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Top 5 web scraping problems and solutions

If you’re considering web scraping and have done any research on the web, or if you already have experience working with a web scraping company as a client, you’ve probably encountered some discussion of the problems that may occur in the process. Maybe you even faced these problems already during a project.

The purpose of this article is to address, with full disclosure, five of the most common problems associated with web scraping…but we won’t leave you there. We’ll also discuss the causes of these problems and how we can avoid them. But in the spirit of full disclosure, we have to point out that these “problems” are both rare and often completely avoidable.

At Ficstar, we are passionate about the benefits of web scraping for a company. In fact, we have made it our goal to become the best web scraping service provider in the world. No, every job did not go perfectly. But because of the sheer volume of web data we scraped, we have an intimate knowledge of the good, the bad, and the ugly of web scraping. Now we can share this information with you. 

The most common web scraping problems and solutions

  • Problem #1: The wrong results were collected
  • Problem #2: Results didn’t arrive on time 
  • Problem #3: Can’t use the results (can’t use the data)
    Problem #4: Missing results
  • Problem #5: No response to my request

Problem #1: Results didn’t arrive on time

Reasons why a web scraping project’s results may be late: 

1. Requirements changed last minute:

If the clients decide to change requirements at the last minute, that is ok, the web scraping service provider will do their best to accommodate the change. However, it can cause delays as the scraping code and configuration need to be adjusted accordingly.

What is the solution: Timely communication with the client is crucial when there are delays in delivering the web scraping results. By informing the client as soon as possible about the delivery time change, the client can adjust their expectations and be aware of the situation while we work on solving the issue.

2. System problem:

The web scraping system itself may encounter technical difficulties or inefficiencies. This could be due to errors in the code, scalability issues, hardware limitations, or other system-related problems. 

What is the solution: If the web scraping process is encountering issues due to errors or inefficiencies in the crawler code, it is essential to identify and rectify these problems. In cases where the web scraping system itself is experiencing problems, such as technical glitches or performance limitations, troubleshooting and resolving these system issues is necessary. This may involve addressing software or hardware-related problems, upgrading infrastructure, or optimizing the system architecture to improve efficiency and eliminate delays.

3. Website blocking crawlers:

Many websites implement measures to prevent automated scraping activities by blocking or restricting access to web crawlers. They may employ techniques like CAPTCHAs, IP blocking, or user agent filtering to identify and block scraping activities. If the web scraping project encounters such restrictions, it can result in delayed or incomplete results. 

What is the solution: If the crawler is being detected or blocked, modifying the crawling anonymity code can help bypass these restrictions. This may involve using proxy servers, rotating user agents, or employing other techniques to mask the crawler’s identity and avoid detection.

If the crawler is being detected or blocked, modifying the crawling anonymity code can help bypass these restrictions. This may involve using residential proxy servers, captcha solving services, anti-fingerprint detection, or employing other techniques to mask the crawler’s identity and avoid detection.

4. Website down:

Website downtime could occur due to server maintenance, server overload, or other technical issues. The target website may also experience technical problems or server-related issues that affect the web scraping process. This could include slow response times, intermittent connectivity, or server errors. Such issues can disrupt the data extraction process and lead to delays in obtaining the desired results. 

What is the solution: If the target website is down, it is important to confirm whether it is a widespread problem or specific to the scraping system. Regularly checking the website’s availability and periodically reattempting the scraping process will allow for prompt resumption of data extraction when the website becomes accessible again. If all else fails, exploring alternative methods can provide fresh approaches to overcome challenges and maintain the scraping process on schedule. Verify cached page

5. Website updated their site and layout:

Websites often undergo updates to improve the user experience or introduce new features. These updates can include changes to the site’s structure, HTML elements, CSS classes, or JavaScript behavior, making the existing scraping code incompatible. 

What is the solution: If the website has undergone updates or changes in its structure or layout, the existing scraping code may need to be updated accordingly. Comparing the existing results with the new site and modifying the code to match the changes ensures accurate data extraction. 


Problem #2:The wrong results were collected 

Reasons why the wrong results may be collected on a web scraping project: 

1. Understanding the client’s requests wrong:

Misinterpreting or misunderstanding the client’s requests can lead to incorrect results. 

What is the solution: First, we access to determine how widespread the error is and confirm the incorrect data. Then we move on to clarification and QA sessions to clarify any uncertainties and to better understand client requests. The next step in the solution process is to create detailed project documentation that captures the client’s requirements accurately. This documentation can serve as a reference point and help avoid misunderstandings or misinterpretations.

2. Website changed:

Sometimes, the results collected during a web scraping project may be incorrect because the target website has undergone changes. This may cause results to vary widely from previous crawls. These changes can include alterations to the website’s structure, layout, or data format. 

What is the solution: Redefine the specs and crawl again. When this happens, it is essential to update the scraping code to match the new website and ensure accurate data extraction. In order to prevent future mistakes, it is important to verify the cache page and set up a system to monitor the target website for changes. 

3. Crawling issue:

Another reason for collecting wrong results can be due to crawling issues. It is possible that the crawler encounters difficulties in navigating the website, accessing certain pages, or retrieving the desired information. 

What is the solution: First we need to identify these crawling issues, and then move to solve it before recrawling the website. Cache all html pages and detect changes through automated regression testing of previous data sets. Implement custom retry logic based on the website’s design and classify known errors into groups such as “404 Not Found.”

4. Different formats:

Sometimes, the target website may present data in various formats. For example, different pages may have different data structures or organizations. 

