• December 21, 2024

Xml Scraping Python

XML Scraping done right! – Towards Data Science

Step by step approach to scrape any ‘XML’ file using PythonPhoto by Franki Chamaki on UnsplashData is the new oil — but it’s definitely not cheap. We have data flowing in from all directions; web, apps, social media, etc and it is imperative that data scientists are able to mine some of it. In the following blog, we will learn how to quickly mine/scrape data from a website (for fun) using a Python library ‘BeautifulSoup’Plan of actionIntroduce the Use-CaseWhat is BeautifulSoup? BS4 in action — understand & extract the dataLast commentsAnyone who has worked in customer experience or hospitality industry understands the importance of customer satisfaction. NPS or Net Promoter Score is considered to be a benchmark for customer experience. Although NPS is a specially designed survey, there are other methods to understand customer sentiment. One of them being — Customer feedback and Rating on Appstore (of course only if your app is available there) here what is we will do —→Take a random app (eg: Facebook)→ Go to iTune reviews→ Extract the rating, comments, date, etc that different user have given→Export them in a clean ‘csv/xlsx’ autiful Soup(aka BS4) is a Python package for parsing HTML and XML documents. It creates a parse tree for parsed pages that can be used to extract data from HTML, which is useful for web scraping. It is available for Python 2. 7 and Python 3XML documents are formed as element trees. An XML tree starts at a root element and branches from the root to child elements. The terms parent, child, and sibling are used to describe the relationships between the above picture we can see that is the parent which is many children. One of the children is which further has many children. In a way — is the grand daddy, is the son and others following are the do we need to extract? For now, let’s suppose that we want to extract the following from each review:Date of reviewTitle of reviewContentRatingName of ReviewerAnd we want to do it for 10 CodeThe code is pretty straightforward→ First use request to import the data from URL→ Convert it into BS4 object using BeautifulSoup→Extra: Can find all the text in data using ndall()→Find the child/tag entry and save it as an object. (It is the first review and contains all the review related info)→ Search its children updated title content im:rating name to extract all the info that is needed and save it in a list→ Find the sibling of child/tag entry by using find_next_sibling() (This will lead you to the next review)→ Continue the loop until no more reviews can be found. Keep appending the data in a dataframe. → Extra: In the above code, I have added another loop to extract all the above info from the first 10 review ’s all. Pretty neat, right! ResultWe should get a dataframe that you looks something like this:Voila — You have successfully extracted the info from the iTunes. Now you can develop your beautiful NLP models over them and get to know what your customers are thinking about go through my other Data Science/Machine Learning blogs please visit:The end for now. Have any ideas to improve this or want me to try any new ideas? Please give your suggestions in the comments. Adios.
XML parsing in Python - GeeksforGeeks

