How to Scrape Image URL and the Best URL Generator to Help You

Web scraping is one of the most powerful ways to gather valuable information to use for a variety of applications. You can capture product listings, for example, from competitors to determine what is working for them. You can also learn how to get an image URL from scraping, and once you do that, you can gather the images you need for websites in a fast and efficient manner.

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Here, we will break down how to get the URL of an image using a web scraper, as well as which image URL generator you can use to help you along the way. No matter what your needs are, the process can be applied to that – URLs of any type of image can be navigated in this way.

How to Get an Image URL: Start Here

To scrape image URLs from a website, you need to have a tool that will extract the source links from those images. These source links are embedded on a web page.

To add a photo to a website, the website owner uploads the image to the site and then saves it on the web server, typically as a static file. In doing that, it creates a specific URL address for that image. Once someone visits a website, the site uses the URLs to display the image for visitors to see.

You are likely to see this noted with the HTML element: <img> or <img scr= LINK” alt+description>

Noting this, you can use a web scraper to scrape the web for the images you are looking for based on the IMG tag used. Web scraping tools or libraries allow you to parse the HTML data you collect from the website and locate the <img> tags. That’s exactly where the Image URL is stored in the SCR attribute.

Confused? The process is not all that complex once you learn how to use web scraping tools. There are a lot of tools out there, but consider why you may want to use Scraping Robot to handle this task for you instead.

Using Python to Get Image URL

One of the options you have for capturing this valuable data is to use Python libraries to help you with the process. Once you install the necessary libraries, you can then begin to capture the information you need. Keep in mind to do this, you will need to install the following components:

• HTTPX
• Playwright
• Beautiful Soup
• Cssutils
• JMESPath
• Asyncio
• Numpy
• Pillow

You’ll need all or most of these to help you with the entire process. To do that, use the following command:

pip install httpx playwright beautifulsoup4 cssutils jmespath asyncio numpy pillow

Once you do that, you can then begin to scrape the data. Here is how it would work in this scenario:

• HTPPX will send the request to the site
• Beautiful Soup then works to parse the HTML data to parse the <img> components. It will also scrape some of the HTML pages to pull out that data.

In short, you’ll need to write some code to help you do this in Python, including code that will scrape the HTML pages and then parse them for the img elements. The code likely needs to do much more for you as well. For example, if you want to extract all of the image URLs from a website, you’ll need a web crawler that will iterate over the pages and capture the HTML for each of those pages you want to pull the image from. Then, you need to parse down all of that information to capture just the IMG elements you want.

Once you do that, you can use CSS selectors to pull the information necessary, such as the image URL and title from the pages, if you are looking at product listings.

You then must append them to the list of image links before iterating over the list that has been created to create a PNG file for each of the products. That file contains the information you need. Finally, a GET request is necessary to save the image binary data.

If you are going to scrape in Python, you could use this code, though you’ll want to make adjustments to the process:

import httpx

from bs4 import BeautifulSoup

# 1. Find image links on the website

image_links = []

# Scrape the first 5 pages

for page in range(4):

url = f”https://web-scraping.dev/products?page={page}”

response = httpx.get(url)

soup = BeautifulSoup(response.text, “html.parser”)

for image_box in soup.select(“div.row.product”):

result = {

“link”: image_box.select_one(“img”).attrs[“src”],

“title”: image_box.select_one(“h3″).text,

}

# Append each image and title to the result array

image_links.append(result)

# 2. Download image objects

for image_object in image_links:

# Create a new .png image file

with open(f”./images/{image_object[‘title’]}.png”, “wb”) as file:

image = httpx.get(image_object[“link”])

#3. Save the image binary data into the file

file.write(image.content)

print(f”Image {image_object[‘title’]} has been scraped”)

You will need to update this with your specific information, and every time you need to gather new images from various sites, you will need to update this code. That can take some time, and it can be quite annoying to learn how to get image URL data from each website like this.

Web Scraping Tools and the Best URL Generator

As noted, Python can do the work for you with a bit of learning and exploring its features. However, you can also use web scraping tools that are actually built to get image URL data for you – in other words, why do all of that coding work if you do not need to do so?

When you choose an image URL generator, you get through the process much faster, which means less time to get all of the images you need. Scraping Robot is an HTML web scraping tool that can be used to get an image to a URL. It goes to work to find what you need and can be very simple to use overall. Here’s what to expect.

Learn How to Get a URL of Image with Scraping Robot

To learn how to get the URL of an image using Scraping Robot, you need very little time and you do not have to learn to write code, which are often requirements using other tools. As one of the best URL generators available, Scraping Robot can do all of the work you want it to do including fetching all of the images you need, analyzing the information collected, and then utilizing the data in a way that is effective for you.

What makes Scraping Robot so efficient is that it includes JavaScript rendering, full proxy management to hide your identification from the websites that you are trying to scrape, metadata parsing, and guaranteed results. It is much like asking the question – is there anything easier to use to get image URL information?

Overcoming Challenges in Getting Image URL Information

Now that you know how to get image URL data, you may go to work to get the job done, only to find that you have a number of obstacles to overcome. This can be frustrating, and this is where some tools limit you.

However, one of the nice features of Scraping Robot is it can help you get around IP blocks and other problems along the way, enabling you to have continuous access to the information you use even if anti-bot technology is in place.

For example, once you start to use the image URL generator to find the images you need, Scraping Robot can help you get around one of the hardest components of the process: CAPTCHAs. These require a person to identify various elements or answer a puzzle, and for most web scraping tools, that’s a big block, meaning if you cannot get past this, you cannot use it. Scraping Robot can help you to do that.

Another obstacle has to do with location. If you are located in an area that has a geo-block on it from the website, that means your IP address – located in that blocked area – will limit your access. However, Scraping Robot allows you to get around that as well when you use web scraping with proxies. This protects your sensitive information and allows you to get the work done rather efficiently.

Scraping Robot also aids in getting dynamic content and working around honeypot traps – one of the most worrisome of traps that are growing in use.

How to Get Started with Scraping Robot

Once you find the benefits in using an image URL generator like Scraping Robot to help you and you link this with Rayobyte’s proxy services, you are able to work around just about any limitation you have with ease. You can consistently learn how to get an image URL by writing your own code if you want, but with tools like this to get image URL data so quickly, there is really no need to do so. Check out how Scraping Robot’s API can help you.

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