Accessing tabular data via hyperlinks with BeautifulSoup - python

There's something I still don't understand about using BeautifulSoup. I can use this to parse the raw HTML of a webpage, here "example_website.com":
from bs4 import BeautifulSoup # load BeautifulSoup class
import requests
r = requests.get("http://example_website.com")
data = r.text
soup = BeautifulSoup(data)
# soup.find_all('a') grabs all elements with <a> tag for hyperlinks
Then, to retrieve and print all elements with the 'href' attribute, we can use a for loop:
for link in soup.find_all('a'):
print(link.get('href'))
What I don't understand: I have a website with several webpages, and each webpage lists several hyperlinks to a single webpage with tabular data.
I can use BeautifulSoup to parse the homepage, but how do I use the same Python script to scrape page 2, page 3, and so on? How do you "access" the contents found via the 'href' links?
Is there a way to write a python script to do this? Should I be using a spider?


You can do that with requests+BeautifulSoup for sure. It would be of a blocking nature, since you would process the extracted links one by one and you would not proceed to the next link until you are done with the current. Sample implementation:
from urlparse import urljoin
from bs4 import BeautifulSoup
import requests
with requests.Session() as session:
r = session.get("http://example_website.com")
data = r.text
soup = BeautifulSoup(data)
base_url = "http://example_website.com"
for link in soup.find_all('a'):
url = urljoin(base_url, link.get('href'))
r = session.get(url)
# parse the subpage
Though, it may quickly get complex and slow.
You may need to switch to Scrapy web-scraping framework which makes web-scraping, crawling, following the links easy (check out CrawlSpider with link extractors), fast and in a non-blocking nature (it is based on Twisted).

Related

Extract single URL from webpage by scraping

I have been trying to scrape a website such as the one below. In the footer there are a bunch of links of their social media out of which the LinkedIn URL is the point of focus for me. Is there a way to fish out only that link maybe using regex or any other libraries available in Python.
This is what I have tried so far -
import requests
from bs4 import BeautifulSoup
url = "https://www.southcoast.org/"
req = requests.get(url)
soup = BeautifulSoup(reqs.text,"html.parser")
for link in soup.find_all('a'):
print(link.get('href'))
But I'm fetching all the URLs instead of the one I'm looking for.
Note: I'd appreciate a dynamic code which I can use for other sites as well.
Thanks in advance for you suggestion/help.

One approach could be to use css selectors and look for string linkedin.com/company/ in values of href attributes:
soup.select_one('a[href*="linkedin.com/company/"]')['href']
Example
import requests
from bs4 import BeautifulSoup
url = "https://www.southcoast.org/"
req = requests.get(url)
soup = BeautifulSoup(req.text,"html.parser")
# single (first) link
link = e['href'] if(e := soup.select_one('a[href*="linkedin.com/company/"]')) else None
# multiple links
links = [link['href'] for link in soup.select('a[href*="linkedin.com/company/"]')]

BeautifulSoup can't find tag

I am trying to scrape a web-page to collect a list of Fortune 500 companies. However, when I run this code, BeautifulSoup can't find <div class="rt-tr-group" role="rowgroup"> tags.
import requests
from bs4 import BeautifulSoup
url = r'https://fortune.com/fortune500/2019/search/'
page = requests.get(url)
soup = BeautifulSoup(page.content, 'lxml')
data = soup.find_all('div', {'class': 'rt-tr-group'})
Instead, I just get an empty list. I've tried changing the parser but saw no results.
The tags exist and can be seen
here:

Data is loading on that page using JS, after some time.
Using Selenium, you can wait for page to be loaded completely, or try to get data from Javascript.
P.S. You can check for XHR requests and try to get JSON instead, without parsing. Here is one request

Content of your parsing page loading with JS, and you can get empty page with requests.get.

