I am trying to scrape a given number results from google search, but I so far I came across two problems: one is that I don't know how to join the URLs and the titles inside the same loop, so they can be shown together in the format:
(Title)
(Website URL)
(---------)
(Title)
(Website URL)
(---------)
I somehow managed to achieve this format, but the loop is going on several times, instead of just showing the top 10 results. I believe it's something to do with how I structured the loops to work together, but I don't know how to avoid this.
The other problem is that I want to obtain both main URL and title of each website within search results, but while I managed to get the right titles, I seem to be getting many links coming from the same website, instead of only the main URL. For instance, if I search for "data science", the second or third title shown is from Coursera, while the link is from wikipedia. I only want the main URL so the title matches the website URL, how do I get it?
Any input will be greatly appreciated
import requests
from bs4 import BeautifulSoup
import re
query = "data science"
search = query.replace(' ', '+')
results = 10
url = (f"https://www.google.com/search?q={search}&num={results}")
requests_results = requests.get(url)
soup_link = BeautifulSoup(requests_results.content, "html.parser")
soup_title = BeautifulSoup(requests_results.text,"html.parser")
links = soup_link.find_all("a")
heading_object=soup_title.find_all( 'h3' )
for link in links:
for info in heading_object:
get_title = info.getText()
link_href = link.get('href')
if "url?q=" in link_href and not "webcache" in link_href:
print(get_title)
print(link.get('href').split("?q=")[1].split("&sa=U")[0])
print("------")
The length of your links doesn't seem to match your heading_object list. I think it's best if you filter it further than just "a".
Editing your solution, you can loop through links like this:
import requests
from bs4 import BeautifulSoup
import re
query = "data science"
search = query.replace(' ', '+')
results = 10
url = (f"https://www.google.com/search?q={search}&num={results}")
requests_results = requests.get(url)
soup_link = BeautifulSoup(requests_results.content, "html.parser")
links = soup_link.find_all("a")
for link in links:
link_href = link.get('href')
if "url?q=" in link_href and not "webcache" in link_href:
title = link.find_all('h3')
if len(title) > 0:
print(link.get('href').split("?q=")[1].split("&sa=U")[0])
print(title[0].getText())
print("------")
Instead of keeping 2 lists for headers and links, we can get the header directly from the link. We do that by by doing another find_all('h3') inside the link object.
Since there are links that match url?q= format but are not part of the actual results you want to display, like the expanding accordion for related searches etc, we need to filter those out too. We can do that by checking if they have an "h3" header that's why we have len(title) > 0.
Try to use requests params as a dict, it's more readable e.g:
params = {
"q": "fus ro dah",
"hl": "en",
"gl": "us",
"num": "100"
}
requests.get('https://www.google.com/search', params=params)
Make sure you're using request headers and passing user-agent to act as a real user-visit. Otherwise Google will block your request eventually because default requests user-agent is python-requests. Check what's your user-agent.
headers = {
"User-Agent":
"Mozilla/5.0 (Windows NT 10.0; Win64; x64) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/72.0.3538.102 Safari/537.36 Edge/18.19582"
}
You don't need to create several soups (BeautifulSoup() object), create only one instead and call it whenever it's needed. CSS selectors reference.
soup = BeautifulSoup(html.text, 'YOUR PARSER OF CHOISE') # try to use 'lxml', it's one of the fastest
# call it
soup.select()
soup.findAll()
soup.a.tag_parent
soup.p.next_element
for i in soup.select('css_selector'):
some_variable = i.select_one('css_selector')
Code and full example in the one IDE:
import requests, lxml
from bs4 import BeautifulSoup
headers = {
"User-Agent":
"Mozilla/5.0 (Windows NT 10.0; Win64; x64) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/72.0.3538.102 Safari/537.36 Edge/18.19582"
}
params = {
'q': 'data science',
'hl': 'en',
'num': '100'
}
html = requests.get('https://www.google.com/search', headers=headers, params=params).text
soup = BeautifulSoup(html, 'lxml')
# container with all needed data
for result in soup.select('.tF2Cxc'):
title = result.select_one('.DKV0Md').text
link = result.select_one('.yuRUbf a')['href']
displayed_link = result.select_one('.TbwUpd.NJjxre').text
try:
snippet = result.select_one('#rso .lyLwlc').text
except: snippet = None
print(f'{title}\n{link}\n{displayed_link}\n{snippet}\n')
print('---------------')
'''
Data Science Specialization - Coursera
https://www.coursera.org/specializations/jhu-data-science
https://www.coursera.org › ... › Data Analysis
Offered by Johns Hopkins University. Launch Your Career in Data Science. A ten-course introduction to data science, developed and taught by .
