How To Install Beautiful Soup In Python 3.9 (Windows 10) | beautifulsoup python download 10 Câu trả lời chính xác nhất

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. The latest Version of Beautifulsoup is v4.9.3 as of now.

Prerequisites

How 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, check out – PIP Installation – Windows || Linux.

Now, run a simple command,

pip install beautifulsoup4

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,

Python setup.py install

Verifying Installation

To check whether the installation is complete or not, let’s try implementing it using python

[ Download | Documentation | Hall of Fame | For enterprise | Source | Changelog | Discussion group | Zine ]

You didn’t write that awful page. You’re just trying to get some data out of it. Beautiful Soup is here to help. Since 2004, it’s been saving programmers hours or days of work on quick-turnaround screen scraping projects.

Beautiful Soup is a Python library designed for quick turnaround projects like screen-scraping. Three features make it powerful:

Beautiful Soup provides a few simple methods and Pythonic idioms for navigating, searching, and modifying a parse tree: a toolkit for dissecting a document and extracting what you need. It doesn’t take much code to write an application Beautiful Soup automatically converts incoming documents to Unicode and outgoing documents to UTF-8. You don’t have to think about encodings, unless the document doesn’t specify an encoding and Beautiful Soup can’t detect one. Then you just have to specify the original encoding. Beautiful Soup sits on top of popular Python parsers like lxml and html5lib, allowing you to try out different parsing strategies or trade speed for flexibility.

Beautiful Soup parses anything you give it, and does the tree traversal stuff for you. You can tell it “Find all the links”, or “Find all the links of class externalLink “, or “Find all the links whose urls match “foo.com”, or “Find the table heading that’s got bold text, then give me that text.”

Valuable data that was once locked up in poorly-designed websites is now within your reach. Projects that would have taken hours take only minutes with Beautiful Soup.

Interested? Read more.

Getting and giving support

If you have questions, send them to the discussion group. If you find a bug, file it on Launchpad. If it’s a security vulnerability, report it confidentially through Tidelift.

If you use Beautiful Soup as part of your work, please consider a Tidelift subscription. This will support many of the free software projects your organization depends on, not just Beautiful Soup.

If Beautiful Soup is useful to you on a personal level, you might like to read Tool Safety, a short zine I wrote about what I learned about software development from working on Beautiful Soup. Thanks!

Download Beautiful Soup

The current release is Beautiful Soup 4.11.1 (April 8, 2021). You can install Beautiful Soup 4 with pip install beautifulsoup4 .

In Debian and Ubuntu, Beautiful Soup is available as the python-bs4 package (for Python 2) or the python3-bs4 package (for Python 3). In Fedora it’s available as the python-beautifulsoup4 package.

Beautiful Soup is licensed under the MIT license, so you can also download the tarball, drop the bs4/ directory into almost any Python application (or into your library path) and start using it immediately. (If you want to do this under Python 3, you will need to manually convert the code using 2to3 .)

Beautiful Soup 4 works on Python 3.6 and up. Support for Python 2 was discontinued on January 1, 2021—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. It does not support Python 3 and was discontinued or January 1, 2021—one year after the Python 2 sunsetting date. If you have any active projects using Beautiful Soup 3, you should migrate to Beautiful Soup 4 as part of your Python 3 conversion.

Here’s the Beautiful Soup 3 documentation.

The current and hopefully final release of Beautiful Soup 3 is 3.2.2 (October 5, 2019). It’s the BeautifulSoup package on pip. It’s also available as python-beautifulsoup in Debian and Ubuntu, and as python-BeautifulSoup in Fedora.

Once Beautiful Soup 3 is discontinued, these package names will be available for use by a more recent version of Beautiful Soup.

Beautiful Soup 3, like Beautiful Soup 4, is supported through Tidelift.

