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{
"cells": [
{
"metadata": {
"ExecuteTime": {
"end_time": "2024-10-25T10:32:47.963356Z",
"start_time": "2024-10-25T10:32:47.950533Z"
}
},
"cell_type": "code",
"source": [
"from fake_headers import Headers\n",
"\n",
"headers = Headers(headers=True).generate()\n",
"headers"
],
"id": "c60b4d771c2e0a21",
"outputs": [
{
"data": {
"text/plain": [
"{'Accept': '*/*',\n",
" 'Connection': 'keep-alive',\n",
" 'User-Agent': 'Mozilla/5.0 (Macintosh; Intel Mac OS X 10_11_6; rv:61.0) Gecko/20100101 Firefox/61.0',\n",
" 'Cache-Control': 'max-age=0',\n",
" 'Upgrade-Insecure-Requests': '1',\n",
" 'Referer': 'https://google.com'}"
]
},
"execution_count": 9,
"metadata": {},
"output_type": "execute_result"
}
],
"execution_count": 9
},
{
"metadata": {
"ExecuteTime": {
"end_time": "2024-10-25T10:32:49.821005Z",
"start_time": "2024-10-25T10:32:49.798988Z"
}
},
"cell_type": "code",
"source": [
"from selenium.webdriver.chrome.options import Options\n",
"from selenium import webdriver\n",
"from selenium.webdriver.support.ui import WebDriverWait\n",
"from selenium.webdriver.support import expected_conditions as EC\n",
"from selenium.webdriver.common.by import By\n",
"from bs4 import BeautifulSoup\n",
"import time\n",
"\n",
"\n",
"def scroll_and_wait(driver, scroll_pause_time=2):\n",
" \"\"\"\n",
" Scroll the page gradually and wait for images to load\n",
" \"\"\"\n",
" # Get scroll height\n",
" last_height = driver.execute_script(\"return document.body.scrollHeight\")\n",
"\n",
" while True:\n",
" # Scroll down gradually\n",
" for i in range(10):\n",
" driver.execute_script(f\"window.scrollTo(0, {(i + 1) * (last_height / 10)});\")\n",
" time.sleep(0.5) # Short pause between each scroll step\n",
"\n",
" # Wait for new images to load\n",
" time.sleep(scroll_pause_time)\n",
"\n",
" # Calculate new scroll height and compare with last scroll height\n",
" new_height = driver.execute_script(\"return document.body.scrollHeight\")\n",
" if new_height == last_height:\n",
" break\n",
" last_height = new_height\n",
"\n",
"\n",
"def wait_for_images(driver, timeout=10):\n",
" \"\"\"\n",
" Wait for images to load and become visible\n",
" \"\"\"\n",
" try:\n",
" # Wait for all image elements to be present\n",
" WebDriverWait(driver, timeout).until(\n",
" EC.presence_of_all_elements_located((By.TAG_NAME, \"img\"))\n",
" )\n",
"\n",
" # Get all image elements\n",
" images = driver.find_elements(By.TAG_NAME, \"img\")\n",
"\n",
" # Wait for images to load\n",
" for img in images:\n",
" try:\n",
" WebDriverWait(driver, 2).until(\n",
" lambda d: img.get_attribute('complete') == 'true' and\n",
" img.get_attribute('naturalHeight') != '0'\n",
" )\n",
" except:\n",
" continue # Skip images that don't load within timeout\n",
"\n",
" except Exception as e:\n",
" print(f\"Warning: Not all images could be loaded: {e}\")"
],
"id": "11933d956e20b6b8",
"outputs": [],
"execution_count": 10
},
{
"metadata": {
"ExecuteTime": {
"end_time": "2024-10-25T10:33:23.469518Z",
"start_time": "2024-10-25T10:32:53.382666Z"
}
},
"cell_type": "code",
"source": [
"chrome_options = Options()\n",
"chrome_options.add_argument(\"--headless\")\n",
"chrome_options.add_argument(\"--disable-gpu\")\n",
"chrome_options.add_argument(\"--no-sandbox\")\n",
"chrome_options.add_argument(\"--disable-dev-shm-usage\")\n",
"\n",
"# Add fake headers\n",
"for key, value in headers.items():\n",
" chrome_options.add_argument(f'--{key.lower()}={value}')\n",
"\n",
"# Additional configurations to appear more human-like\n",
"chrome_options.add_argument(\"--disable-blink-features=AutomationControlled\")\n",
"chrome_options.add_argument(\"--window-size=1920,1080\")\n",
"\n",
"# Enable images in headless mode\n",
"chrome_options.add_argument(\"--force-device-scale-factor=1\")\n",
"chrome_options.add_argument(\"--high-dpi-support=1\")\n",
"\n",
"# Privacy and fingerprinting prevention\n",
"chrome_options.add_argument(\"--disable-blink-features\")\n",
"chrome_options.add_argument(\"--disable-infobars\")\n",
