Web Scraping, Data Mining Archives - Page 5 of 5

Some commonly used Practices and Approaches to bypass website block in Web Scraping

Some Commonly Used Practices and Approaches to Bypass Website Block in Web Scraping With over a decade of experience in the field of web scraping and data mining of all kinds of data from thousands of websites out there, Scraping Solution has written down some major techniques, tools, and services websites use to block IP addresses or restrict your entry to the webpage if they find any bot activity or scraping on their websites. User-Agent DetectionIP Address TrackingCAPTCHARate LimitingCloudFlareHTTP Headers InspectionIP Reputation DatabasesFingerprintingSSL FingerprintingBehavioral BiometricsAdvanced CAPTCHA There are some known techniques that websites use to detect bot activity. Some of these are easy to bypass while others are hard. With AI coming into the IT sectors, new techniques are getting into the market which analyzes the behavior of the request made to the website — these are most effective in blocking the scrapers and are almost impossible to dodge. In the article below, we have discussed each blocking system mentioned above with some possible hacks or techniques to bypass these kinds of blocks: User-Agent Detection: Old days were good days when you just faced ‘user-agent detection’ blocking services and just by rotating user-agents with each request, you can present yourself as a different type of browser or device with each request, making it more difficult for the website to detect that you are scraping its data. You can learn more about automated extraction on our detailed guide to web automation. IP Address Tracking: Using a VPN or proxy rotation service to send your requests with a temporary IP address can help you hide your real IP and avoid being detected or blocked by the website. This technique still works for 90% of websites, but you need to make sure that the proxies you are rotating are up and fast (only use credible service providers). For large-scale automation, you can also explore Google Maps scraping for location-based data. Rate Limiting: Adding a random delay between requests using time.sleep() in Python can help you avoid being detected as a scraper if the website has rate-limiting measures in place. Limiting your rate by adding random delays also feels more like human behavior rather than a bot action. Learn how Python data analysis can be combined with scraping for smarter automation. HTTP Headers Inspection: By rotating the headers for each request, you can avoid having a consistent pattern of header information that could be used to identify you as a scraper. You can also inspect the headers used by your browser when you manually access the website and use those headers in your scraping requests. Fingerprinting: By changing the headers for different devices and user-agents, you can avoid being detected through fingerprinting, which uses information about the device and browser being used to identify the user. You can also refresh the cookies, and if the website still blocks you, try changing the IP address too. In fingerprinting, you can play with all the options you got. SSL Fingerprinting: To go one step further and to avoid SSL fingerprinting detection, web scrapers may use techniques like rotating SSL certificates, using a VPN, or using a proxy service that hides their real IP address. Behavioural Biometrics: Getting avoided by Behavioral biometrics is tricky; however, we can avoid it by generating less data for behavioral biometrics, using a headless browser, randomizing mouse movements, scrolling on the website, etc. Cloudflare: The method of using Selenium to bypass Cloudflare is indeed one of the simplest ways to do so most of the time, but it is not efficient or reliable. It’s slow and can affect the memory of your system, and it’s also considered a deprecated technique. It’s recommended to use other methods, such as IP rotation or proxy servers, to bypass Cloudflare. Doing the above-mentioned exercises may not get you through Cloudflare as it has different levels of detection from basic to advanced. A website with an advanced level of Cloudflare might not let you through it even if you try everything above — doing regular scrapes of such websites is simply not practical. To manage such complex scraping projects, professional scraping consultancy can be highly beneficial. CAPTCHA: There are third-party services available that can solve CAPTCHAs for you, allowing you to continue scraping without interruptions. However, this is an additional cost and may not be a reliable solution in the long term.Use a VPN or proxy service: A VPN or proxy service can sometimes help to bypass CAPTCHAs by making it appear as if the request is coming from a different location.However, manually solve the CAPTCHA and use the headers from the manual request: This involves manually solving the CAPTCHA and then using the headers from the successful manual request in future scraping requests. This can help to reduce the number of CAPTCHA interruptions but requires manual intervention.Rotate headers every time a CAPTCHA shows up: This involves rotating the headers used in your scraping requests every time a CAPTCHA is encountered. This can help to bypass the CAPTCHA but requires additional work to manage the headers. It’s important to note that these techniques are not foolproof, and websites can still use other techniques to detect and block scrapers. However, implementing these techniques mentioned above can help to reduce the risk of encountering CAPTCHAs and make it more difficult for a website to detect and block your scraping activities. Note from Author Scraping Solution also provides consultation in web scraping and web development to companies in the UK, USA, and around the globe. Feel free to ask any questions here or request a quote. follow us on Facebook Linkedin Instagram

