Web Scraping Guide for 2025 - How it Works, Types, Legality, Tools, etc.
12 min read
12 May 2025
Louis
Web Scraping
This is a term that comes up a lot: Web Scraping. What can it be used for and why is it used so much? Well, the reason is that the web is full of information. Imagine for a moment that you could harvest this information for yourself, the possibilities that it could open up for you. That is why this field has become very popular.
Web scraping is simply the collection of data available on the web. It helps meet the needs of data analysts to quickly obtain relevant data to analyze. This practice contributes to the marketing or growth hacking strategy of companies.
You can do Web Scraping using an API, a browser extension, or even a Python library like BeautifulSoup or Scrapy. The reason why web scraping techniques are used is that we want to enhance existing databases to allow for a more in-depth analysis of a project.
There are a lot of reasons to do web scraping. Here are some examples:
Sites like LinkedIn are often scraped to obtain additional information about a certain type of profile. For example, if you are a marketing agency that offers SEO optimization services, your team could scrape LinkedIn data to obtain the profiles of marketing teams of top companies.
You might also want to get statistics on a domain and go to Wikipedia to retrieve the information. You may want to perform semantic analysis on different product reviews. To do this, you could scrape sites like Amazon or Twitter to get reviews or small text reviews written by Internet users.
Extracting data from a web page is a quick way for businesses to build a usable database. It saves you from manually collecting content from certain websites. With Web Scraping, you also minimize the risk of copy-paste errors. Automating data extraction using a Web Scraper allows the business to always work on up-to-date information.
Of course, this is not an exhaustive list but it is to give you an idea of all the fields of application of the field.
Legality of Web Scraping
Before getting to the heart of the matter, it is important to clarify the legality of web scraping. As we are touching on the field of data, it is always legitimate to wonder if this technique and the use of this data are legal.
Rest assured, web scraping is legal, under certain conditions:
This is a gray area and that is why we often assume the legality of web scraping. To put it simply, web scraping is governed by the general country laws of the site on which the data resides.
However, it is strictly forbidden in almost all countries to collect data belonging to a site without permission, and you expose yourself to sanctions if you try to scrap it and get caught.
In reality, it is still very unlikely that you will get “caught” because it is difficult to trace the identity of the scraper. However, it is not unlikely that on sites that are used to being scraped, your IP address will be banned if it is detected as having fraudulent activity. If you want to know more about the legal environment, do not hesitate to contact us to look at your project.
Finally, it is important to always look out for changes in individual country laws regarding web scraping to ensure you stay out of trouble.
The user of a web scraper must first specify the URL of the site or pages he wishes to explore. It is then necessary to indicate very precisely the sections that must be analyzed:
The web scraper will then explore the indicated pages and most often produce a .CSV file that can be opened in Excel or Google Sheets.
Here is a non-exhaustive list of activities that can benefit from web scraping.
If you are in the business of selling any type of item, you should make a point of comparing prices offered by major e-commerce sites, ideally on a day-to-day basis.
For many businesses or executives, it is valuable to know what the search trends are among Internet users in a field, or how demand is changing in a particular sector.
Some sites pride themselves on spotting good deals and directing their visitors to them. This is called affiliation because the advice site is paid based on the traffic it brings to the destination site. By necessity, web scraping helps to spot the good deals in question. This activity is found in particular in real estate.
Media, politicians, and also companies are curious to know the public's feelings about a topic. Web scraping can therefore help to decode what the general mood is on a subject at a specific moment.
Various types of web scraping can be used for various purposes. Below, we’ll share some of these web scraping techniques.
Quite often, web scraping is done from a web browser like Chrome or Firefox. The advantage is that the user can order the capture of information "on the fly". If he visits a site that he considers interesting, he can then activate a web scraping extension and configure it by inspecting the presentation of the information.
In some cases, the most appropriate solution will be to create a custom web scraping tool, using a language such as Python. The downside is that it is necessary to have a good command of programming beforehand.
There are many web scraping software on the market and they usually have more extensive configuration possibilities than browser extensions. It is usually necessary to dedicate a high-capacity machine to this potentially time-consuming activity for several hours in a row. In fact, it happens that a web scraping tool is required to analyze millions of pages.
Some web scraping service providers offer the possibility to operate from their servers, which increases convenience and effectiveness.
Data Scraping
Data scraping is organized into two main parts: retrieving the HTML code of the web page and analyzing the collected data. A web scraping project takes place in five stages:
Below, we will elaborate on the most important part of these steps:
The first thing to think about is data: what do you need? Clearly prioritizing the data you are looking for will give you a clear starting point.
This first step consists of designing your database, and defining which data are priority and can provide value without being inefficient and filled with unwanted data.
Using an airline as an example, you might decide that retrieving flight schedules and prices is necessary for your operations, whereas retrieving flight numbers and the number of stops would be useful but dispensable.
The goal of this step is to keep the scraping process as simple as possible to ensure that it runs smoothly. This also helps to create a database that does not contain obsolete or polluting information.
Once your database is set up, you need to look at the sources. We recommend that you start by exploring all the public sources that are likely to contain the data you are looking for: online directories, blogs, open data, etc.
After that, you can apply filters to this list of sources. By looking at the important data that interests you, you will be able to determine the criteria to prioritize within these sources.
You may need to find one source that provides you with the most recent data and another source that provides 100% reliable data. In these conditions, it is interesting to scrape both sources and combine the results to obtain quality data.
In our airline example, one criterion that could be important would be to choose airline sites that have little or no anti-scraping protection: you might be looking for easily accessible information to quickly create a comparison platform.