---------------
'''
Alternatively, you can do the same thing using Google Organic Results API from SerpAPI. It's a paid API with a free plan.
The main difference is that you only need to iterate over structured JSON and get the data you want without figuring out how to select certain elements and extract data from there or bypass Google blocks if they'll appear or if you don't want to deal with JavaScript websites, e.g. Google Maps.
Code to integrate:
from serpapi import GoogleSearch
import os
params = {
"api_key": os.getenv("API_KEY"), # serpapi API key
"engine": "google", # search engine
"q": "data science", # search query
"hl": "en" # language of the search
}
search = GoogleSearch(params) # where data extraction happens
results = search.get_dict() # JSON -> Python dictionary
for result in results['organic_results']:
title = result['title']
link = result['link']
displayed_link = result['displayed_link']
snippet = result['snippet']
print(f"{title}\n{link}\n{displayed_link}\n{snippet}\n")
print('---------------')
'''
Data science - Wikipedia
https://en.wikipedia.org/wiki/Data_science
https://en.wikipedia.org › wiki › Data_science
Data science is an interdisciplinary field that uses scientific methods, processes, algorithms and systems to extract knowledge and insights from structured ...
---------------
'''
Disclaimer, I work for SerpApi.
Related
I've seen this before but I've never seen anything related to Google. When something is searched on Google, all of the links and titles are put in h3 tags. However, if i try to use Beautiful Soup, none of the h3 tags appear and it seems like a lot of the tags are missing. I don't think this is a JavaScript issue. Is there anything I'm missing?
link = "http://google.com/search?q=" + input
soup = BeautifulSoup(link, "lxml")
for item in soup.find_all("h3"):
print (item)
Edit: code
According to your code, you get the empty result because you didn't send any request for example via requests module as other people in the answers mentioned. You just passed it right into beautifulsoup and he doesn't know what to do with it.
Also, it's because there's no user-agent aka headers specified, and Google could block a request eventually. What is my user-agent
Code (CSS selectors reference):
import requests, lxml
from bs4 import BeautifulSoup
headers = {
'User-agent':
"Mozilla/5.0 (Windows NT 10.0; Win64; x64) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/70.0.3538.102 Safari/537.36 Edge/18.19582"
}
params = {
"q": "python memes",
"hl": "en"
}
soup = BeautifulSoup(requests.get('https://www.google.com/search', headers=headers, params=params).text, 'lxml')
# container will all title and links. Iterating over each title and link
for result in soup.select('.yuRUbf'):
title = result.select_one('.DKV0Md').text
url = result.a['href']
print(f'{title}, {url}\n')
---------
'''
35 Funny And Best Python Programming Memes - CodeItBro, https://www.codeitbro.com/funny-python-programming-memes/
ML Memes (#python.memes_) • Instagram photos and videos, https://www.instagram.com/python.memes_/?hl=en
...
'''
Alternatively, you can do the same thing using Google Organic Results API from SerpApi. It's a paid API with a free plan.
The differences are is that you only need to iterate over JSON string rather than scraping everything from scratch and don't worry about bypass blocks from Google or trying to understand how to scrape data from JavaScript, e.g. Google Maps or extract images from Google Images since it's already done for the end-user.