Hall of Fame

Over the years, Beautiful Soup has been used in hundreds of different projects. There’s no way I can list them all, but I want to highlight a few high-profile projects. Beautiful Soup isn’t what makes these projects interesting, but it did make their completion easier:

If you’ve used Beautiful Soup in a project you’d like me to know about, please do send email to me or the discussion group.

Development

Development happens at Launchpad. You can get the source code or file bugs.

Beautiful Soup – Installation

Advertisements

As BeautifulSoup is not a standard python library, we need to install it first. We are going to install the BeautifulSoup 4 library (also known as BS4), which is the latest one.

To isolate our working environment so as not to disturb the existing setup, let us first create a virtual environment.

Creating a virtual environment (optional)

A virtual environment allows us to create an isolated working copy of python for a specific project without affecting the outside setup.

Best way to install any python package machine is using pip, however, if pip is not installed already (you can check it using – “pip –version” in your command or shell prompt), you can install by giving below command −

Linux environment

$sudo apt-get install python-pip

Windows environment

To install pip in windows, do the following −

Download the get-pip.py from https://bootstrap.pypa.io/get-pip.py or from the github to your computer.

Open the command prompt and navigate to the folder containing get-pip.py file.

Run the following command −

>python get-pip.py

That’s it, pip is now installed in your windows machine.

You can verify your pip installed by running below command −

>pip –version pip 19.2.3 from c:\users\yadur\appdata\local\programs\python\python37\lib\site-packages\pip (python 3.7)

Installing virtual environment

Run the below command in your command prompt −

>pip install virtualenv

After running, you will see the below screenshot −

Below command will create a virtual environment (“myEnv”) in your current directory −

>virtualenv myEnv

Screenshot

To activate your virtual environment, run the following command −

>myEnv\Scripts\activate

In the above screenshot, you can see we have “myEnv” as prefix which tells us that we are under virtual environment “myEnv”.

To come out of virtual environment, run deactivate.

(myEnv) C:\Users\yadur>deactivate C:\Users\yadur>

As our virtual environment is ready, now let us install beautifulsoup.

Installing BeautifulSoup

As BeautifulSoup is not a standard library, we need to install it. We are going to use the BeautifulSoup 4 package (known as bs4).

Linux Machine

To install bs4 on Debian or Ubuntu linux using system package manager, run the below command −

$sudo apt-get install python-bs4 (for python 2.x) $sudo apt-get install python3-bs4 (for python 3.x)

You can install bs4 using easy_install or pip (in case you find problem in installing using system packager).

$easy_install beautifulsoup4 $pip install beautifulsoup4

(You may need to use easy_install3 or pip3 respectively if you’re using python3)

Windows Machine

To install beautifulsoup4 in windows is very simple, especially if you have pip already installed.

>pip install beautifulsoup4

So now beautifulsoup4 is installed in our machine. Let us talk about some problems encountered after installation.

Problems after installation

On windows machine you might encounter, wrong version being installed error mainly through −

error: ImportError “No module named HTMLParser” , then you must be running python 2 version of the code under Python 3.

error: ImportError “No module named html.parser” error, then you must be running Python 3 version of the code under Python 2.

Best way to get out of above two situations is to re-install the BeautifulSoup again, completely removing existing installation.

If you get the SyntaxError “Invalid syntax” on the line ROOT_TAG_NAME = u’[document]’, then you need to convert the python 2 code to python 3, just by either installing the package −

$ python3 setup.py install

or by manually running python’s 2 to 3 conversion script on the bs4 directory −

$ 2to3-3.2 -w bs4

Installing a Parser

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 −

Linux Machine

$apt-get install python-lxml $apt-get insall python-html5lib

Windows Machine

$pip install lxml $pip install html5lib

Generally, users use lxml for speed and it is recommended to use lxml or html5lib parser if you are using older version of python 2 (before 2.7.3 version) or python 3 (before 3.2.2) as python’s built-in HTML parser is not very good in handling older version.

Running Beautiful Soup

It is time to test our Beautiful Soup package in one of the html pages (taking web page – https://www.tutorialspoint.com/index.htm, you can choose any-other web page you want) and extract some information from it.