In summary, the goal is to search for as many sources as possible that fit your criteria and to select the most relevant and best-suited sources for your needs.
The 3rd step will be to choose the web scraper best suited to the sources you have just selected.
There are free or paid tools, no code or requiring development skills. In the event that you have several sources to scrape, you may be faced with different problems.
Maybe your first source, which only has a few pages to scrape, has anti-scraping protection while the second source you are interested in does not but instead requires scraping thousands of pages.
You would then have to use several web scrapers, it's up to you to adapt and make the right choice or request for our help!
If an airline site requires a CAPTCHA test, you will need a web scraper that can bypass this test. Another example is if you have 10 sources that represent hundreds of thousands of pages to scrape, you will need a tool powerful enough to handle this load.
To continue, you will need to install the web scraper(s), configure it to browse the sources that interest you, and retrieve the expected and structured data.
This step alone deserves an entire article, due to its importance and the number of different tools available on the market. Contact us if you would like to explore this point further, or subscribe to the newsletter so you don't miss the release of our next articles on web scraping.
The last important point for web scraping is to monitor your web scraper during its execution. The goal is to ensure that it retrieves the completeness of the data because we are never safe from a surprise on websites that we do not know!
Indeed, your scraper may be configured to crawl the 22 result pages of a site, but an unforeseen event on the source or an error in the scraper configuration interferes with the scraping.
For example, to program the scraper to crawl the flight results pages of an airline website. Retrieving data on pages 1 to 22 could result from scraping pages 0 to 21 based on the indexing of the source pages: it is possible that on the target site, page 1 corresponds to an index number 0, page 2 to an index number 1, and so on.
To avoid having incomplete scraping or different from expected, it is important to monitor your scraper!
Best Web Scraping Tools in 2025
Do you need to quickly collect data from websites to prepare a marketing campaign? You can create your scraping tool with Python or opt for software from the market. The choice depends on your level of knowledge of HTML code.
Easier than Python programming, this practice is suitable for those who want to do Web Scraping without knowing how to code. This tool allows two websites or two applications to exchange information without going through Python programming.
With APIs, you are freed from writing code. In addition, the data collected is directly usable by the machine. It is therefore not necessary to extract the data from the source code. This avoids the tedious step of data scraping.
Not all websites provide an API for data extraction. In this case, you can use a browser extension or a dedicated data scraping software to collect the information. As with APIs, using these web scraping tools does not require writing any code with Python.
Browser extensions do not take up hard disk resources. Download the extension to the browser and let it guide you to collect data. WebScraper, Data Miner, and Data Scraper are some examples of browser extensions to try.
Data Scraping software offers more efficient features for extracting content from a web page. Most of them are paid. Among them are Octoparse, ParseHub, and Import.io. Each Web Scraping tool has its specificities. To make the right choice, clearly define your research objectives beforehand.
Are you thinking of using these web tools for data scraping? Python libraries allow you to collect data that meets your business needs. By writing your code, you can extract more data. These are better formatted with Python. BeautifulSoup, Selenium, and Scrapy are the few Python libraries dedicated to web scraping.
The Python library BeautifulSoup is one of the oldest web scraping tools. Here, scraping can be done using simple scripts. BeautifulSoup is an easy-to-use way to extract targeted data from one or more pages of a website. This open-source tool is powerful in parsing XML and HTML data. BeautifulSoup often works in combination with the Requests library which is responsible for extracting the HTML code of the web page.
Scrapy is another open-source library for Python. Capable of extracting HTML source code from multiple web pages in parallel, Scrapy can also collect information from websites via APIs. This Python library uses object-oriented programming to create web scrapers. It is recommended for extracting large volumes of data.
Originally intended for website testing, the open-source library Selenium can be used for scraping with Python. The advantage of this tool lies in its ability to access the dynamic content of a web page. Selenium can work with BeautifulSoup and Scrapy. It provides the HTML source code and entrusts the analysis of the extracted data to the other two Web Scraping software.
Effective Web Scraping
Once the mission to be accomplished by a web scraper has been well defined, it will normally accomplish its task with speed. However, the preparatory stage may be long. There are many reasons for this.
Websites are designed to be a pleasure to use for their visitors. This usability factor is essential. Website creators do not care about crawling and analysis programs such as web scrapers. In fact, if they can make it difficult for them, they will not hesitate to do so, because why let your competitors benefit from the treasure trove of customer data?
So, a web scraping application must be brought to identify the precise sections of a web page that interest the analyst. To do this, it is sometimes necessary to interfere in the internal code of a web page and to have at least a minimal mastery of the languages that allowed its creation: HTML, CSS, JavaScript, XML, etc.
Some websites use "captchas" to verify that they are visited by humans and not by robots. There are various systems for automatically bypassing captchas, and their effectiveness varies. It also happens that some sites analyze the behavior of certain visitors and identify a "bot" such as a web scraper, in which case they block its access.
Some services manage to bypass such limitations, for example by multiplying the IPs from which the web scraper gives the impression of connecting and by spacing out requests in a way that appears natural.
Are you having an issue scrapping a website? Zyneto has the best team and software expertise to safely and efficiently scrape data from any website of your choice. Contact us today!
Web Scraping is the art of extracting data published on websites automatically. The use of software, Web Scraper, allows you to retrieve the HTML content of web pages and extract information useful to the company. Data scraping is legal when the data collected is made available to the public by websites. On the other hand, the extraction of personal data must comply with the terms of the GDPR.
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