How Scraping Solution Captured its market share in 2022

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How Scraping Solution Captured Its Market Share in 2022 In the post-pandemic era, the IT industry has seen significant growth due to the shift towards remote work and digitalization. However, the market has also become highly competitive with a large number of IT service providers entering the market. In order to stay competitive and continue to grow, IT companies, particularly software houses, need to diversify their revenue streams by offering a variety of products and services, and exploring new market opportunities. Scraping Solution has gained market share by diversifying its operations and expanding into different areas of the market using strong marketing strategies and branding. By forming partnerships with other IT companies and organizations, the company has offered tailored services that meet the specific needs of its clients. This not only brings in more revenue but also provides valuable insights into the local market and potential opportunities for further expansion and diversifying its skill pool and operations. Therefore, for a software house to succeed in the market, it is essential to have a diverse range of skills and services to offer. Initially, Scraping Solution only offered web scraping and data mining services, but it has expanded its portfolio to include web automation, e-commerce management, and backend development. This diversification proved to be successful and beneficial in the first year of offering these new services. Some of our successful gigs on top freelance marketplaces are mentioned here along with the service details: Web Scraping Service on Fiverr Scraping Solution has a very strong and versatile portfolio at Fiverr in the web scraping and data mining niche. In fact, we are the TOP SELLER and MOST REVIEWED seller in this marketplace, competing with others with a huge gap due to our versatile skills, unbeatable customer care, and record completion time. Have a look at our service mentioned below by clicking on the image below: Web Scraping Service on Fiverr Web Scraping and Web Development Service on PPH Scraping Solution’s second most successful venture was on PeoplePerHour, where it offered two services: Web Scraping and Web Automation and Web Design and Development. Within a year, the company was able to serve around 200 clients from all over the world, particularly in the UK and the USA, and it established itself as a top-rated seller with the most reviews on the platform. You can visit our profile and services here and here. Scraping Service on PeoplePerHour Other than that, Scraping Solution has a very strong presence on LinkedIn and other social media platforms, which doesn’t only help with branding but also brings many opportunities in various ways. Conclusion For small or medium IT firms to be successful in the competitive market, they must diversify their skill set and focus on building a strong online presence. Without these efforts, it may be difficult for the company to sustain itself and compete with others in the market. Even the simplest of offerings can benefit from a proper diversification plan to stay afloat in the market. Written By Umar Khalid follow us on Facebook Linkedin Instagram

Why do we need Web Scraping?