Code to integrate:
from serpapi import GoogleSearch
import os
params = {
"api_key": os.getenv("API_KEY"),
"engine": "google",
"q": "python memes",
"hl": "en"
}
search = GoogleSearch(params)
results = search.get_dict()
for result in results['organic_results']:
title = result['title']
url = result['link']
print(f'{title}, {url}\n')
---------
'''
35 Funny And Best Python Programming Memes - CodeItBro, https://www.codeitbro.com/funny-python-programming-memes/
ML Memes (#python.memes_) • Instagram photos and videos, https://www.instagram.com/python.memes_/?hl=en
...
'''
P.S. - I wrote a more detailed blog post about how to scrape Google Organic Results.
Disclaimer, I work for SerpApi.
Use requests to get the data. And narrow down your search in order to print only the titles:
from bs4 import BeautifulSoup
import requests
link = "http://google.com/search?q=" + input("Enter search")
headers = {'user-agent': 'Mozilla/5.0 (Macintosh; Intel Mac OS X 10.9; rv:32.0) Gecko/20100101 Firefox/32.0'}
r = requests.get(link, headers=headers)
soup = BeautifulSoup(r.text,'html5lib')
headings = soup.find_all('h3', class_ = 'LC20lb DKV0Md')
for heading in headings:
print(heading.text)
Output:
Enter search>? beautifulsoup
Beautiful Soup Documentation — Beautiful Soup 4.9.0 ...
Beautiful Soup: We called him Tortoise because he taught us.
Beautiful Soup documentation - Crummy
beautifulsoup4 · PyPI
Intro to Beautiful Soup | Programming Historian
Beautiful Soup (HTML parser) - Wikipedia
Implementing Web Scraping in Python with BeautifulSoup ...
Tutorial: Web Scraping with Python Using Beautiful Soup
Beautiful Soup - Quick Guide - Tutorialspoint
You need to first get the source code of the webpage using requests module and then you can pass it to BeautifulSoup constructor (also don't use input as variable name):
import requests
from bs4 import BeautifulSoup
Input = input("Enter search string: ")
link = "http://google.com/search?q=" + Input
html = requests.get(link).content
soup = BeautifulSoup(html, "lxml")
for item in soup.find_all("h3"):
print (item.text)
You can made the input fail safe too. In google search URL you should replace the spaces by + and + by %20:
import requests
from bs4 import BeautifulSoup
Input = input("Enter search string: ")
Input = Input.replace(" ","+").replace("+","%20")
link = "http://google.com/search?q=" + Input
html = requests.get(link).content
soup = BeautifulSoup(html, "lxml")
for item in soup.find_all("h3"):
print (item.text)
If you don't have the requests
I want to search google using BeautifulSoup and open the first link. But when I opened the link it shows error. The reason i think is that because google is not providing exact link of website, it has added several parameters in url. How to get exact url?
When i tried to use cite tag it worked but for big urls its creating problem.
The first link which i get using soup.h3.a['href'][7:] is:
'http://www.wikipedia.com/wiki/White_holes&sa=U&ved=0ahUKEwi_oYLLm_rUAhWJNI8KHa5SClsQFggbMAI&usg=AFQjCNGN-vlBvbJ9OPrnq40d0_b8M0KFJQ'
Here is my code:
import requests
from bs4 import Beautifulsoup
r = requests.get('https://www.google.com/search?q=site:wikipedia.com+Black+hole&gbv=1&sei=YwHNVpHLOYiWmQHk3K24Cw')
soup = BeautifulSoup(r.text, "html.parser")
print(soup.h3.a['href'][7:])
You could split the returned string:
url = soup.h3.a['href'][7:].split('&')
print(url[0])
hope by clubbing all answer together presented above ,your code will look like
this:
from bs4 import BeautifulSoup
import requests
import csv
import os
import time
url = "https://www.google.co.in/search?q=site:wikipedia.com+Black+hole&dcr=0&gbv=2&sei=Nr3rWfLXMIuGvQT9xZOgCA"
r = requests.get(url)
data = r.text
url1 = "https://www.google.co.in"
soup = BeautifulSoup(data, "html.parser")
get_details = soup.find_all("div", attrs={"class":"g"})
final_data = []
for details in get_details:
link = details.find_all("h3")
#links = ""
for mdetails in link:
links = mdetails.find_all("a")
lmk = ""
for lnk in links:
