What Is Parsing and How Does It Work
Often, necessary data cannot be aggregated manually, or it takes a large amount of time. That's when parsing (web scraping) comes into play — it is the process of automatically collecting information from websites in a structured format. It helps anyone who deals with data aggregation in any form: online businesses and their representatives, marketers, analysts, and SEO optimizers.
Today we will break down what parsing is in simple words, how it works, and which services allow you to perform the task of data collection most quickly and efficiently.
How parsing works
From a technical standpoint, parsing is a method of extracting data from HTML pages of a website. For better understanding, let's introduce a few basic terms.
HTML — a markup language that is the foundation of any page. HTML tags explain to the browser how to display text, where to insert links, and where an image is located. A parser downloads the HTML code to extract the necessary pieces of information from it.
XML — a language for storing and transmitting data between programs. It is in XML format that websites usually export their products. It is much easier and more convenient to parse the necessary information from it.
JSON — a popular data exchange format that is understandable to both computers and humans. Information in it is stored in the form of "key-value" pairs, for example, { "name": "Sergey", "age": 40 }. Most websites today use JSON when loading products, from which parsers extract the necessary data.
CSS selectors — these are a kind of pointers to specific elements of a webpage. For example, if you want to find all headings highlighted in green, you will need the selector h2.green.
XPath — a query language that allows you to navigate the structure of an HTML or XML document like a navigator. You can give it tasks like "Find the third paragraph inside the table located in the right column, and take the link from it." It is indispensable for very complex and deep code.
Regular expressions — a tool for finding and extracting text by a pattern. For example, if you need to parse all phone numbers in the format "+7 (999) 123-45-67", a regular expression will do it instantly.
Now we can list and explain the main stages of parsing:
- Data retrieval. At the first stage, the parser sends a request and downloads the source material. The source can be a webpage (HTML code), a website API (returning information in a pure form, for example, in JSON), or a ready-made file (XML or CSV export).
- Data preprocessing. The downloaded data array needs to be put in order: unnecessary elements (HTML tags, CSS styles, etc.) that interfere with the analysis and have no value for obtaining the result are removed from the raw text.
- Structure analysis. The program studies the skeleton of the received document and evaluates the hierarchy: where each heading is located, in which block the price is, and so on.
- Data extraction. Using navigation tools (XPath, CSS selectors, etc.), the parser selects the necessary data: product names, contacts, prices, or links.
- Data saving. The collected information is structured neatly in a convenient format: a simple table (CSV, Excel), a database (SQL), or a flexible file for data exchange (JSON).
Parsing tools — an overview of popular solutions
Knowing what parsing is, we can move on to reviewing tools that differ in capabilities, pricing, and additional options. Let's look at the most popular ones, based on the format of working with content.
Specialized programs
If you need a powerful and functional tool that is installed directly on your computer, you should look into specialized programs. They offer extensive options for configuring parsing, often work through a visual interface (point-and-click), and are suitable for regular data collection from a wide variety of websites — from simple online stores to complex web applications with dynamic content loading.
Octoparse — a popular data parser used to collect information about users, products, and services, as well as to conduct various research. With it, you can parse websites by element type, exporting the results to Excel, CSV, and via API, without knowing how to code.
Octoparse has a free version with a limit of 10 tasks per month. More advanced plans start at $69 per month, and there is customization of the personal account — in this case, the rate is set by mutual agreement.
ParseHub — a web scraping program for automating the collection of information from the internet. It is actively used by marketers, researchers, analysts, and e-commerce specialists. Data export is available in Excel, API, or JSON formats.
The free plan in ParseHub includes up to 5 tasks, the data for which is stored for 14 days. The price of the standard version is $189, and the professional plan with 120 tasks and the saving of files and images will cost $599 per month.
WebHarvy — specialized data parsing software with support for multi-page scraping, keywords, and JavaScript. Among its advantages is smart pattern recognition, which requires no additional configuration.
WebHarvy is notable for its affordability: the basic version of the software for one user will cost $129 per year. And for $699, you can buy an annual license with an unlimited number of users in the account.
Online services
For those who do not want to overload their computer or need a ready-made infrastructure for large-scale data collection, cloud-based online services are the ideal choice. They take care of all the technical hassles, from managing proxies and bypassing blocks to providing data through a convenient API. Such platforms allow you to quickly connect to information collection without complex installation and configuration.
Import.io — a website for collecting information on the internet in real-time. It allows you to extract phone numbers, IP addresses, emails, and images with full data analysis. More than 100 web sources are available for simultaneous work.
Import.io does not have a free or trial version. There are two main plans — Fully Managed and Self-Service Solution, and the price for both of them is calculated individually by a service manager depending on your tasks and needs.
Diffbot — a parsing service for collecting data from organization websites, news sites, and product catalogs. It is designed to work with large volumes of information, while clients only have access to a web version in English.
The free version of Diffbot provides quite a few parsing capabilities and is activated without linking a bank card. Paid plans start at $299 per month.
Apify — a data collection service that has been operating since 2015. It functions as a simple and accessible web environment using only frontend JavaScript. With Apify, you can collect and structure any information from websites with subsequent export to CSV, Excel, or JSON.
Apify has a free version, but it involves a payment of $0.3 for each new compute unit. The Starter plan will cost $29, and the most expensive Business plan is $999 per month.