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Why Do We Need Web Scraping? Web scraping is a technique that utilizes automated intelligence to quickly and efficiently collect large amounts of data from websites, rather than manually obtaining it. This process can save time and effort and is particularly useful for gathering large amounts of information. In this blog, we will provide detailed information about the process of web scraping to give you a better understanding of it. What is Web Scraping? Web scraping is a method of automatically gathering large amounts of data from websites, typically in HTML format. This data is then converted into a structured format using databases or spreadsheets for various purposes. Professionals can use various techniques for web scraping, including APIs, online services, or creating custom code. Many well-known websites like Twitter, Google, and Facebook offer APIs for accessing their data in a structured format. However, some websites do not provide such access, making web scraping tools necessary. The process of web scraping consists of two parts: The crawler, an AI algorithm that searches the web for relevant data, and The scraper, which extracts the data from the website. The design of the scraper can vary depending on the project’s scope and complexity, allowing for efficient and accurate data extraction. Basic Web Scraping Code in Python (Here, you may show an example script or link to your Web Scraping Consultancy page for expert guidance.) How Web Scraper Works? Web scraping can be used to extract specific data or all data from a website, depending on the user’s needs. It’s more efficient to specify what data is needed so that the web scraper can complete the task quickly. For example, when scraping a website for home appliances, one might only want data on the different models of juicers available, rather than customer testimonials and reviews. The scraping process begins by providing URLs, then loading the HTML code for those websites. Advanced scrapers may also extract JavaScript and CSS elements. The scraper then extracts the specified data from the HTML code and outputs it in a format defined by the user, such as an Excel spreadsheet, CSV file, or other formats like JSON files. Types of Web Scrapers There are several types of web scrapers available, each with its own advantages and limitations: Local web scrapers: These run on a computer using its own resources. They may use more CPU or RAM, which can result in slower computer performance. Browser extensions: These web scrapers are added to the browser and are easy to use as they are integrated with it. However, their functions may be limited. Software web scrapers: These can be downloaded and installed on a computer, providing more advanced features than browser extensions. However, they may be more complex to use. Cloud web scrapers: These run on the cloud, typically on a server provided by the company offering the scraper. This allows your computer to focus on other tasks since it doesn’t need to use its resources for scraping. For professional or large-scale needs, you can explore our Web Automation or Data Mining services that automate and optimize scraping processes securely. Benefits of Web Scraping Web scraping can be used in various ways to gain a competitive edge in the digital retail market. Pricing Optimization: Scraping customer information can provide insight into how to improve satisfaction and create a dynamic pricing strategy that maximizes profits. Web scraping for e-commerce management can also be used to track changes in promotional events and market prices across different marketplaces. Lead Generation: While web scraping may not be a sustainable solution for lead generation, it can be used to extract contact details from relevant sites in a short period of time. By creating a target persona and sending relevant information, businesses can increase their leads without breaking the budget. Learn more about our Scraping Consultancy to build ethical, scalable lead pipelines. Product Optimization: Web scraping can also be used to analyze customer sentiment, providing valuable insights into how to improve and optimize products. Competitor Monitoring: By scraping information from competitors’ websites, businesses can quickly update new product launches, devise new marketing strategies, gain insight into their budget and advertising, and stay on top of fashion trends. Investment Decisions: According to Investopedia, data analysis can guide better investment and business strategy decisions. Web scraping can be used to extract historical data for analysis, providing insights into past successes and failures and helping businesses make informed investment decisions. follow us on Facebook Linkedin Instagram

Beginner’s Guide for Web Scraping

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Best Web Scraping Beginners Guide Understanding the Power of Web Scraping and Why Python is the Best Choice Suppose we have a website that has tons of useful data, e.g., millions of email addresses or names of hospitals in the whole state, which needs to be downloaded. Manually, it would be very difficult to extract them into the computer for further processing, here comes web scraping. Web scraping makes it easier to extract data or information from websites or web pages into a personal computer in much lesser time without doing much manual work. It is done by writing code or programs that will reach the website, parse the HTML of the pages, and extract the data from predefined tags of HTML. Programming languages vary, but the most recommended programming language for web scraping is Python due to its processing speed, simplified syntax, mature community, and overwhelming adoption by corporate sectors. Let’s Understand by a Scenario Suppose you have a website that contains 30 thousand schools in the USA, UK, or say New York, and you need the names and contact numbers of these schools. Would you open 30K links and copy-paste the names and contact numbers manually? No. So, the developer writes Python code and executes it. The code sends HTTPS requests to the website and gets the response back from the website in HTML. It parses this HTML, searches for names and contact numbers of schools effectively, and stores them in Excel or JSON on the local computer. And this all takes much less time than doing it manually. For large-scale scraping or ongoing projects, you can also get help from Scraping Consultancy Services to build efficient, secure, and scalable scrapers. Why Python? Easy to learn for beginners with simple syntax yet a powerful programming language with a collection of more than 100,000 libraries and huge community support. Python is also known for fewer lines of code for large tasks compared to other programming languages like Java or C#. If you’re building automation-based solutions, you can combine your scraping with Web Automation tools for a more robust workflow. What You Should Know Before Learning Web Scraping Basic Programming in Python: Loops, if-else, try-except, list, dictionary, sets, Data Frame, typecasting, etc.Built-in functions like len, type, range, break, pass, etc.Boolean operators: or, and, not. HTML: HTML (Hypertext Markup Language) is used for creating the structure of web pages and formatting content. It’s standard for creating web pages, as almost all websites on the internet use HTML for their structure. It consists of elements represented by HTML tags; these tags contain content like text, links, and images enclosed between them or sometimes nested inside. Applications of Web Scraping Extract Data Images Contacts Customized Data E-commerce Product Scraping Comparison of Products and/or Prices Events Betting Statistics Scraping If your business involves real estate or price tracking, our specialized Property Data Scraping and Price Comparison Services can also help automate your data collection. How Data is Delivered The scraped data or content can be delivered in various forms. MS Excel (.xlsx) or CSV (.csv) files are most commonly used. Although JSON or SQL Databases could also be good options for structured data storage. Main Libraries for Beginners Pandas BS4 or Beautiful Soup Requests Selenium Extras Basics of Servers: Servers in web scraping are used to execute time-taking scripts that need more computational power. Linux Commands: Proficiency in basic Linux commands is necessary for effectively utilizing Linux servers for web scraping tasks. Converting (.py) to (.exe): pyinstaller is used to convert script.py into a script.exe file. Future of Web Scraping Web scraping will continue to be vital for data analysis, market analysis, and sentiment analysis to drive results and make data-oriented decisions. Further, web scraping can be extended into data mining, data preparation, and data visualization to support AI and machine learning projects. If you have any questions, are curious to learn, or don’t know where to start, or if you have a task you want done, don’t hesitate to reach out to Scraping Solution by email or WhatsApp live chat. follow us on Facebook Linkedin Instagram