lmk = lnk.get("href")[7:].split("&")
sublist = []
sublist.append(lmk[0])
final_data.append(sublist)
filename = "Google.csv"
with open("./"+filename, "w")as csvfile:
csvfile = csv.writer(csvfile, delimiter=",")
csvfile.writerow("")
for i in range(0, len(final_data)):
csvfile.writerow(final_data[i])
It's much simpler. You're looking for this:
# instead of this:
soup.h3.a['href'][7:].split('&')
# use this:
soup.select_one('.yuRUbf a')['href']
Code and example in the online IDE:
from bs4 import BeautifulSoup
import requests, lxml
headers = {
'User-agent':
"Mozilla/5.0 (Windows NT 10.0; Win64; x64) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/70.0.3538.102 Safari/537.36 Edge/18.19582"
}
params = {
"q": "site:wikipedia.com black hole", # query
"gl": "us", # country to search from
"hl": "en" # language
}
html = requests.get("https://www.google.com/search", headers=headers, params=params)
soup = BeautifulSoup(html.text, 'lxml')
first_link = soup.select_one('.yuRUbf a')['href']
print(first_link)
# https://en.wikipedia.com/wiki/Primordial_black_hole
Alternatively, you can achieve the same thing by using Google Organic Results API from SerpApi. It's a paid API with a free plan.
The difference in your case is that you only need to extract the data from the structured JSON rather than figuring out why things don't work and then maintain it over time if some selectors will change.
Code to integrate:
import os
from serpapi import GoogleSearch
params = {
"engine": "google",
"q": "site:wikipedia.com black hole",
"hl": "en",
"gl": "us",
"api_key": os.getenv("API_KEY"),
}
search = GoogleSearch(params)
results = search.get_dict()
# [0] - first index of search results
first_link = results['organic_results'][0]['link']
print(first_link)
# https://en.wikipedia.com/wiki/Primordial_black_hole
Disclaimer, I work for SerpApi.
I am trying to scrape the PDF links from the search results from Google Scholar. I have tried to set a page counter based on the change in URL, but after the first eight output links, I am getting repetitive links as output.
#!/usr/bin/env python
from mechanize import Browser
from BeautifulSoup import BeautifulSoup
from bs4 import BeautifulSoup
import urllib2
import requests
#modifying the url as per page
urlCounter = 0
while urlCounter <=30:
urlPart1 = "http://scholar.google.com/scholar?start="
urlPart2 = "&q=%22entity+resolution%22&hl=en&as_sdt=0,4"
url = urlPart1 + str(urlCounter) + urlPart2
page = urllib2.Request(url,None,{"User-Agent":"Mozilla/5.0 (X11; U; Linux i686) Gecko/20071127 Firefox/2.0.0.11"})
resp = urllib2.urlopen(page)
html = resp.read()
soup = BeautifulSoup(html)
urlCounter = urlCounter + 10
recordCount = 0
while recordCount <=9:
recordPart1 = "gs_ggsW"
finRecord = recordPart1 + str(recordCount)
recordCount = recordCount+1
#printing the links
for link in soup.find_all('div', id = finRecord):
linkstring = str(link)
soup1 = BeautifulSoup(linkstring)
for link in soup1.find_all('a'):
print(link.get('href'))
Change the following line in your code:
finRecord = recordPart1 + str(recordCount)
To
finRecord = recordPart1 + str(recordCount+urlCounter-10)
The real problem: div ids in the first page are gs_ggsW[0-9], but ids on the second page are gs_ggsW[10-19]. So beautiful soup will find no links on the 2nd page.
Python's variable scope may confuse people from other languages, like Java. After the for loop below being executed, the variable link still exists. So the link is referenced to the last link on the 1st page.
for link in soup1.find_all('a'):
print(link.get('href'))
Updates:
Google may not provide pdf download links for some papers, so you can't use id to match the link of each paper. You can use css selecters to match all the links together.
soup = BeautifulSoup(html)
urlCounter = urlCounter + 10
for link in soup.select('div.gs_ttss a'):
print(link.get('href'))
Have a look at the SelectorGadget Chrome extension to grab CSS selectors by clicking on the desired element in your browser.