ScraperAPI— a system for extracting data from the internet with flexible solutions for individual users and large companies. A unique advantage of the service is its function for detecting and bypassing bots, due to which almost all of its requests reach the websites and return with a result.
ScraperAPI does not have a completely free version, but you can use a trial with limited features for 7 days. For personal use or small projects, the minimum Hobby plan priced at $49 per month is perfect; more expensive service packages will cost from $149 to $475 per month with a significant expansion in the volume of requests and data storage duration.
WebScraper — a parsing program designed to work with big data, including databases, product catalogs, and various lists. It features an intuitive interface and works perfectly with complex websites that have multi-level navigation.
In the free version, WebScraper works as a browser extension with a minimum of working functions, which only include exporting data to CSV and XLSX. Therefore, it is better to start with the Project plan priced at $50 per month: it provides almost all the necessary resources for parsing, and you can also sign up for a free one-week trial for it. The Professional and Scale packages for $100 and from $200 per month, respectively, increase the number of available links, parallel tasks, and data storage duration.
Niche tools
Parsing can be not only general but also for specific professional tasks. A separate niche is occupied by highly specialized tools tailored for a certain type of data or source. They are not suitable for universal tasks, but they are useful for working in specific areas.
Screaming Frog SEO Spider — a niche tool for SEO specialists that allows conducting website audits and identifying inaccuracies in them. Thus, the software can detect broken pages, duplicate titles, pages with missing descriptions, and generally any pages with certain repeating fragments. In the search bar, you can enter not only the entire website but also a number of selected pages.
The free version of Screaming Frog SEO Spider allows limited data parsing with a limit of 500 URL links. The paid version opens up unlimited possibilities for parsing and crawling, and it will cost $279 per year.
Netpeak Spider — an advanced parser for studying web resources and finding errors in them. The service allows you to identify code errors, incorrectly configured redirects, duplicate content, and other problems. All the obtained information can be exported in Excel format.
Netpeak Spider has a 14-day trial. Paid solutions start from $20 monthly, and the most expensive plan is $99 per month.
Scrapingdog — a parsing program with the ability to solve a variety of tasks, but most often it is used to collect data from the LinkedIn social network. The service allows you to collect company and user profiles according to selected criteria and exports the data in JSON format.
You can use Scrapingdog for free for 30 days. After that, you will need to subscribe to the service: this is a minimum of $90 per month, and a maximum (Business plan) of $500 per month.
Conclusion
Parsing is an indispensable stage in the process of making money online for specialists from many online spheres. With the help of parsing, you can quickly collect data that is publicly available. There are plenty of services on the Web that provide parsing services for a wide range of topics or with specific features — choose the one that best solves your tasks and get to work. And in future articles, we will delve deeper into the topic of parsing and talk in more detail about this technology and the services that allow it to be implemented.
Frequently Asked Questions
Parsing is the process of automatically collecting information and converting it into a structured format — a spreadsheet or a database. This is necessary to quickly obtain up-to-date data in large volumes when manual collection is impossible or takes too long. For example, parsing is useful for monitoring competitor prices, finding clients, or analyzing market trends.
To start, an understanding of website logic and basic knowledge of HTML is enough — to navigate the page structure. If you choose visual tools like Octoparse or ParseHub, coding knowledge is not required. For more complex tasks, Python skills (BeautifulSoup, Scrapy libraries) and an understanding of data formats (JSON, XML) will be useful.
Yes, parsing itself is not prohibited, but it is important to follow the rules. Collecting publicly available information in reasonable volumes is legal, however, you cannot collect personal data without consent, create excessive load on website servers, or violate the resource's terms of use if they explicitly prohibit automated collection. It is always worth checking the site's robots.txt file — this is good practice and a marker of good faith.
Essentially, they are almost synonyms, but there is a technical nuance. Scraping is specifically the process of extracting 'raw' data from a webpage. Parsing is a broader concept that includes not only extraction but also the subsequent breakdown, analysis, and conversion of this data into the desired structure. In a professional environment, these words are often used interchangeably.
The main limitations are divided into technical and legal. Technically, sites can protect themselves from parsing using CAPTCHAs, IP address blocking, dynamic content loading via JavaScript, or restrictions in the robots.txt file. Legally, you cannot collect personal data without consent, bypass explicit technical blocks, or use the collected data for competitive espionage if it is prohibited by the site's terms of use.
Both languages are excellent choices, but the selection depends on the task. Python is considered the classic choice due to the huge number of specialized libraries (BeautifulSoup, Scrapy, Requests) and the simplicity of writing code. JavaScript (Node.js) is indispensable if you need to parse sites with intensive use of dynamic content, as it can work with the DOM directly, but for complex projects, more code may be required for data processing.
To bypass restrictions, a set of measures is used: IP address rotation through proxies, changing the User-Agent, and integrating automatic CAPTCHA recognition services. Anti-detect browsers deserve special mention — they spoof the device's digital fingerprint (screen resolution, fonts, time zone), simulating a real user. Combined with high-quality proxies, this is one of the most effective ways to remain invisible to security systems. The main rule is to act carefully and not create an anomalous load on the server.
The robots.txt file is not a law, but a recommendation, yet it shouldn't be mindlessly ignored. First, try to find alternative data sources: perhaps the site has an open API or official data exports. If parsing is still necessary, observe etiquette — reduce the request rate so as not to overload the server, and make sure you are not collecting personal data. In controversial cases, it is better to consult a lawyer, especially if the data is planned to be used for commercial purposes.
