Data has recently become the need of almost every business. For this reason, web scraping has become one of the most popular topics today. It is frequently used by many businesses, platforms, and especially artificial intelligence projects. It is now easier and faster to obtain data from websites. Data can be scraped easily with a web scraping API or any library in the Python programming language.
Many data extraction options exist, such as web scraping API, a Python library, or manual scraping data. However, these methods have advantages and disadvantages over each other. In this article, we will talk about which method should be preferred for which situation. Next, we’ll review the most popular Python web scraping libraries.
Which Method Should Be Preferred for Web Data Extraction?
There are two most popular methods for developing web scraping applications. Using a Python library or using a web scraper API.
A popular web scraper API like Zenscrape provides businesses with many services without additional development. Chief among these is the proxy pool and automatic rotation of IP addresses. This service allows users to create automated web scraping processes without additional development.
In addition, it is easier to use in applications with distributed software architecture. Because it integrates easily into all programming languages. Its structure is quite simple and it can also provide location-based scraping service.
On the other hand, performing web scraping using a Python library is completely free. Adjusting the configurations in many matters belongs to the developer.
Python web scraping libraries are open source so you can be a part of the community. Since there are multiple libraries in Python, it is possible to try alternatives easily. In addition, it is very simple to use.
Most Popular Web Scraper Libraries to Extract Data in Python
In this section, we will examine 5 Python web scraping libraries. These libraries are the most preferred web scraping libraries by developers.
Beautiful Soup is the most popular web scraping library among Python libraries. This library is used to pull and analyze data from web pages. It is used to shred HTML and XML documents and allows you to extract tags and text from these documents. It is fast and effective in data extraction and analysis.
Scrapy is a Python-based open-source framework. It allows extracting data from structural content such as HTML and XML. It can do scraping and crawling fast enough, especially on websites. Scrapy can automatically track data changes on websites and automate data collection.
Requests, a popular library in the Python programming language, allows us to exchange data by communicating with websites over the HTTP protocol. The Requests library, which is frequently used especially in web scraping projects, makes it easy for us to make HTTP requests with a simple interface.
Selenium automates web crawlers and facilitates various tasks such as testing web applications, data collection, and bot creation. Also, Selenium, which is an open-source software, can be used with different programming languages.
Especially often used in web scraping projects, Selenium offers a simple API that provides all the necessary features to control the web browser with the programming language.
LXML is a library in the Python programming language that provides XML and HTML processing functionality. This library reads, writes, edits, and queries XML documents and HTML pages, making it highly useful for collecting data from web pages.
In conclusion, with the increasing importance of data, data scraping processes have become easier. Businesses and developers can get the data they need from the internet using the web scraper API or Python libraries.
Q: Which Python Tools Work as Web Scrapers?
A: Python offers developers many libraries to facilitate data scraping from web pages. With the libraries it provides, developers can get all the data from any web page. Some of the web scraper libraries available in Python are as follows.
- Beautiful Soup
Q: Can Web Scraping Processes Be Automated With a Python Library?
A: Yes it can. However, this is not the best method to scrape data because it may be blocked when extracting data from target web pages. The target website can block the IP address. Therefore, if you want to perform an automated web scraping process with a Python library, it is necessary to configure the web scraping code very well.
Q: Does the Zenscrape API Provide Proxy Pooling?
A: Yes it does. Zenscrape API provides a large proxy pool to ensure that web scraping processes are not disrupted and that there is no blocking. IP addresses are rotated automatically in this proxy pool.
Q: Is the Zenscrape API a Free Web Crawler API?
A: Yes it is a free API. It has 5 affordable subscription plans for web crawling. One of these plans is the free plan. It has a limit of up to 1,000 requests per month.