Code and example in the online IDE to extract PDF's:
from bs4 import BeautifulSoup
import requests, lxml
params = {
"q": "entity resolution", # search query
"hl": "en" # language
}
# https://requests.readthedocs.io/en/master/user/quickstart/#custom-headers
headers = {
"User-Agent": "Mozilla/5.0 (Windows NT 10.0; Win64; x64) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/72.0.3538.102 Safari/537.36 Edge/18.19582",
}
html = requests.get("https://scholar.google.com/scholar", params=params, headers=headers, timeout=30)
soup = BeautifulSoup(html.text, "lxml")
for pdf_link in soup.select(".gs_or_ggsm a"):
pdf_file_link = pdf_link["href"]
print(pdf_file_link)
# output from the first page:
'''
https://linqs.github.io/linqs-website/assets/resources/getoor-vldb12-slides.pdf
http://ilpubs.stanford.edu:8090/859/1/2008-7.pdf
https://drum.lib.umd.edu/bitstream/handle/1903/4241/umi-umd-4070.pdf;sequence=1
https://citeseerx.ist.psu.edu/viewdoc/download?doi=10.1.1.169.9535&rep=rep1&type=pdf
https://arxiv.org/pdf/1208.1927
https://citeseerx.ist.psu.edu/viewdoc/download?doi=10.1.1.77.6875&rep=rep1&type=pdf
http://da.qcri.org/ntang/pubs/vldb18-deeper.pdf
'''
Alternatively, you can achieve the same thing by using Google Scholar Organic Results API from SerpApi. It's a paid API with a free plan.
The main difference is that you only need to grab the data from structured JSON instead of figuring out how to extract the data from HTML, how to bypass blocks from search engines.
Code to integrate:
from serpapi import GoogleSearch
params = {
"api_key": "YOUR_API_KEY", # SerpApi API key
"engine": "google_scholar", # Google Scholar organic reuslts
"q": "entity resolution", # search query
"hl": "en" # language
}
search = GoogleSearch(params)
results = search.get_dict()
for pdfs in results["organic_results"]:
for link in pdfs.get("resources", []):
pdf_link = link["link"]
print(pdf_link)
# output:
'''
https://linqs.github.io/linqs-website/assets/resources/getoor-vldb12-slides.pdf
http://ilpubs.stanford.edu:8090/859/1/2008-7.pdf
https://drum.lib.umd.edu/bitstream/handle/1903/4241/umi-umd-4070.pdf;sequence=1
https://citeseerx.ist.psu.edu/viewdoc/download?doi=10.1.1.169.9535&rep=rep1&type=pdf
https://arxiv.org/pdf/1208.1927
https://citeseerx.ist.psu.edu/viewdoc/download?doi=10.1.1.77.6875&rep=rep1&type=pdf
http://da.qcri.org/ntang/pubs/vldb18-deeper.pdf
'''
If you want to scrape more data from organic results, there's a dedicated Scrape Google Scholar with Python blog post of mine.
Disclaimer, I work for SerpApi.
It appears that google searches will give the following url:
/url?q= "URL WOULD BE HERE" &sa=U&ei=9LFsUbPhN47qqAHSkoGoDQ&ved=0CCoQFjAA&usg=AFQjCNEZ_f4a9Lnb8v2_xH0GLQ_-H0fokw
When subjected to a html parsing by BeautifulSoup.
I am getting the links by using soup.findAll('a') and then using a['href'].