"chrome_options.add_experimental_option(\"excludeSwitches\", [\"enable-automation\"])\n",
"chrome_options.add_experimental_option(\"useAutomationExtension\", False)\n",
"\n",
"# Enable JavaScript\n",
"chrome_options.add_argument(\"--enable-javascript\")\n",
"\n",
"driver = webdriver.Chrome(options=chrome_options)\n",
"\n",
"driver.execute_cdp_cmd(\"Page.addScriptToEvaluateOnNewDocument\", {\n",
" \"source\": \"\"\"\n",
" Object.defineProperty(navigator, 'webdriver', {\n",
" get: () => undefined\n",
" })\n",
" \"\"\"\n",
"})\n",
"\n",
"products_url = \"https://www.target.com/s?searchTerm=Peach&tref=typeahead%7Cterm%7CPeach%7C%7C%7Chistory\"\n",
"driver.get(products_url)\n",
"\n",
"time.sleep(3)\n",
"\n",
"# Scroll and wait for content\n",
"scroll_and_wait(driver)\n",
"\n",
"# Wait for images to load\n",
"wait_for_images(driver)\n",
"\n",
"time.sleep(2)\n",
"\n",
"soup = BeautifulSoup(driver.page_source, \"html.parser\")\n",
"driver.quit()"
],
"id": "ac14cff825f0887f",
"outputs": [],
"execution_count": 11
},
{
"metadata": {
"ExecuteTime": {
"end_time": "2024-10-25T10:52:34.470225Z",
"start_time": "2024-10-25T10:52:34.458243Z"
}
},
"cell_type": "code",
"source": [
"from urllib.parse import urljoin\n",
"import json\n",
"\n",
"\n",
"def convert_relative_urls(soup, base_url):\n",
" \"\"\"\n",
" Convert all relative URLs in the soup object to absolute URLs.\n",
" Handles href, src, and data-src attributes.\n",
" \"\"\"\n",
" # Convert href attributes (links)\n",
" for tag in soup.find_all(href=True):\n",
" tag['href'] = urljoin(base_url, tag['href'])\n",
"\n",
" # Convert src attributes (images, scripts, etc.)\n",
" for tag in soup.find_all(src=True):\n",
" tag['src'] = urljoin(base_url, tag['src'])\n",
"\n",
" # Convert data-src attributes (lazy loaded images)\n",
" for tag in soup.find_all(attrs={'data-src': True}):\n",
" tag['data-src'] = urljoin(base_url, tag['data-src'])\n",
"\n",
" return soup\n",
"\n",
"\n",
"def count_images_in_element(element):\n",
" \"\"\"\n",
" Count all images within an element, including nested ones.\n",
" \"\"\"\n",
" return len(element.find_all('img', recursive=True))\n",
"\n",
"\n",
"def get_element_identifier(element):\n",
" \"\"\"\n",
" Create a unique identifier for an element including tag and classes.\n",
" \"\"\"\n",
" identifier = element.name\n",
" if element.get('class'):\n",
" identifier += f\" .{' .'.join(element['class'])}\"\n",
" if element.get('id'):\n",
" identifier += f\" #{element['id']}\"\n",
" return identifier\n",
"\n",
"\n",
"def has_child_with_same_count(element, image_count, all_elements_with_counts):\n",
" \"\"\"\n",
" Check if the element has any child with the same image count.\n",
" \"\"\"\n",
" for other_element, other_count in all_elements_with_counts:\n",
" if other_count == image_count and other_element != element:\n",
" if any(parent == element for parent in other_element.parents):\n",
" return True\n",
" return False\n",
"\n",
"\n",
"def print_results_with_content(element_list):\n",
" \"\"\"\n",
" Print formatted results including the inner content of elements.\n",
" \"\"\"\n",
" print(\"\\nElements Containing Most Images (Lowest Level for Each Count):\")\n",
" print(\"=\" * 100)\n",
"\n",
" for rank, (tag_info, count, element) in enumerate(element_list, 1):\n",
" print(f\"\\nRank {rank}:\")\n",
" print(\"-\" * 100)\n",
" print(f\"Element: {tag_info}\")\n",
" print(f\"Image Count: {count}\")\n",
" print(\"\\nContent Preview:\")\n",
" print(\"-\" * 100)\n",
"\n",
" # Get all immediate img tags\n",
" immediate_images = element.find_all('img', recursive=False)\n",
" nested_images = element.find_all('img', recursive=True)\n",
"\n",
" print(f\"Direct images: {len(immediate_images)}\")\n",
" print(f\"Total images (including nested): {len(nested_images)}\")\n",
" print(\"\\nImage sources:\")\n",
"\n",
" # Print image sources and alt text\n",
" for img in nested_images:\n",
" src = img.get('src', 'No source')\n",
" alt = img.get('alt', 'No alt text')\n",
" print(f\"- Source: {src}\")\n",
