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/"]')]
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']]
I seek help as I am stuck on how to crawl each and every link (pages or sub pages) in a webpage and find the frequency of any word. I used beautiful soup
for scraping but I don't think so I am doing it right. For ex: I need to go to Service now official page > Solutions > View all Solutions. And find the frequency of "Intelligent" in all the links/sub pages under View all Solutions.
Any help would be very much appreciated.
Thank you :)
My Code
import requests
from bs4 import BeautifulSoup
url = "https://www.servicenow.com/solutions-by-category.html"
serviceNow_r = requests.get(url)
sNow_soup = BeautifulSoup(serviceNow_r.text, 'html.parser')
print(sNow_soup.find_all('href',{'class':'cta-list component'}))
for name in sNow_soup.find_all('href',{'class':'cta-list component'}):
print(name.text)
This is what you need to access the href attribute for every link in the page.
import requests
from bs4 import BeautifulSoup
url = "https://www.servicenow.com/solutions-by-category.html"
serviceNow_r = requests.get(url)
sNow_soup = BeautifulSoup(serviceNow_r.text, 'html.parser')
for anchor in sNow_soup.find_all('a', href=True):
print(anchor['href'])
You are searching for an href tag. This is wrong!
You should search for an a tag then get the href attribute. This is the url of the linked page.
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".
Trying out BeautifulSoup for the first time.
I have this link http://www.mediafire.com/download/alv8dq6k35n4m2k/For+You.zip
I want to catch the direct download url from the download button which is
http://download2110.mediafire.com/niz8p9iu6r9g/alv8dq6k35n4m2k/For+You.zip
What I have tried so far.
r = requests.get(url)
soup = BeautifulSoup(r.content)
links = soup.findAll('a')
I think the last function findAll('a')would find all the links from that page, but I could not find the direct download url in my linkslist.
Am I doing something wrong here? If so, how can I grab that link with beautifulsoup. I inspect the element in Chrome Developer Console and I see that the link is there.
You can try this to extract the url from the javascript:
from bs4 import BeautifulSoup
import requests
r = requests.get("http://www.mediafire.com/download/alv8dq6k35n4m2k/For+You.zip")
soup = BeautifulSoup(r.content)
link = soup.find("div",{"class":"download_link"})
import re
url = re.findall("http.*.zip?",link.text)[0]