![]() elem.getchildren() gets a list of the children of elem, while elem.getiterator() allows for iterating over all the descendants of elem.Similarly, elem.getprevious() and elem.getnext() may return a single element, or None. elem.getparent() gets the parent element of elem.elem.xpath(some_path) and elem.cssselect(some_selector) find a list of nodes relative to elem matching the given XPath or CSS selector expression, respectively.It then illustrates some operations on the elements. This code begins by building a tree of Elements from the HTML using (some_html). Title html: b'Resolutions adopted by the United Nations Security Council in 2016 \n' Title text: Resolutions adopted by the United Nations Security Council in 2016 The following illustrates loads the response HTML into a tree of elements, and illustrates the xpath and cssselect methods provided on an ElementTree (and each Element thereof), as well as other tree traversal. We now have the page content, but as a string of textual characters, not as a tree of elements. response.text reads all the content sent back by the web server (and raises an error if the request was unsuccessful), in this case HTML source code.requests.get(URL) tries to request the URL from the web server and returns a Response object which includes various details about the request and its response.import requests has made the requests library available to your Python code.Resolutions adopted by the United Nations Security Council since 1946 If all are correctly installed, it should be possible to then write the following Python code without an error occurring: To use CSS selectors, the cssselect package must also be installed. It is also able to construct new well-formed HTML/XML documents, element by element. It knows how to handle badly-formed HTML (such as an opening tag that is never closed, or a closing tag that is never opened), although it may not handle it identically to a particular web browser. It facilitates extracting the text, attribute values or HTML for a particular element. It facilitates navigating from one element to another. It evaluates XPath and CSS selectors to find matching elements. Lxml is a tool for working with HTML and XML documents, represented as an element tree. It can manage cookies, keeping track of a logged-in session.Īnd it helps handling cases where the web site is down or takes a long time to respond. ![]() It can submit data as if filled out in a form on a web page. It can download a web page’s HTML given its URL. Requests focuses on the task of interacting with web sites. We make use of two tools that are not specifically developed for scraping, but are very useful for that purpose (among others).īoth of these require a Python installation (Python 2.7, or Python 3.4 and higher although our example code will focus on Python 3),Īnd each library (requests and lxml and cssselect) needs to be installed as described in Setup. Writing a scraper in code may make it easier to maintain and extend, or to incorporate quality assurance and monitoring mechanisms. There may also be too much data, or too many pages to visit, to simply run the scraper in a web browser, as some visual scrapers operate. Limitations in using the tools we have seen so far.įor example, some data may be structured in ways that are too out of the ordinary for visual scrapers, perhaps requiring items to be processed only in certain conditions. This is quite a toolset already, and it’s probably sufficient for a number of use cases, but there are These help determine an appropriate selector, and may be able to navigate through a web site collecting data.
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