" print(f\" Alt text: {alt}\")\n",
"\n",
" print(\"\\nFull HTML structure:\")\n",
" print(\"-\" * 100)\n",
" # Print formatted HTML structure\n",
" html_content = element.prettify()\n",
" print(html_content)\n",
" print(\"=\" * 100)\n",
"\n",
"\n",
"def find_top_image_parent(soup, base_url):\n",
" \"\"\"\n",
" Find the element containing the most images at the lowest level and return its details as JSON.\n",
" \"\"\"\n",
" # Collect all elements with their image counts\n",
" soup = convert_relative_urls(soup, base_url)\n",
"\n",
" elements_with_counts = []\n",
" for element in soup.find_all():\n",
" if element.name != 'img': # Skip img tags themselves\n",
" image_count = count_images_in_element(element)\n",
" if image_count > 0:\n",
" elements_with_counts.append((element, image_count))\n",
"\n",
" # Sort by image count in descending order\n",
" elements_with_counts.sort(key=lambda x: x[1], reverse=True)\n",
"\n",
" if not elements_with_counts:\n",
" return json.dumps({\"error\": \"No elements with images found\"}, indent=2)\n",
"\n",
" max_count = elements_with_counts[0][1]\n",
"\n",
" # Get all elements with max count\n",
" top_elements = [(elem, count) for elem, count in elements_with_counts if count == max_count]\n",
" print(len(elements_with_counts))\n",
" # \n",
" # # Find the lowest-level element among those with max count\n",
" # top_element = None\n",
" # for element, count in top_elements:\n",
" # if not has_child_with_same_count(element, count, elements_with_counts):\n",
" # top_element = element\n",
" # break\n",
" # \n",
" # if not top_element:\n",
" # return json.dumps({\"error\": \"No suitable element found\"}, indent=2)\n",
" # \n",
" # # Collect all images within the element\n",
" # images = []\n",
" # for img in top_element.find_all('img', recursive=True):\n",
" # image_data = {\n",
" # \"src\": img.get('src', 'No source'),\n",
" # \"alt\": img.get('alt', 'No alt text')\n",
" # }\n",
" # # Add any other attributes that exist\n",
" # for attr in ['title', 'width', 'height', 'class']:\n",
" # if img.get(attr):\n",
" # image_data[attr] = img[attr]\n",
" # images.append(image_data)\n",
" # \n",
" # # Create result dictionary\n",
" # result = {\n",
" # \"element\": {\n",
" # \"tag\": top_element.name,\n",
" # \"identifier\": get_element_identifier(top_element),\n",
" # \"classes\": top_element.get('class', []),\n",
" # \"id\": top_element.get('id', None)\n",
" # },\n",
" # \"image_count\": max_count,\n",
" # \"images\": images,\n",
" # \"html_content\": str(top_element)\n",
" # }\n",
" # \n",
" # # Create styled HTML output\n",
" # style_tag = f\"\"\"\n",
" # <style>\n",
" # img {{\n",
" # width: 300px;\n",
" # height: 300px;\n",
" # object-fit: contain;\n",
" # }}\n",
" # </style>\n",
" # \"\"\"\n",
" # html_output = style_tag + str(top_element)\n",
" # \n",
" # return json.dumps(result, indent=2), html_output\n"
],
"id": "3830f2e224e84798",
"outputs": [],
"execution_count": 33
},
{
"metadata": {},
"cell_type": "markdown",
"source": "",
"id": "80fa7f140d4da0a2"
},
{
"metadata": {
"ExecuteTime": {
"end_time": "2024-10-25T10:52:36.684418Z",
"start_time": "2024-10-25T10:52:36.614623Z"
}
},
"cell_type": "code",
"source": [
"base_url = products_url.rsplit('/', 1)[0]\n",
"find_top_image_parent(soup, base_url)\n",
"#\n",
"# with open(\"output.json\", \"w\") as file:\n",
"# file.write(json_data)\n",
"# \n",
"# with open(\"output.html\", \"w\") as file:\n",
"# file.write(html_content)"
],
"id": "20b0b8cd238de02d",
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"411\n"
]
}
],
"execution_count": 34
}
],
"metadata": {
"kernelspec": {
"display_name": "Python 3",
"language": "python",
"name": "python3"
},
"language_info": {
"codemirror_mode": {
"name": "ipython",
"version": 2
},
"file_extension": ".py",
"mimetype": "text/x-python",
"name": "python",
"nbconvert_exporter": "python",
"pygments_lexer": "ipython2",
"version": "2.7.6"
}
},
"nbformat": 4,
"nbformat_minor": 5
}
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