How to extract images from a website during scraping?

Leonzio Jonatan · 2024-12-18T05:50:22+00:00

Extracting images from a website involves identifying the HTML tags where the image URLs are stored. Most images are found in img elements with src attributes that point to the image file. Using Python’s BeautifulSoup, you can easily extract these URLs for static pages. For dynamic sites, tools like Puppeteer or Selenium can help load all images before scraping.Here’s an example using BeautifulSoup:import requests from bs4 import BeautifulSoupurl "https://example.com/gallery"headers {"User-Agent": "Mozilla/5.0"}response requests.get(url, headersheaders)if response.status_code 200: soup BeautifulSoup(response.content, "html.parser") images soup.find_all("img") for idx, img in enumerate(images, 1): src img.get("src") print(f"Image {idx}: {src}")else: print("Failed to fetch the page.")For saving images locally, you can use the requests library to download each image. Dynamic content, such as lazy-loaded images, requires browser automation tools to ensure all images are fully loaded before extraction. How do you handle large-scale image scraping efficiently?

General Web Scraping

How to extract images from a website during scraping?

Posted by Leonzio Jonatan on 12/18/2024 at 5:50 am
Extracting images from a website involves identifying the HTML tags where the image URLs are stored. Most images are found in img elements with src attributes that point to the image file. Using Python’s BeautifulSoup, you can easily extract these URLs for static pages. For dynamic sites, tools like Puppeteer or Selenium can help load all images before scraping.
Here’s an example using BeautifulSoup:
```
import requests
from bs4 import BeautifulSoup
url = "https://example.com/gallery"
headers = {"User-Agent": "Mozilla/5.0"}
response = requests.get(url, headers=headers)
if response.status_code == 200:
    soup = BeautifulSoup(response.content, "html.parser")
    images = soup.find_all("img")
    for idx, img in enumerate(images, 1):
        src = img.get("src")
        print(f"Image {idx}: {src}")
else:
    print("Failed to fetch the page.")
```
For saving images locally, you can use the requests library to download each image. Dynamic content, such as lazy-loaded images, requires browser automation tools to ensure all images are fully loaded before extraction. How do you handle large-scale image scraping efficiently?
Leonzio Jonatan replied 4 days, 19 hours ago 1 Member · 0 Replies
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