Is web scraping legal?

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Is Web Scraping Legal? There has been great talk about the legality of scraping information from the internet in the past decade, especially since the boom of IT and automation. Companies in marketing and other business sectors were hunting for data from all available sources, but the question was always there: Is scraping legal at all? This discussion was not only among netizens but also in many courts in the UK, Europe, and the USA, where the legality of web scraping has been debated for years. Different rulings have been passed depending on the nature of data, but none have completely banned web scraping in any country. To better understand this, it’s important to know what kind of data we can scrape legally and what kind of data is illegal to scrape. Globally, data is divided into two major categories as mentioned below: Publicly Available Data Publicly available data is associated with company data, business sector data, or real estate data. This type of data is usually advertised on business directories, maps, or public/government databases by companies themselves to increase digital visibility. Such data is legal to scrape all around the world, and laws generally allow you to use it for marketing or business purposes. If you want to collect publicly available business or listings data, our team at Scraping Solution can help with custom data mining and Google Maps scraping solutions tailored to your needs. Private/Personal Data According to the General Data Protection Regulation (GDPR), personal data is defined as: “Personal data means any information relating to an identified or identifiable natural person.” Although this data is not publicly available on any directories, it sometimes appears online when stolen or sold by different apps or websites. Due to the rise of social media, users often publish their information on platforms like Facebook, Instagram, or LinkedIn, which makes it accessible to the public. However, scraping this kind of personal data is not legal in most parts of the world. The only partial exception is in California’s privacy law (CCPA), where scraping publicly available information voluntarily posted by users may be allowed under certain conditions (as of 2023). Therefore, it’s a good practice to avoid personal data and focus instead on business-to-business (B2B) data, which in itself is a vast and valuable field with plenty of untapped opportunities. Ethics of Scraping Even if you are dealing with public records, which are legitimate to scrape, Scraping Solution always follows strong ethical practices to keep the process transparent and responsible. If you are involved in scraping, you should consider the same principles: Always use an API to get the data if the API is available, rather than scraping it from the front end. Do not publish scraped data as-is on any platform. Avoid sending too many requests that affect website performance or resemble a DDoS attack. Always include a User-Agent string to inform the site owner that you are scraping publicly available data. Whenever possible, seek permission from the owner especially if it’s an e-commerce website. Be ethical when using someone else’s data and never misuse or devalue its original source. For organizations wanting to ensure compliance and efficiency, our Scraping Consultancy team can help you plan secure, compliant, and optimized scraping solutions. Conclusion While web scraping remains legal for publicly available data, it comes with ethical and compliance responsibilities. Understanding the distinction between public and personal data is crucial. By adhering to legal frameworks and practicing responsible scraping, companies can safely leverage data for marketing, analytics, and automation. If you’re unsure where your project stands legally or ethically, reach out to Scraping Solution our experts can guide you on how to collect, process, and use data the right way. follow us on Facebook Linkedin Instagram