Data is frequently used in the development processes of applications that people use frequently in daily life. In fact, there is a strong correlation between the increasing data set and the reduction of errors in the application. Today, almost every application, especially artificial intelligence applications, needs up-to-date and quality data.
There are many different ways to obtain data. The most popular of these ways is to scrape data from target websites using web scraping APIs. With web scraping APIs, data from target websites are regularly obtained in an automated way and data flow is provided. This helps the dataset grow with up-to-date and accurate data.
Web scraping APIs need to make some adjustments automatically in order to avoid any blockage while obtaining data from target websites. Proxy settings are the best example of this. In addition, providing a large IP pool helps the processes to proceed without interruption for users.
The most preferred service offering web scraping today is the zenscrape API. With the API it provides, zenscrape automatically provides data from target websites without any hindrance or interruption. And within seconds. Zenscrape API, which has more than 10,000 customers, can be integrated into all programming languages. It provides a fast and easy integration.
Other APIs that provide web scraping services, such as the zenscrape API, are generally used by integrating with the Python programming language. In this article, we’ll first cover why Python is such a popular programming language, and then we’ll take a look at why Python was chosen for web scraping.
Why is Python popular
Reasons for Python’s recent popularity in 3 items.
1. Active User Communities
Python, with the advantage of being used for a long time, has a wide user network from amateur level to experts. Access to information and necessary documents is a serious problem, especially in individual programming. Thanks to the large user base of Python and the active user communities created by this audience, this problem is largely resolved for Python. Problems encountered during programming can be solved by users in these communities in a short time, or educational files are shared by users on these platforms.
2. Sponsor Support
The popularity of programming languages increases drastically, especially as giant companies integrate these languages into their work. In addition to using the software language chosen by the companies in their applications, they produce various educational tools for learning the languages they support. Another factor that makes the language widespread is the existence of these educational tools. The giant sponsor of Python is Google. Google has integrated Python into many of its platforms and applications since 2006; produced support tools and documents. Other companies using Python include Disney, Mozilla, and Bank of America.
3. Python in Big Data
Python is the second most common programming language used in data science after R. Its use has also increased in recent technologies, including artificial intelligence, deep learning, and cloud systems. Python’s ability to analyze data easily and its user interface is among the reasons why it is preferred.
Web scraping in Python
We’ve mentioned some of the reasons why Python is so popular. So why should we choose Python over other languages for web scraping, we’ll touch on that now.
Here is the list of Python features that make it more suitable for web scraping.
Ease of use: Python is easy to code. “;” You don’t have to add semicolons. or “{}” curly braces anywhere. This makes the code less messy and easy to use.
Large collection of libraries: Python, Numpy, Matlplotlib, Pandas, etc. It has a very large collection of libraries offering methods and services for various purposes such as Therefore, it is quite suitable for data scraping and manipulation of extracted data.
Dynamically typed: In Python, you don’t need to define data types for variables, you can use variables directly wherever you want. This saves time and makes your work faster.
Easily understandable syntax: Python syntax is easy to understand, basically because reading a Python code is very similar to reading an English expression.
Small code, big task: Web scraping is used to save time. What good does it do if you spend more time writing the code? Well, you don’t have to. You can write small code to do big tasks in Python. Thus, you save time even writing the code.
Community: What if you get stuck writing the code? You do not need to worry. The Python community has one of the largest and most active communities where you can get help. This is one of the most important items.
As we know, Python is used for various applications and there are different libraries for different purposes. In our further demonstrations, we will use the following libraries:
Selenium: Selenium is a web testing library. Used to automate browser activities.
BeautifulSoup: Beautiful Soup is a Python package for parsing HTML and XML documents. It creates parse trees that help extract data easily.
Pandas: Pandas is a library for data manipulation and analysis. It is used to extract data and store it in the desired format.
Conclusion
Web scraping has become very important as the value of data is increasing day by day. There are many more advantages that web scraping brings to businesses. To take advantage of these advantages and privileges, visit the zenscrape API, which is easily integrated into all programming languages.