XML parsing in Python – GeeksforGeeks

This article focuses on how one can parse a given XML file and extract some useful data out of it in a structured XML stands for eXtensible Markup Language. It was designed to store and transport data. It was designed to be both human- and ’s why, the design goals of XML emphasize simplicity, generality, and usability across the XML file to be parsed in this tutorial is actually a RSS RSS(Rich Site Summary, often called Really Simple Syndication) uses a family of standard web feed formats to publish frequently updated informationlike blog entries, news headlines, audio, video. RSS is XML formatted plain RSS format itself is relatively easy to read both by automated processes and by humans RSS processed in this tutorial is the RSS feed of top news stories from a popular news website. You can check it out here. Our goal is to process this RSS feed (or XML file) and save it in some other format for future Module used: This article will focus on using inbuilt xml module in python for parsing XML and the main focus will be on the ElementTree XML API of this plementation:import csvimport requestsimport as ETdef loadRSS(): resp = (url) with open(”, ‘wb’) as f: (ntent)def parseXML(xmlfile): tree = (xmlfile) root = troot() newsitems = [] for item in ndall(‘. /channel/item’): news = {} for child in item: news[‘media’] = [‘url’] else: news[] = (‘utf8’) (news) return newsitemsdef savetoCSV(newsitems, filename): fields = [‘guid’, ‘title’, ‘pubDate’, ‘description’, ‘link’, ‘media’] with open(filename, ‘w’) as csvfile: writer = csv. DictWriter(csvfile, fieldnames = fields) writer. writeheader() writer. writerows(newsitems)def main(): loadRSS() newsitems = parseXML(”) savetoCSV(newsitems, ”)if __name__ == “__main__”: main()Above code will:Load RSS feed from specified URL and save it as an XML the XML file to save news as a list of dictionaries where each dictionary is a single news the news items into a CSV us try to understand the code in pieces:Loading and saving RSS feeddef loadRSS():
# url of rss feed
url = ”
# creating HTTP response object from given url
resp = (url)
# saving the xml file
with open(”, ‘wb’) as f:
(ntent)Here, we first created a HTTP response object by sending an HTTP request to the URL of the RSS feed. The content of response now contains the XML file data which we save as in our local more insight on how requests module works, follow this article:GET and POST requests using PythonParsing XMLWe have created parseXML() function to parse XML file. We know that XML is an inherently hierarchical data format, and the most natural way to represent it is with a tree. Look at the image below for example:Here, we are using (call it ET, in short) module. Element Tree has two classes for this purpose – ElementTree represents the whole XMLdocument as a tree, and Element represents a single node in this tree. Interactions with the whole document (reading and writing to/from files) are usually done on the ElementTree level. Interactions with a single XML element and its sub-elements are done on the Element, so let’s go through the parseXML() function now:tree = (xmlfile)Here, we create an ElementTree object by parsing the passed = troot()getroot() function return the root of tree as an Element item in ndall(‘. /channel/item’):Now, once you have taken a look at the structure of your XML file, you will notice that we are interested only in item element.. /channel/item is actually XPath syntax (XPath is a language for addressing parts of an XML document). Here, we want to find all item grand-children of channel children of the root(denoted by ‘. ’) can read more about supported XPath syntax item in ndall(‘. /channel/item’):
# empty news dictionary
news = {}
# iterate child elements of item
for child in item:
# special checking for namespace object content:media
if == ‘{content’:
news[‘media’] = [‘url’]
else:
news[] = (‘utf8’)
# append news dictionary to news items list
(news)Now, we know that we are iterating through item elements where each item element contains one news. So, we create an empty news dictionary in which we will store all data available about news item. To iterate though each child element of an element, we simply iterate through it, like this:for child in item:Now, notice a sample item element here:We will have to handle namespace tags separately as they get expanded to their original value, when parsed. So, we do something like this:if == ‘{content’:
news[‘media’] = [‘url’] is a dictionary of all the attributes related to an element. Here, we are interested in url attribute of media:content namespace, for all other children, we simply do:news[] = (‘utf8’) contains the name of child element. stores all the text inside that child element. So, finally, a sample item element is converted to a dictionary and looks like this:{‘description’: ‘Ignis has a tough competition already, from Hyun….,
‘guid’: ‘….,
‘link’: ‘….,
‘media’: ‘…,
‘pubDate’: ‘Thu, 12 Jan 2017 12:33:04 GMT ‘,
‘title’: ‘Maruti Ignis launches on Jan 13: Five cars that threa….. }Then, we simply append this dict element to the list nally, this list is data to a CSV fileNow, we simply save the list of news items to a CSV file so that it could be used or modified easily in future using savetoCSV() function. To know more about writing dictionary elements to a CSV file, go through this article:Working with CSV files in PythonSo now, here is how our formatted data looks like now:As you can see, the hierarchical XML file data has been converted to a simple CSV file so that all news stories are stored in form of a table. This makes it easier to extend the database, one can use the JSON-like data directly in their applications! This is the best alternative for extracting data from websites which do not provide a public API but provide some RSS the code and files used in above article can be found next? You can have a look at more rss feeds of the news website used in above example. You can try to create an extended version of above example by parsing other rss feeds you a cricket fan? Then this rss feed must be of your interest! You can parse this XML file to scrape information about the live cricket matches and use to make a desktop notifier! Quiz of HTML and XMLThis article is contributed by Nikhil Kumar. If you like GeeksforGeeks and would like to contribute, you can also write an article and mail your article to See your article appearing on the GeeksforGeeks main page and help other write comments if you find anything incorrect, or you want to share more information about the topic discussed above
Python XML Parser Tutorial: Read xml file example(Minidom, ElementTree)

Python XML Parser Tutorial: Read xml file example(Minidom, ElementTree)

