Scraping Websites With Python And BeautifulSoup Semalt Advice

1. 23.05.2018 Scraping Websites With Python And BeautifulSoup – Semalt Advice There is more than enough information on the internet about how to scrape websites and blogs properly. What we need is not just the access to that data but the scalable ways to collect, analyze and organize it. Python and BeautifulSoup are two marvelous tools to scrape websites and extract data. In web scraping, data can be easily extracted and presented in a format you need. If you are an avid investor that values his/her time and money, you de?nitely need to speed up the web scraping process and make it as optimized as it could be. Getting Started We are going to use both Python and BeautifulSoup as the main scraping language. 1. For Mac users, Python is pre-installed in the OS X. They just have to open Terminal and type in python – version version. This way, they will be able to see Python 2.7 version. python – 2. For the Windows users, we recommend installing Python via its of?cial site. 3. Next, you have to access BeautifulSoup library with the help of pip. This package management tool was made especially for Python. In the terminal, you have to insert the following code: https://rankexperience.com/articles/article2098.html 1/3

2. 23.05.2018 easy_install pip easy_install pip pip install BeautifulSoup4 pip install BeautifulSoup4 Scraping Rules: The main scraping rules you should take care of are: 1. You have to check the site's Rules and Regulations before getting started with its scraping. So be very careful! 2. You should not request the data from the sites too aggressively. Make sure, the tool you use behaves reasonably. Otherwise, you can break the site. 3. One request per second is the right practice. 4. The layout of the blog or site can be altered any time, and you may have to revisit that site and rewrite your own code whenever needed. Inspect the Page Hover your cursor on the Price page to understand what should be done. Read the text related to both HTML and Python, and from the results, you'll see the prices inside the HTML tags. Export to Excel CSV Once you have extracted the data, the next step is to save it of?ine. The Excel Comma Separated Format is the best choice in this regard, and you can easily open it in your Excel sheet. But ?rst, you would have to import the Python CSV modules and the date-time modules to record your data properly. The following code can be inserted in the import section: import csv import csv from datetime import to datetime from datetime import to datetime Advanced Scraping Techniques BeautifulSoup is one of the simplest and comprehensive tools for web scraping. However, if you need to harvest large volumes of data, consider some other alternatives: 1. Scrapy is a powerful and amazing python scraping framework. 2. You can also integrate the code with a public API. The ef?ciency of your data will be important. For example, you can try Facebook Graph API, which helps hide the data and does not show it up on the Facebook pages. https://rankexperience.com/articles/article2098.html 2/3

3. 23.05.2018 3. Besides, you can use the backend programs such as MySQL and store the data in a large amount with great accuracy. 4. DRY stands for "Don't Repeat Yourself" and you can try to automate the regular tasks using this technique. https://rankexperience.com/articles/article2098.html 3/3