percentage": null
},
"specifications": {
"screen_size": "15.6\"",
"display_type": null,
"processor": "Intel Pentium N200",
"graphics": null,
"memory": "8GB RAM",
"storage": "256GB SSD",
"operating_system": null,
"connectivity": null
},
"color": "Blue",
"model": "15-fd0015tg",
"rating": {
"stars": 4.0,
"total_reviews": 516
},
"availability": {
"shipping": null,
"free_shipping": null
},
"highly_rated": true,
"sponsored": false
},
{
"id": 12,
"name": "Lenovo IP 5 16IAU7 16\" Laptop 2.5K",
"brand": "Lenovo",
"price": {
"current": 268.99,
"regular": 527.99,
"discount_percentage": 49
},
"specifications": {
"screen_size": "16\"",
"display_type": "2.5K",
"processor": "i3-1215U",
"graphics": null,
"memory": "8GB RAM",
"storage": "128GB eMMC",
"operating_system": "Chrome OS",
"connectivity": null
},
"color": null,
"rating": {
"stars": 4.0,
"total_reviews": 5
},
"availability": {
"shipping": null,
"free_shipping": null
},
"condition": "Manufacturer Refurbished",
"sponsored": false
},
{
"id": 13,
"name": "Lenovo IdeaPad 3 Chrome 15IJL6 15.6\" Laptop",
"brand": "Lenovo",
"price": {
"current": 144.99,
"regular": 289.99,
"discount_percentage": 50
},
"specifications": {
"screen_size": "15.6\"",
"display_type": null,
"processor": "Celeron N4500",
"graphics": null,
"memory": "4GB RAM",
"storage": "64GB eMMC",
"operating_system": "Chrome OS",
"connectivity": null
},
"color": null,
"rating": {
"stars": 4.1,
"total_reviews": 19
},
"availability": {
"shipping": null,
"free_shipping": null
},
"condition": "Manufacturer Refurbished",
"sponsored": false
},
{
"id": 14,
"name": "Acer Chromebook 315 15.6\" HD Laptop",
"brand": "Acer",
"price": {
"current": 229.00,
"regular": 349.00,
"discount_percentage": 34
},
"specifications": {
"screen_size": "15.6\"",
"display_type": "HD",
"processor": "Intel Pentium N6000",
"graphics": null,
"memory": "4GB RAM",
"storage": "128GB eMMC",
"operating_system": "Chrome OS",
"connectivity": null
},
"color": null,
"rating": {
"stars": 4.3,
"total_reviews": 7
},
"availability": {
"shipping": null,
"free_shipping": null
},
"includes": "Protective Sleeve",
"sponsored": false
},
{
"id": 15,
"name": "Acer 315 - 15.6\" Chromebook Intel Celeron 64GB Flash",
"brand": "Acer",
"price": {
"current": 109.99,
"regular": 219.99,
"discount_percentage": 50,
"price_range": "109.99 - 152.99",
"regular_range": "219.99 - 279.99"
},
"specifications": {
"screen_size": "15.6\"",
"display_type": null,
"processor": "Intel Celeron",
"graphics": null,
"memory": null,
"storage": "64GB Flash",
"operating_system": "ChromeOS",
"connectivity": null
},
"color": null,
"rating": {
"stars": 4.0,
"total_reviews": 60
},
"availability": {
"shipping": null,
"free_shipping": null
},
"condition": "Manufacturer Refurbished",
"sponsored": false
}
],
"popular_filters": [
"Gaming",
"HP",
"Deals",
"Under $300",
"Windows"
],
"price_ranges": {
"minimum": 109.99,
"maximum": 2349.99,
"budget_under_300": true,
"mid_range_300_800": true,
"premium_800_plus": true
},
"brands_available": [
"Lenovo",
"HP",
"HP Inc.",
"ASUS",
"Acer"
],
"operating_systems": [
"Windows 11 Home",
"Chrome OS",
"ChromeOS"
],
"screen_sizes": [
"14\"",
"15.6\"",
"16\"",
"17.3\""
],
"notes": {
"shipping_policy": "Most items ship within 1-2 days with free shipping",
"promotion_end_date": "2025-07-12",
"data_completeness": "This represents page 1 of 35 total pages of results"
}
}Conclusion
La cible est difficile, mais pas impossible. Manuellement, vous avez besoin d’une approche intelligente avec un vrai navigateur, un défilement automatisé, des attentes et une connexion proxy. Vous pouvez également créer un agent d’intelligence artificielle qui sait exactement comment gérer le contenu dynamique de Target. Le navigateur de scraping et le serveur MCP de Bright Data rendent cela possible, que vous soyez développeur ou que vous préfériez laisser l’IA s’occuper des tâches les plus lourdes.
Bright Data propose également une API Target Scraper dédiée qui fournit les résultats à votre système de stockage préféré.
Inscrivez-vous pour un essai gratuit et commencez dès aujourd’hui !
