The internet is full of useful data for price tracking, lead generation, sentiment analysis, stock market research, and many other use cases. Collecting it efficiently and in a timely manner requires carefully selected tools. With a bit of knowledge of web scraping, you can collect this data too.
What is web scraping?
To simplify a bit, web scraping uses automatic means to extract and format data from the world wide web. Usually it is done by using automated bots, called scrapers or scraper bots. But before web scraping can begin, the target website must be indexed.
The process of indexing websites is called web crawling. Imagine a bot visiting a website and making a list of everything there—every text, image, and other element. A user can then command a scraper bot to extract the needed data without downloading the whole website.
The final web scraping result is usually packaged in a user-friendly format, such as HTML, XML, JSON, or a simple Excel file (CSV). Businesses and individuals later analyze this data to make data-based decisions in various business and scientific fields.
Technically, you can perform both actions manually, but using automated bots is much easier and less time-consuming. A bot can extract data from a website in minutes, while the same amount would take a person weeks to process by hand.
Web scraping software
Building a Python web scraper yourself is a more effective web scraping method. It gives more flexibility to build your own rules for scraper bots, which is important for accessing data from less popular websites. Scraping software uses predetermined templates that might not fit your use case or the target website.
However, creating a Python web scraper requires significant knowledge of the programming language and using scraping libraries, such as BeautifulSoup and Scrapy. It shouldn’t be an issue for an experienced Python programmer, but if you are just a beginner, there is no shame in starting with web scraping software.
Octoparse is one of the most popular web scraping software solutions with a full graphical layout and easy-to-use interface. Their Smart and Wizard Modes allow even those with zero coding experience to find and extract the needed data. It supports multiple data formats, including such ordinary ones as Excel sheets.
Some users find Octoparse’s customization options limited. The limited set of tools might make scraping certain websites impossible. However, I haven’t encountered such issues frequently. The one time I struggled with a competitor’s website, I reached out to their support, and they helped me set the settings correctly.
ParseHub does seem like an even easier alternative to most users. I agree that their onboarding process is much easier, so you are quick to start. But this might as well be because of a lack of settings. With ParseHub, you’ll need to select many elements by hand, which works best for small scraping projects.
If you need data at a larger scale, it will take some time to mark all elements and export them to when you need JSON or Excel formats. I prefer Octoparse as it has a lot of templates for popular websites and is a bit cheaper. However, ParseHub is superior for niche websites when you don’t have any workaround for marking elements by hand.
Proxies for web scraping
No matter what route you will take in terms of proxy software, you will need a proxy server for web scraping. Any web scraper you use will send hundreds of requests to websites. This is far more than an ordinary visitor would, and thus, websites will try to limit your access to avoid server overload.
Scraping without a proxy is not just likely to get your home IP address restricted or even blocked, it will not provide full access to the needed data. Most websites impose geo-restrictions on their visitors for adjusting prices, visual elements, or other data.
For example, if you need to access data about a specific product sold only in a specific region, you will need an IP address from that region. Using a proxy server will conceal your original IP address and show a needed region for the target website.
Proxies work by acting as intermediaries between you and the internet. You first send a request to a proxy device (a PC or a server, for example), which forwards the requests as if connecting on its own. Such a process conceals your IP address and allows you to select a needed geographical region for connection.
Proxy type
A large pool of datacenter proxies is best when you need to scrape large amounts of data from a website that doesn’t have many anti-scraping measures. These proxies are hosted on fast, professional servers, while their IPs are hosted virtually to lower the costs. Unfortunately, such proxies are relatively easily detected by websites, so if your project is small, I recommend going with residential proxies.
Residential proxies are hosted on physical devices located in residential areas. In comparison to datacenter proxies, these intermediaries are slower, but their connection is more genuine. Your scraper is least likely to get CPATCHAS or other restrictions while using residential proxies.
Proxy protocol
The proxy protocol isn’t especially important for web scraping. Most software will accept HTTP proxies, as this is the basis of most websites. But if you want faster transfer speeds and more versatility, I suggest going with SOCKS5. It’s an advanced protocol made to support the newest network rules, such as IPv6.
So, in general, my advice is to go with a SOCKS5 residential proxy. Unlike with HTTP datacenter proxies, you are unlikely to get IP blocks, low transfer speeds, and won’t have any compatibility issues with scraping software.
Conclusion
Web scraping software, such as Octoparse, and proxies, such as SOCKS5 residential ones, are all you need to start web scraping. Large web scraping projects might require you to learn Python and invest in more than one IP address, but this is enough to get your feet wet.