In the below code, we are trying to extract the title from the webpage −

from bs4 import BeautifulSoup import requests url = “https://www.tutorialspoint.com/index.htm” req = requests.get(url) soup = BeautifulSoup(req.text, “html.parser”) print(soup.title)

Output

One common task is to extract all the URLs within a webpage. For that we just need to add the below line of code −

for link in soup.find_all(‘a’): print(link.get(‘href’))

Output

https://www.tutorialspoint.com/index.htm https://www.tutorialspoint.com/about/about_careers.htm https://www.tutorialspoint.com/questions/index.php https://www.tutorialspoint.com/online_dev_tools.htm https://www.tutorialspoint.com/codingground.htm https://www.tutorialspoint.com/current_affairs.htm https://www.tutorialspoint.com/upsc_ias_exams.htm https://www.tutorialspoint.com/tutor_connect/index.php https://www.tutorialspoint.com/whiteboard.htm https://www.tutorialspoint.com/netmeeting.php https://www.tutorialspoint.com/index.htm https://www.tutorialspoint.com/tutorialslibrary.htm https://www.tutorialspoint.com/videotutorials/index.php https://store.tutorialspoint.com https://www.tutorialspoint.com/gate_exams_tutorials.htm https://www.tutorialspoint.com/html_online_training/index.asp https://www.tutorialspoint.com/css_online_training/index.asp https://www.tutorialspoint.com/3d_animation_online_training/index.asp https://www.tutorialspoint.com/swift_4_online_training/index.asp https://www.tutorialspoint.com/blockchain_online_training/index.asp https://www.tutorialspoint.com/reactjs_online_training/index.asp https://www.tutorix.com https://www.tutorialspoint.com/videotutorials/top-courses.php https://www.tutorialspoint.com/the_full_stack_web_development/index.asp …. …. https://www.tutorialspoint.com/online_dev_tools.htm https://www.tutorialspoint.com/free_web_graphics.htm https://www.tutorialspoint.com/online_file_conversion.htm https://www.tutorialspoint.com/netmeeting.php https://www.tutorialspoint.com/free_online_whiteboard.htm http://www.tutorialspoint.com https://www.facebook.com/tutorialspointindia https://plus.google.com/u/0/+tutorialspoint http://www.twitter.com/tutorialspoint http://www.linkedin.com/company/tutorialspoint https://www.youtube.com/channel/UCVLbzhxVTiTLiVKeGV7WEBg https://www.tutorialspoint.com/index.htm /about/about_privacy.htm#cookies /about/faq.htm /about/about_helping.htm /about/contact_us.htm

Similarly, we can extract useful information using beautifulsoup4.

Now let us understand more about “soup” in above example.

Relevant Projects

In this PyTorch Project, you will build an image classification model in PyTorch using the ResNet pre-trained model.

In this loan prediction project you will build predictive models in Python using H2O.ai to predict if an applicant is able to repay the loan or not.

In this Machine Learning Regression project, you will build and evaluate various regression models in Python for house price prediction.

In this Azure MLOps Project, you will learn to perform docker-based deployment of RNN and CNN Models for Time Series Forecasting on Azure Cloud.

Learn the basic aspects of chatbot development and open source conversational AI RASA to create a simple AI powered chatbot on your own.

Implement a machine learning approach using various classification techniques in Python to examine the digitalisation process of bank customers.

Classification ML Project for Beginners – A Hands-On Approach to Implementing Different Types of Classification Algorithms in Machine Learning for Predictive Modelling

In this Deep Learning Project, you will learn how to optimally tune the hyperparameters (learning rate, epochs, dropout, early stopping) of a neural network model in PyTorch to improve model performance.

In this machine learning and IoT project, we are going to test out the experimental data using various predictive models and train the models and break the energy usage.

Use the Adult Income dataset to predict whether income exceeds 50K yr based oncensus data.