Functions such as importlib.import_module() and built-in__import__() can also be used to invoke the import machinery. ¶This method is called when an unrecognized declaration is read by the parser. This parser does not check that end tags match start tags or call the end-tag handler for elements which are closed implicitly by closing an outer element. An HTMLParser instance is fed HTML data and calls handler methods when start tags, end tags, text, comments, and other markup elements are encountered. The user should subclass HTMLParser and override its methods to implement the desired behavior. In last tutorial, we get to know how to run a simple flask app.

You can configure another image editor in which the IDE will open files. PyCharm offers several ways to view images embedded in an HTML file. You can use navigation to source, open an image in an external graphical editor, or preview images on-the-fly.

Strings And Stripped_strings¶

Beautiful Soup is powerful because our Python objects match the nested structure of the HTML document we are scraping. The HTML content of the webpages can be parsed and scraped with Beautiful Soup. In the following section, we will be covering those functions that are useful for scraping webpages. APIs are created to provide access to data in a controlled way as defined by the owners of the data. This article will give you a crash course on web scraping in Python with Beautiful Soup – a popular Python library for parsing HTML and XML.

What are the basic HTML codes?

Basic HTMLTagDescriptionDefines the document typeDefines an HTML documentContains metadata/information for the documentDefines a title for the document6 more rows</p> </div></div> </div> <p>As of Beautiful Soup version 4.10.0, you can call get_text(), .strings, or .stripped_strings on a NavigableString object. It will either return the object itself, or nothing, so the only reason to do this is when you’re iterating over a mixed list. This means it supports most of the methods described <a href="https://www.youtube.com/results?search_query=python import html">python import html</a> inNavigating the tree and Searching the tree. Tags have a lot of attributes and methods, and I’ll cover most of them in Navigating the tree and Searching the tree. For now, the most important features of a tag are its name and attributes. If you can, I recommend you install and use lxml for speed.</p> <h2 id="toc-1">Extract Information Using Class Or Id</h2> <p>Text strings will be ignored, as will tags whose names that don’t match. Notice how tag was broken and attributes for the tag were also extracted. The three handler functions we showed above are the functions which are available for customisation from the class. But these are not the only functions which can be overidden.</p> <div itemScope itemProp="mainEntity" itemType="https://schema.org/Question"> <div itemProp="name"> <h3>Can we connect Python to database?</h3> </div> <div itemScope itemProp="acceptedAnswer" itemType="https://schema.org/Answer"> <div itemProp="text"> <p>Python can be used in database applications. One of the most popular databases is MySQL.</p> </div></div> </div> <p>Typically an HTML file begins with a doctype declaration. You saw this when you wrote an HTML “Hello World” program in an earlier lesson. To make reading our code easier, we will omit the doctype in this example. Recall a multi-line string is created by enclosing the text in three quotation marks . There are also various tools for obtaining the XPath of elements such as FireBug for Firefox or the Chrome Inspector. If you’re using Chrome, you can right click an element, choose ‘Inspect element’, highlight the code, right click again, and choose ‘Copy XPath’.</p> <h2 id="toc-2">Python Modules</h2> <p>We ended up scraping tons of data from the web using this simple module in the process of writing this tutorial. Subclassing lets us override the default functionality of a method and add some better functions instead. But if we need to add functionality, what’s the use of the HTMLParser? This module saves us the time of creating the functionality of identifying tags ourselves.</p> <ul> <li>Instead, it gets the module object by looking the module name up in sys.modules.</li> <li>In order to support imports of modules and initialized packages and also to contribute portions to namespace packages, path entry finders must implement the find_spec() method.</li> <li>¶When being redirected we may want to change the method of the request based on certain specs or browser behavior.</li> <li>One thing to keep in mind is that changes to a web page’s HTML might break your code, so make sure to keep everything up to date if you’re building applications on top of this.</li> <li>Create a branch of the Beautiful Soup repository, add your translation, and propose a merge with the main branch, the same as you would do with a proposed change to the source code.</li> <li>Finally in the above you’ll see an empty paragraph tag – tags with no contents get no closing tag.</li> </ul> <p>There have also been reports on Windows machines of the wrong version being installed. Dash is the best way to build analytical apps in Python using Plotly figures. To run the app below, run pip install dash, click „Download“ to get the code and run python app.py.</p> <h2 id="toc-3">What Is Requests</h2> <p>Before moving on, you will need to make sure you have an up to date version of Python 3 and pip installed. Make sure you create and <a href="https://www.google.com/search?q=python import html">python import html</a> activate a virtual environmentbefore installing any dependencies. This is what most people would need the HTMLParser module for.</p> <p>Use of loader.module_repr()has been deprecated and the module spec is now used by the import machinery to generate a module repr. The module must exist in sys.modules before the loader executes the module code, to prevent unbounded recursion or multiple loading. To begin the search, Python needs the fully qualifiedname of the module being imported. This name may come from <a href="https://cosmeticasimple.com/how-to-determine-your-app-marketing-budget/">Hire a PHP Developer</a> various arguments to the import statement, or from the parameters to theimportlib.import_module() or __import__() functions. For the purposes of this documentation, we’ll use this convenient analogy of directories and files. Like file system directories, packages are organized hierarchically, and packages may themselves contain subpackages, as well as regular modules.