Easyinstall BeautifulSoup4 # for older v3: # easyinstall BeautifulSoup easyinstall will take care of downloading, unpacking, building, and installing the package. The advantage to using easyinstall is that it knows how to search for many different Python packages, because it queries the PyPI registry. Beautiful Soup 4 works on both Python 2 (2.7+) and Python 3. Support for Python 2 will be discontinued on or after December 31, 2020—one year after the Python 2 sunsetting date. Beautiful Soup 3. Beautiful Soup 3 was the official release line of Beautiful Soup from May 2006 to March 2012. Beautiful Soup is a Python library that uses your pre-installed html/xml parser and converts the web page/html/xml into a tree consisting of tags, elements, attributes and values. To be more exact, the tree consists of four types of objects, Tag, NavigableString, BeautifulSoup. Download the get-pip.py from https. By default, Beautiful Soup supports the HTML parser included in Python’s standard library, however it also supports many external third party python parsers like lxml parser or html5lib parser. To install lxml or html5lib parser, use the command −.
Beautiful Soup is a Python library for pulling data out of HTML and XML files. It works with your favorite parser to provide idiomatic ways of navigating, searching, and modifying the parse tree. It commonly saves programmers hours or days of work. Latest Version of Beautifulsoup is v4.8.2 as of now.
PrerequisitesHow to install Beautifulsoup
To install Beautifulsoup on Windows, Linux or any operating system, one would need pip package. To check how to install pip on your operating system, checkoout – PIP Installation – Windows || Linux.
Now, run a simple command,
Beautiful Soup is a library for pulling data out of HTML and XML files. It provides ways of navigating, searching, and modifying parse trees.
Wait and relax, Beautifulsoup would be installed shortly.
Install Beautifulsoup4 using Source code![]()
One can install beautifulsoup, using source code directly, install beautifulsoup tarball from here – download the Beautiful Soup 4 source tarball
after downloading cd into the directory and run, Verifying Installation
To check whether installation is complete or not, let’s try implementing it using python
Recommended Posts:
If you like GeeksforGeeks and would like to contribute, you can also write an article using contribute.geeksforgeeks.org or mail your article to [email protected]. See your article appearing on the GeeksforGeeks main page and help other Geeks.
Please Improve this article if you find anything incorrect by clicking on the 'Improve Article' button below.
by Justin Yek
There is more information on the Internet than any human can absorb in a lifetime. What you need is not access to that information, but a scalable way to collect, organize, and analyze it.
You need web scraping.
Web scraping automatically extracts data and presents it in a format you can easily make sense of. In this tutorial, we’ll focus on its applications in the financial market, but web scraping can be used in a wide variety of situations.
If you’re an avid investor, getting closing prices every day can be a pain, especially when the information you need is found across several webpages. We’ll make data extraction easier by building a web scraper to retrieve stock indices automatically from the Internet.
Getting Started
We are going to use Python as our scraping language, together with a simple and powerful library, BeautifulSoup.
Next we need to get the BeautifulSoup library using
pip , a package management tool for Python.
In the terminal, type:
Note: If you fail to execute the above command line, try adding
sudo in front of each line.
The Basics
Before we start jumping into the code, let’s understand the basics of HTML and some rules of scraping.
HTML tags
If you already understand HTML tags, feel free to skip this part.
This is the basic syntax of an HTML webpage. Every
<tag> serves a block inside the webpage:1. <!DOCTYPE html> : HTML documents must start with a type declaration.2. The HTML document is contained between <html> and </html> .3. The meta and script declaration of the HTML document is between <head> and </head> .4. The visible part of the HTML document is between <body> and </body> tags.5. Title headings are defined with the <h1> through <h6> tags.6. Paragraphs are defined with the <p> tag.
Other useful tags include
<a> for hyperlinks, <table> for tables, <tr> for table rows, and <td> for table columns.