More specifically, the code I have used is the following:
import urllib2
from BeautifulSoup import BeautifulSoup, SoupStrainer
import re
main_site = 'https://www.google.com/'
search = 'search?q='
query = 'pillows'
full_url = main_site+search+query
request = urllib2.Request(full_url, headers={'User-Agent': 'Chrome/16.0.912.77'})
main_html = urllib2.urlopen(request).read()
results = BeautifulSoup(main_html, parseOnlyThese=SoupStrainer('div', {'id': 'search'}))
try:
for search_hit in results.findAll('li', {'class':'g'}):
for elm in search_hit.findAll('h3',{'class':'r'}):
for a in elm.findAll('a',{'href':re.compile('.+')}):
print a['href']
except TypeError:
pass
Also, I have noticed on other sites that the a['href'] may return something like /dsoicjsdaoicjsdcj where the link would take you to website.com/dsoicjsdaoicjsdcj.
I know if this is the case that I can simply concatenate them, but I feel like it shouldn't be that I should have to change the way I parse up and treat the a['href'] based on which website I'm looking at. Is there a better way to get this link? Is there some javascript that I need to take into account? Surely there is a simply way in BeautifulSoup to get the full html to follow from a?
SoupStrainer('div', {'class': "vsc"})
returns nothing cause when you do:
print main_html
and search for "vsc", there is no result
You're looking for this:
# container with needed data: title, link, etc.
for result in soup.select('.tF2Cxc'):
link = result.select_one('.yuRUbf a')['href']
Also, while using requests library, you can pass URL params easily like so:
# this:
main_site = 'https://www.google.com/'
search = 'search?q='
query = 'pillows'
full_url = main_site+search+query
# could be translated to this:
params = {
'q': 'minecraft',
'gl': 'us',
'hl': 'en',
}
html = requests.get('https://www.google.com/search', params=params)
While using urllib you can do it like so (In python 3, this has been moved to urllib.parse.urlencode):
# https://stackoverflow.com/a/54050957/15164646
# https://stackoverflow.com/a/2506425/15164646
url = "https://disc.gsfc.nasa.gov/SSW/#keywords="
params = {'keyword':"(GPM_3IMERGHHE)", 't1':"2019-01-02", 't2':"2019-01-03", 'bboxBbox':"3.52,32.34,16.88,42.89"}
quoted_params = urllib.parse.urlencode(params)
# 'bboxBbox=3.52%2C32.34%2C16.88%2C42.89&t2=2019-01-03&keyword=%28GPM_3IMERGHHE%29&t1=2019-01-02'
full_url = url + quoted_params
# 'https://disc.gsfc.nasa.gov/SSW/#keywords=bboxBbox=3.52%2C32.34%2C16.88%2C42.89&t2=2019-01-03&keyword=%28GPM_3IMERGHHE%29&t1=2019-01-02'
resp = urllib.urlopen(full_url).read()
Code and example in the online IDE:
from bs4 import BeautifulSoup
import requests, lxml
headers = {
'User-agent':
'Mozilla/5.0 (Windows NT 10.0; Win64; x64) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/70.0.3538.102 Safari/537.36 Edge/18.19582'
}
params = {
'q': 'minecraft',
'gl': 'us',
'hl': 'en',
}
html = requests.get('https://www.google.com/search', headers=headers, params=params)
soup = BeautifulSoup(html.text, 'lxml')
for result in soup.select('.tF2Cxc'):
link = result.select_one('.yuRUbf a')['href']
print(link)
---------
'''
https://www.minecraft.net/en-us/
https://classic.minecraft.net/
https://play.google.com/store/apps/details?id=com.mojang.minecraftpe&hl=en_US&gl=US
https://en.wikipedia.org/wiki/Minecraft
'''
Alternatively, you can achieve the same thing by using Google Organic Results API from SerpApi. It's a paid API with a free plan.
The difference in your case is that you don't have to make everything from scratch, bypass blocks, and maintain the parser over time.
Code to integrate to achieve your goal:
import os
from serpapi import GoogleSearch
params = {
"engine": "google",
"q": "minecraft",
"hl": "en",
"gl": "us",
"api_key": os.getenv("API_KEY"),
}
search = GoogleSearch(params)
results = search.get_dict()
for result in results["organic_results"]:
print(result['link'])
---------
'''
https://www.minecraft.net/en-us/
https://classic.minecraft.net/
https://play.google.com/store/apps/details?id=com.mojang.minecraftpe&hl=en_US&gl=US
https://en.wikipedia.org/wiki/Minecraft
'''
Disclaimer, I work for SerpApi.