What is the solution: In such cases, the scraping code needs to be adaptable and capable of handling these variations to collect accurate results consistently. Develop flexible parsing techniques that can adapt to different data formats. Utilize libraries or tools that can handle varying structures and organizations. Employ techniques like CSS selectors or XPath expressions to target specific elements irrespective of the format.

5. Parsing errors:

Parsing errors can occur when extracting and processing the collected data. These errors can stem from inconsistencies in the data format, unexpected characters, or missing information. Careful parsing and handling of these errors, such as using robust data cleaning and validation techniques, are necessary to avoid inaccuracies in the collected results.

What is the solution: Implement thorough data validation techniques to identify and handle parsing errors. This can involve checking for data inconsistencies, validating data types, and applying data cleaning methods to address unexpected characters or missing information. Implement error handling mechanisms within the scraping code to gracefully handle parsing errors. This can include logging the errors, retrying failed requests, or skipping erroneous data entries.

6. The request is country-specific, such as currency:

When the web scraping project involves retrieving data that is specific to a particular country or region, such as currency exchange rates, wrong results can be collected if the requests are not properly tailored.

What is the solution: Ensuring that the scraping requests include the necessary parameters or filters to match the desired country or region is crucial for obtaining accurate results. Verify the correctness of the filters and update them as needed.

7. Website inserted incorrect data:

In some cases, the website itself may contain incorrect or misleading information. This can happen due to human error, data entry mistakes, or outdated content.

What is the solution:  Validating the collected data against trusted sources or performing data consistency checks can help identify and rectify such inaccuracies. In cases where no immediate answer is available, it may be necessary to wait for the website administrator to address the error on their end. During this time, it is important to periodically check the website for updates to ensure that the corrected data becomes available. 

8. Time-specific:

Certain web scraping projects may require collecting data that is time-specific, such as stock prices or real-time updates. If the scraping process is not synchronized with the time-sensitive nature of the data, wrong results can be collected.

What is the solution: Cache the page and record the cache time to infer the data was collected correctly at the time of crawling. We can further test the crawler on specific examples on the live site to ensure they are collecting the current live data, increasing our confidence the website has updated since the crawl.

Problem #3: Can’t use the results

Reasons why you cannot process the results on a web scraping project: 

1. Formatting or file naming issues:

These issues can arise when the collected data is not consistently formatted or when the files are not named in a standardized manner, making it challenging to parse and analyze the data effectively.

What is the solution:  Cleaning inconsistent fields, converting data into a uniform format, and performing processes to address formatting issues in the data. This includes removing or correcting erroneous characters, handling missing or incomplete data, and resolving inconsistencies across different data sources. This can involve manual review or automated checks. 

Problem #4: Missing results 

Reasons why results were missing on a web scraping project: 

1. Blocked by the site:

Some websites actively block web scraping activities by implementing measures such as IP blocking, CAPTCHAs, or anti-scraping mechanisms. As a result, the web scraper is unable to access and collect the desired data from the website.

What is the solution:

Determine how the website notifies the crawler of being blocked. It could be a 403 status code or a message like “We have detected unusual activity from your IP”. Crawlers can be configured to detect when they are blocked and retry opening the webpage or save appropriate errors into the results. Crawling anonymity code can be adjusted and the crawler can rescan all the blocked pages to complete the result set.

2. Site layout changed:

Websites often undergo updates or redesigns that can alter the structure and layout of the web pages. These changes can disrupt the scraping process, causing the scraper to miss or incorrectly extract the desired data due to the new organization or placement of elements on the site.

What is the solution:

Update the scraping code to adapt to the new structure. Review and modify the scraping script to accurately locate and extract the data from the revised layout. Regular monitoring of the target website’s updates and implementing a robust error-handling mechanism can help address layout changes effectively.

3. Products on the site were removed:

The website may remove or modify the products or information being scraped. This can occur due to changes in inventory, updates to product listings, or temporary unavailability of certain items. As a result, the web scraper may miss the data related to these removed products or information.

What is the solution: In this case, no immediate solution is available. The only thing we can do is to keep track of changes in website structure and data sources. Regularly check if the required data is available and adapt the scraping process accordingly.

Problem #5: No response to my request

Reasons why we did not respond to your request on the web scraping project: 

1. Communication Breakdown:

If you didn’t receive a response to your request after 24 hours, most possible it was due to technical issues or lost requests that prevented us from receiving or accessing the request, such as email delivery problems, server downtime, or accidental deletion. 

What is the solution: We recommend clients resend the request if they do not hear back within 24 hours. To avoid such issues in the future, we implement a more robust communication system, including alternative contact methods: a project management system or chat. Additionally, regular monitoring of communication channels will be ensured.

2. Time and Resource Constraints:

We may have received multiple requests simultaneously and had to prioritize other projects that were more urgent and unfortunately failed to notify the client about the time constraints.

What is the solution: Again, we recommend clients to resend the request if they do not hear back within 24 hours. On our end, we will reinforce to our team members the importance of replying promptly to any message, even if the answer involves telling the client that the request will be tackled at a later time due to time constraints. Another solution that should take place is to establish a clearer process for evaluating and prioritizing web scraping requests based on factors such as importance, impact, urgency, and available resources. Communication with requestors can help set realistic expectations and provide updates on the status of their requests.

3. The request requires additional testing:

In some cases, the initial request may require additional testing before we can address it, but we failed to notify you about this delay. In such cases, you will eventually receive an answer, but it may not be prompt.

What is the solution: Implementing effective communication channels will help ensure that requests are received and processed promptly.  Once again, encourage clients to resend the request if they do not receive a response within 24 hours.


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