Also, HTML tags sometimes come with
id or class attributes. The id attribute specifies a unique id for an HTML tag and the value must be unique within the HTML document. The class attribute is used to define equal styles for HTML tags with the same class. We can make use of these ids and classes to help us locate the data we want.
For more information on HTML tags, id and class, please refer to W3Schools Tutorials.
Scraping Rules
Inspecting the Page
Let’s take one page from the Bloomberg Quote website as an example.
As someone following the stock market, we would like to get the index name (S&P 500) and its price from this page. First, right-click and open your browser’s inspector to inspect the webpage.
Try hovering your cursor on the price and you should be able to see a blue box surrounding it. If you click it, the related HTML will be selected in the browser console.
From the result, we can see that the price is inside a few levels of HTML tags, which is
<div> → <div> → <div> .
Similarly, if you hover and click the name “S&P 500 Index”, it is inside
<div> and <h1> .
Now we know the unique location of our data with the help of
class tags.
Jump into the Code
Now that we know where our data is, we can start coding our web scraper. Open your text editor now!
First, we need to import all the libraries that we are going to use.
Next, declare a variable for the url of the page.
Then, make use of the Python urllib2 to get the HTML page of the url declared.
Finally, parse the page into BeautifulSoup format so we can use BeautifulSoup to work on it.
Now we have a variable,
soup , containing the HTML of the page. Here’s where we can start coding the part that extracts the data.
Remember the unique layers of our data? BeautifulSoup can help us get into these layers and extract the content with
find() . In this case, since the HTML class name is unique on this page, we can simply query <div> .
After we have the tag, we can get the data by getting its
text .
Similarly, we can get the price too.
When you run the program, you should be able to see that it prints out the current price of the S&P 500 Index.
Export to Excel CSV
Now that we have the data, it is time to save it. The Excel Comma Separated Format is a nice choice. It can be opened in Excel so you can see the data and process it easily.
But first, we have to import the Python csv module and the datetime module to get the record date. Insert these lines to your code in the import section.
At the bottom of your code, add the code for writing data to a csv file.
Now if you run your program, you should able to export an
index.csv file, which you can then open with Excel, where you should see a line of data. Realplayer cloud free download for mac.
Gui toolkit mono for mac download. So if you run this program everyday, you will be able to easily get the S&P 500 Index price without rummaging through the website!
![]() Going Further (Advanced uses)
Multiple Indices
So scraping one index is not enough for you, right? We can try to extract multiple indices at the same time.
First, modify the
quote_page into an array of URLs.
How To Download Beautiful Soup On Mac Os
Then we change the data extraction code into a
for loop, which will process the URLs one by one and store all the data into a variable data in tuples. Emily is away free download mac.
Also, modify the saving section to save data row by row.
How To Download Beautiful Soup On Mac Catalina
Rerun the program and you should be able to extract two indices at the same time!
Advanced Scraping Techniques
BeautifulSoup is simple and great for small-scale web scraping. But if you are interested in scraping data at a larger scale, you should consider using these other alternatives:
Adopt the DRY MethodBeautifulsoup Python 3
DRY stands for “Don’t Repeat Yourself”, try to automate your everyday tasks like this person. Some other fun projects to consider might be keeping track of your Facebook friends’ active time (with their consent of course), or grabbing a list of topics in a forum and trying out natural language processing (which is a hot topic for Artificial Intelligence right now)!
If you have any questions, please feel free to leave a comment below.
References
http://www.gregreda.com/2013/03/03/web-scraping-101-with-python/ http://www.analyticsvidhya.com/blog/2015/10/beginner-guide-web-scraping-beautiful-soup-python/
This article was originally published on Altitude Labs’ blog and was written by our software engineer, Leonard Mok. Altitude Labs is a software agency that specializes in personalized, mobile-first React apps.
Comments are closed.
|
AuthorWrite something about yourself. No need to be fancy, just an overview. Archives
December 2020
Categories |