Web Scraping through links with Beautiful Soup

I'm trying to Scrape a blog "https://blog.feedspot.com/ai_rss_feeds/" and crawl through all the links in it to look for Artificial Intelligence related information in each of the crawled links.
The blog follows a pattern - It has multiple RSS Feeds and each Feed has an attribute called "Site" in the UI. I need to get all the links in the "Site" attribute. Example : aitrends.com, sciecedaily.com/... etc. In the code, the main div has a class called "rss-block", which has another nested class called "data" and each data has several tags and the tags have in them. The value in href gives the links to be crawled upon. We need to look for AI related articles in each of those links found by scraping the above-mentioned structure.
I've tried various variations of the following code but nothing seemed to help much.
import requests
from bs4 import BeautifulSoup
page = requests.get('https://blog.feedspot.com/ai_rss_feeds/')
soup = BeautifulSoup(page.text, 'html.parser')
class_name='data'
dataSoup = soup.find(class_=class_name)
print(dataSoup)
artist_name_list_items = dataSoup.find('a', href=True)
print(artist_name_list_items)
I'm struggling to even get the links in that page, let alone craling through each of these links to scrape articles related to AI in them.
If you could help me finish both the parts of the problem, that'd be a great learning for me. Please refer to the source of https://blog.feedspot.com/ai_rss_feeds/ for the HTML Structure. Thanks in advance!

The first twenty results are stored in the html as you see on page. The others are pulled from a script tag and you can regex them out to create the full list of 67. Then loop that list and issue requests to those for further info. I offer a choice of two different selectors for the initial list population (the second - commented out - uses :contains - available with bs4 4.7.1+)
from bs4 import BeautifulSoup as bs
import requests, re
p = re.compile(r'feed_domain":"(.*?)",')
with requests.Session() as s:
r = s.get('https://blog.feedspot.com/ai_rss_feeds/')
soup = bs(r.content, 'lxml')
results = [i['href'] for i in soup.select('.data [rel="noopener nofollow"]:last-child')]
## or use with bs4 4.7.1 +
#results = [i['href'] for i in soup.select('strong:contains(Site) + a')]
results+= [re.sub(r'\n\s+','',i.replace('\\','')) for i in p.findall(r.text)]
for link in results:
#do something e.g.
r = s.get(link)
soup = bs(r.content, 'lxml')
# extract info from indiv page

To get all the sublinks for each block, you can use soup.find_all:
from bs4 import BeautifulSoup as soup
import requests
d = soup(requests.get('https://blog.feedspot.com/ai_rss_feeds/').text, 'html.parser')
results = [[i['href'] for i in c.find('div', {'class':'data'}).find_all('a')] for c in d.find_all('div', {'class':'rss-block'})]
Output:
[['http://aitrends.com/feed', 'https://www.feedspot.com/?followfeedid=4611684', 'http://aitrends.com/'], ['https://www.sciencedaily.com/rss/computers_math/artificial_intelligence.xml', 'https://www.feedspot.com/?followfeedid=4611682', 'https://www.sciencedaily.com/news/computers_math/artificial_intelligence/'], ['http://machinelearningmastery.com/blog/feed', 'https://www.feedspot.com/?followfeedid=4575009', 'http://machinelearningmastery.com/blog/'], ['http://news.mit.edu/rss/topic/artificial-intelligence2', 'https://www.feedspot.com/?followfeedid=4611685', 'http://news.mit.edu/topic/artificial-intelligence2'], ['https://www.reddit.com/r/artificial/.rss', 'https://www.feedspot.com/?followfeedid=4434110', 'https://www.reddit.com/r/artificial/'], ['https://chatbotsmagazine.com/feed', 'https://www.feedspot.com/?followfeedid=4470814', 'https://chatbotsmagazine.com/'], ['https://chatbotslife.com/feed', 'https://www.feedspot.com/?followfeedid=4504512', 'https://chatbotslife.com/'], ['https://aws.amazon.com/blogs/ai/feed', 'https://www.feedspot.com/?followfeedid=4611538', 'https://aws.amazon.com/blogs/ai/'], ['https://developer.ibm.com/patterns/category/artificial-intelligence/feed', 'https://www.feedspot.com/?followfeedid=4954414', 'https://developer.ibm.com/patterns/category/artificial-intelligence/'], ['https://lexfridman.com/category/ai/feed', 'https://www.feedspot.com/?followfeedid=4968322', 'https://lexfridman.com/ai/'], ['https://medium.com/feed/#Francesco_AI', 'https://www.feedspot.com/?followfeedid=4756982', 'https://medium.com/#Francesco_AI'], ['https://blog.netcoresmartech.com/rss.xml', 'https://www.feedspot.com/?followfeedid=4998378', 'https://blog.netcoresmartech.com/'], ['https://www.aitimejournal.com/feed', 'https://www.feedspot.com/?followfeedid=4979214', 'https://www.aitimejournal.com/'], ['https://blogs.nvidia.com/feed', 'https://www.feedspot.com/?followfeedid=4611576', 'https://blogs.nvidia.com/'], ['http://feeds.feedburner.com/AIInTheNews', 'https://www.feedspot.com/?followfeedid=623918', 'http://aitopics.org/whats-new'], ['https://blogs.technet.microsoft.com/machinelearning/feed', 'https://www.feedspot.com/?followfeedid=4431827', 'https://blogs.technet.microsoft.com/machinelearning/'], ['https://machinelearnings.co/feed', 'https://www.feedspot.com/?followfeedid=4611235', 'https://machinelearnings.co/'], ['https://www.artificial-intelligence.blog/news?format=RSS', 'https://www.feedspot.com/?followfeedid=4611100', 'https://www.artificial-intelligence.blog/news/'], ['https://news.google.com/news?cf=all&hl=en&pz=1&ned=us&q=artificial+intelligence&output=rss', 'https://www.feedspot.com/?followfeedid=4611157', 'https://news.google.com/news/section?q=artificial%20intelligence&tbm=nws&*'], ['https://www.youtube.com/feeds/videos.xml?channel_id=UCEqgmyWChwvt6MFGGlmUQCQ', 'https://www.feedspot.com/?followfeedid=4611505', 'https://www.youtube.com/channel/UCEqgmyWChwvt6MFGGlmUQCQ/videos']]