A google search gives me the following first result on HTML:
<h3 class="r"><em>Quantitative Trading</em>: <em>How to Build Your Own Algorithmic</em> <b>...</b> - Amazon</h3>
I would like to extract the link http://www.amazon.com/Quantitative-Trading-Build-Algorithmic-Business/dp/0470284889 from this, but when I use beautiful soup to extract the information, I obtain
soup.find("h3").find("a").get("href")
I obtain the following string instead:
/url?q=http://www.amazon.com/Quantitative-Trading-Build-Algorithmic-Business/dp/0470284889&sa=U&ei=P2ycT6OoNuasiAL2ncV5&ved=0CBIQFjAA&usg=AFQjCNEo_ujANAKnjheWDRlBKnJ1BGeA7A
I know that the link is in there and I could parse it by deleting the /url?q= and everything after the & symbol, but I was wondering if there was a cleaner solution.
Thanks!
You can use a combination of urlparse.urlparse and urlparse.parse_qs, e.g
>>> import urlparse
>>> url = '/url?q=http://www.amazon.com/Quantitative-Trading-Build-Algorithmic-Business/dp/0470284889&sa=U&ei=P2ycT6OoNuasiAL2ncV5&ved=0CBIQFjAA&usg=AFQjCNEo_ujANAKnjheWDRlBKnJ1BGe'
>>> data = urlparse.parse_qs(
... urlparse.urlparse(url).query
... )
>>> data
{'ei': ['P2ycT6OoNuasiAL2ncV5'],
'q': ['http://www.amazon.com/Quantitative-Trading-Build-Algorithmic-Business/dp/0470284889'],
'sa': ['U'],
'usg': ['AFQjCNEo_ujANAKnjheWDRlBKnJ1BGe'],
'ved': ['0CBIQFjAA']}
>>> data['q'][0]
'http://www.amazon.com/Quantitative-Trading-Build-Algorithmic-Business/dp/0470284889'
To extract only the first result from the page you can use select_one() by passing a CSS selectors or find() bs4 methods.
Code and example in the online IDE:
import requests, lxml
from bs4 import BeautifulSoup
headers = {
"User-Agent":
"Mozilla/5.0 (Windows NT 10.0; Win64; x64) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/72.0.3538.102 Safari/537.36 Edge/18.19582"
}
# passing parameters in URLs
# https://docs.python-requests.org/en/master/user/quickstart/#passing-parameters-in-urls
params = {'q': 'Quantitative Trading How to Build Your Own Algorithmic - amazon'}
def bs4_get_first_googlesearch():
html = requests.get('https://www.google.com/search', headers=headers, params=params).text
soup = BeautifulSoup(html, 'lxml')
first_link = soup.select_one('.yuRUbf').a['href']
print(first_link)
bs4_get_first_googlesearch()
# output:
'''
https://www.amazon.com/Quantitative-Trading-Build-Algorithmic-Business/dp/0470284889
'''
Alternatively, you can do the same thing using Google Search Engine Results API from SerpApi. It's a paid API with a free trial of 5,000 searches. Check out the playground.
The big difference is that everything is already done for the end-user: selecting elements, bypass blocking, proxy rotation, and more.
Code to integrate:
from serpapi import GoogleSearch
import os
def serpapi_get_first_googlesearch():
params = {
"api_key": os.getenv("API_KEY"),
"engine": "google",
"q": "Quantitative Trading How to Build Your Own Algorithmic - amazon",
"hl": "en",
}
search = GoogleSearch(params)
results = search.get_dict()
# [0] - first element from the search results
first_link = results['organic_results'][0]['link']
print(first_link)
serpapi_get_first_googlesearch()
# output:
'''
https://www.amazon.com/Quantitative-Trading-Build-Algorithmic-Business/dp/0470284889
'''
Disclaimer, I work for SerpApi.