What is XML?
XML stands for eXtensible Markup Language. It was designed to store and transport small to medium amounts of data and is widely used for sharing structured information.
Python enables you to parse and modify XML document. In order to parse XML document you need to have the entire XML document in memory. In this tutorial, we will see how we can use XML minidom class in Python to load and parse XML file.
In this tutorial, we will learn-
How to Parse XML using minidom
How to Create XML Node
How to Parse XML using ElementTree
We have created a sample XML file that we are going to parse.
Step 1) Inside file, we can see first name, last name, home and the area of expertise (SQL, Python, Testing and Business)
Step 2) Once we have parsed the document, we will print out the “node name” of the root of the document and the “firstchild tagname”. Tagname and nodename are the standard properties of the XML file.
Import the module and declare file that has to be parsed ()
This file carries some basic information about employee like first name, last name, home, expertise, etc.
We use the parse function on the XML minidom to load and parse the XML file
We have variable doc and doc gets the result of the parse function
We want to print the nodename and child tagname from the file, so we declare it in print function
Run the code- It prints out the nodename (#document) from the XML file and the first child tagname (employee) from the XML file
Note:
Nodename and child tagname are the standard names or properties of an XML dom. In case if you are not familiar with these type of naming conventions.
Step 3) We can also call the list of XML tags from the XML document and printed out. Here we printed out the set of skills like SQL, Python, Testing and Business.
Declare the variable expertise, from which we going to extract all the expertise name employee is having
Use the dom standard function called “getElementsByTagName”
This will get all the elements named skill
Declare loop over each one of the skill tags
Run the code- It will give list of four skills
We can create a new attribute by using “createElement” function and then append this new attribute or tag to the existing XML tags. We added a new tag “BigData” in our XML file.
You have to code to add the new attribute (BigData) to the existing XML tag
Then you have to print out the XML tag with new attributes appended with existing XML tag
To add a new XML and add it to the document, we use code “ elements”
This code will create a new skill tag for our new attribute “Big-data”
Add this skill tag into the document first child (employee)
Run the code- the new tag “big data” will appear with the other list of expertise
XML Parser Example
Python 2 Example
import
def main():
# use the parse() function to load and parse an XML file
doc = (“”);
# print out the document node and the name of the first child tag
print deName
print rstChild. tagName
# get a list of XML tags from the document and print each one
expertise = tElementsByTagName(“expertise”)
print “%d expertise:”%
for skill in expertise:
print tAttribute(“name”)
# create a new XML tag and add it into the document
newexpertise = eateElement(“expertise”)
tAttribute(“name”, “BigData”)
endChild(newexpertise)
print ” ”
if name == “__main__”:
main();
Python 3 Example
print (deName)
print (rstChild. tagName)
print (“%d expertise:”%)
print (tAttribute(“name”))
print (” “)
if __name__ == “__main__”:
ElementTree is an API for manipulating XML. ElementTree is the easy way to process XML files.
We are using the following XML document as the sample data:


SQL
Python


Reading XML using ElementTree:
we must first import the module.
import as ET
Now let’s fetch the root element:
root = troot()
Following is the complete code for reading above xml data
tree = (”)
# all items data
print(‘Expertise Data:’)
for elem in root:
for subelem in elem:
print()
output:
Expertise Data:
SQL
Python
Summary:
Python enables you to parse the entire XML document at one go and not just one line at a time. In order to parse XML document you need to have the entire document in memory.
To parse XML document
Import
Use the function “parse” to parse the document ( (file name);
Call the list of XML tags from the XML document using code (tElementsByTagName( “name of xml tags”)
To create and add new attribute in XML document
Use function “createElement”

Frequently Asked Questions about xml scraping python

How do I scrape an XML file in Python?

In order to parse XML document you need to have the entire document in memory.To parse XML document.Import xml.dom.minidom.Use the function “parse” to parse the document ( doc=xml.dom.minidom.parse (file name);Call the list of XML tags from the XML document using code (=doc.getElementsByTagName( “name of xml tags”)More items…•Sep 13, 2021

What is XML scraping?

XML separates data from HTML and simplifies data sharing and data transport since it stores data in plain text format and provides a software- and hardware-independent way of storing data. …Sep 4, 2013

Can you use BeautifulSoup for XML?

This type of tree structure is applicable to XML files as well. Therefore, the BeautifulSoup class can also be used to parse XML files directly.

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