How to sift through specific items from a webpage using conditional statement

I've made a scraper in python. It is running smoothly. Now I would like to discard or accept specific links from that page as in, links only containing "mobiles" but even after making some conditional statement I can't do so. Hope I'm gonna get any help to rectify my mistakes.
import requests
from bs4 import BeautifulSoup
def SpecificItem():
url = 'https://www.flipkart.com/'
Process = requests.get(url)
soup = BeautifulSoup(Process.text, "lxml")
for link in soup.findAll('div',class_='')[0].findAll('a'):
if "mobiles" not in link:
print(link.get('href'))
SpecificItem()
On the other hand if I do the same thing using lxml library with xpath, It works.
import requests
from lxml import html
def SpecificItem():
url = 'https://www.flipkart.com/'
Process = requests.get(url)
tree = html.fromstring(Process.text)
links = tree.xpath('//div[#class=""]//a/#href')
for link in links:
if "mobiles" not in link:
print(link)
SpecificItem()
So, at this point i think with BeautifulSoup library the code should be somewhat different to get the purpose served.

The root of your problem is your if condition works a bit differently between BeautifulSoup and lxml. Basically, if "mobiles" not in link: with BeautifulSoup is not checking if "mobiles" is in the href field. I didn't look too hard but I'd guess it's comparing it to the link.text field instead. Explicitly using the href field does the trick:
import requests
from bs4 import BeautifulSoup
def SpecificItem():
url = 'https://www.flipkart.com/'
Process = requests.get(url)
soup = BeautifulSoup(Process.text, "lxml")
for link in soup.findAll('div',class_='')[0].findAll('a'):
href = link.get('href')
if "mobiles" not in href:
print(href)
SpecificItem()
That prints out a bunch of links and none of them include "mobiles".

Requests Only Returns Partial Results

I'm trying to scrape the links for the top 10 articles on medium each day - by the looks of it, it seems like all the article links are in the class "postArticle-content," but when I run this code, I only get the top 3. Is there a way to get all 10?
from bs4 import BeautifulSoup
import requests
r = requests.get("https://medium.com/browse/726a53df8c8b")
data = r.text
soup = BeautifulSoup(data)
data = soup.findAll('div', attrs={'class' : 'postArticle-content'})
for div in data:
links = div.findAll('a')
for link in links:
print(link.get('href'))

requests gave you the entire results.
That page contains only the first three. The website's design is to use javascript code, running in the browser, to load additional content and add it to the page.
You need an entire web browser, with a javascript engine, to do what you are trying to do. The requests and beautiful-soup libraries are not a web browser. They are merely an implementation of the HTTP protocol and an HTML parser, respectively.

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