</p> <h2 id="toc-4">Example Html Parser Application¶</h2> <p>The import path is a list of locations that may name file system paths or zip files. It can also be extended to search for any locatable resource, such as those identified by URLs. Once we have the raw data we need available to us, we then use a parsing library to extract information from this data using <a href="https://www.newcapitalofegypt.com/2021/01/21/pwc-global-blockchain-survey/">pros and cons of using a staffing agency</a> parsing methods. As the raw data we have is XML format, we can use the lxml library to assist in unpacking it into XML which is easier to work with. When supported by the zipimportmodule in the standard library, the default path entry finders also handle loading all of these file types from zipfiles.</p> <p>“No module named bs4”, your problem is that you’re trying to run Beautiful Soup 4 code, but you only have Beautiful Soup 3 installed. “No module named BeautifulSoup”, your problem is that <a href="https://recipes.galitein.com/abnehmen/forex-trading/balancing-hipaa-cloud-compliance/">Agile Methodologies</a> you’re trying to run Beautiful Soup 3 code, but you only have Beautiful Soup 4 installed. This makes it possible to publish the documentation in a variety of formats, not just HTML.</p> <p>It is stored in a text format and contains tags that define the layout and content of the webpage. HTML files are widely used online and displayed in web browsers. For deeply nested HTML documents, navigation could quickly become tedious. Luckily, Beautiful Soup comes with a search function so we don’t have to navigate to retrieve HTML elements.</p> <p><img class='aligncenter' style='display: block;margin-left:auto;margin-right:auto;' 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" width="505px" alt="python import html"/></p> <p>If you right-click on the element you’re interested in, you can inspect the HTML behind that element to figure out how you can programmatically access the data you want. You can also provide different arguments to find_all, such as regular expressions or tag attributes <a href="https://www.bing.com/search?q=python import html">python import html</a> to filter your search as specifically as you want. HTMLParser only identifies the tags or data for us but does not output any data when something is identified. We need to add functionality to the methods before they can output the information they find.</p> <h2 id="toc-6">Other Technical Seo Guides With Python</h2> <p>When fed with HTML data, the tag reads through it one tag at a time, going from start tags to the tags within, then the end tags and so on. Urllib2 can take a Request object as an argument to add headers to the request and more, <a href="http://www.traventure.forumindonesiamuda.org/2020/11/android-vs-ios-development/">social network development</a> while urllib can only accept a string URL. To analyze the HTML content and obtain the necessary data, the simplest way is to use the BeautifulSoup library. This is an amazing Python package for parsing HTML and XML documents.</p> <p><img class='aligncenter' style='display: block;margin-left:auto;margin-right:auto;' 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" width="504px" alt="python import html"/></p> <p>The last line in the code is where we feed data to the parser. I fed basic HTML code directly, but you can do the same by using the urllib module to directly import a website into python too. Let’s define basic print functionalities to the methods in the HTMLParser module. In the below example, all I’m doing is adding a print method whenever the method is called.</p> <p>Before writing more code to parse the content that we want, let’s first take a look at the HTML that’s rendered by the browser. Every web page is different, and sometimes getting the right data out of them requires a bit of creativity, pattern recognition, and experimentation. With this soup object, you can navigate and search through the HTML for data that you want. For example, if you run soup.title after the previous code in a Python shell you’ll get the title of the web page. If you run print(soup.get_text()), you will see all of the text on the page. You’ll need to install the Requestslibrary for making HTTP requests to get data from the web page, and Beautiful Soupfor parsing through the HTML.</p> </div><!-- .entry-content --> <footer class="entry-meta"> </footer><!-- .entry-meta --> </article><!-- #post --> </div> </div> </div> </section> <footer id="main-footer"> <div class="container"> <div class="row"> <div class="col-md-3 col-xs-12"> <div class="footer-logo"> <img src="https://www.kalap.sk/wp-content/themes/kalap/images/logo_white.png" class="img-fluid" /> </div> </div> <div class="col-md-9 col-xs-12"> <div class="row"> <div class="col-md-4 col-xs-12 m-break"> KALAP s.r.o.<br /> Vladina 695/46<br /> 027 44 Tvrdošín<br /> </div> <div class="col-md-4 col-xs-12 m-break"> <strong> IČO:</strong> 36 420 387<br /> <strong> IČDPH:</strong> SK2021857398<br /><br /> <strong> Email:</strong> kalap@kalap.sk<br /> <strong> T-mobile:</strong> +421 902 550 640<br /> <strong> Orange:</strong> +421 905 550 640<br /> <strong> O2:</strong> +421 948 550 640<br /> </div> <div class="col-md-4 col-xs-12 m-break break-border"> <div id="nav" class="menu"><ul> <li class="page_item page-item-13"><a href="https://www.kalap.sk/gdpr/">GDPR</a></li> <li class="page_item page-item-9 page_item_has_children"><a href="https://www.kalap.sk/">Karosárske a lakýrnické práce</a></li> <li class="page_item page-item-11"><a href="https://www.kalap.sk/kontakt/">Kontakt</a></li> </ul></div> </div> </div> </div> </div> </div> </footer> </div> <script type='text/javascript' src='https://www.kalap.sk/wp-includes/js/wp-embed.min.js?ver=5.3.9'></script> </body> </html>