Scraping an 'onclick' table with Selenium in Python
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I am attempting to scrape the following webpage, using Selenium in Python (with Chrome Web Driver).
https://www.betexplorer.com/soccer/argentina/superliga/argentinos-jrs-talleres-cordoba/ptSIK7kB/#ah1
I only wish to collect the rows of data in which the bookmaker is Bet365.
I have been able to obtain all the rows where this is the case. However, I am struggling to scrape the information within the 'onclick' table that appears when the values are clicked:
The image above shows the table ARCHIVE ODDS, which appears when the 5.90 is clicked.
The aim is to collect the information from each table in all the rows where Bet365 is the bookmaker.
My attempt so far has been to locate all the 'onclick' links using a CSS-selector:
table_links = browser.find_elements_by_css_selector("span[onclick*='16);']")
And then to loop through each of the table_links, click each one, and scrape the data which appears using the xpath:
bet365table =
for i in table_links:
i.click()
xx = browser.find_element_by_xpath("//TBODY[@id='aodds-tbody']")
bet365table.append(xx)
However, this fails each time with the error stating the element is not clickable.
python selenium web-scraping
asked Nov 23 '18 at 11:24
bobmanbobman
368
add a comment |
I am attempting to scrape the following webpage, using Selenium in Python (with Chrome Web Driver).
https://www.betexplorer.com/soccer/argentina/superliga/argentinos-jrs-talleres-cordoba/ptSIK7kB/#ah1
I only wish to collect the rows of data in which the bookmaker is Bet365.
I have been able to obtain all the rows where this is the case. However, I am struggling to scrape the information within the 'onclick' table that appears when the values are clicked:
The image above shows the table ARCHIVE ODDS, which appears when the 5.90 is clicked.
The aim is to collect the information from each table in all the rows where Bet365 is the bookmaker.
My attempt so far has been to locate all the 'onclick' links using a CSS-selector:
table_links = browser.find_elements_by_css_selector("span[onclick*='16);']")
And then to loop through each of the table_links, click each one, and scrape the data which appears using the xpath:
bet365table =
for i in table_links:
i.click()
xx = browser.find_element_by_xpath("//TBODY[@id='aodds-tbody']")
bet365table.append(xx)
However, this fails each time with the error stating the element is not clickable.
python selenium web-scraping
asked Nov 23 '18 at 11:24
bobmanbobman
368
Update the question with the relevant HTML and your code trials
– DebanjanB
Nov 23 '18 at 11:26
@DebanjanB i've updated the post with my attempts so far - from my end the link in the post works, but please let me know if you're having difficulties reaching it!
– bobman
Nov 23 '18 at 11:41
add a comment |
I am attempting to scrape the following webpage, using Selenium in Python (with Chrome Web Driver).
https://www.betexplorer.com/soccer/argentina/superliga/argentinos-jrs-talleres-cordoba/ptSIK7kB/#ah1
I only wish to collect the rows of data in which the bookmaker is Bet365.
I have been able to obtain all the rows where this is the case. However, I am struggling to scrape the information within the 'onclick' table that appears when the values are clicked:
The image above shows the table ARCHIVE ODDS, which appears when the 5.90 is clicked.
The aim is to collect the information from each table in all the rows where Bet365 is the bookmaker.
My attempt so far has been to locate all the 'onclick' links using a CSS-selector:
table_links = browser.find_elements_by_css_selector("span[onclick*='16);']")
And then to loop through each of the table_links, click each one, and scrape the data which appears using the xpath:
bet365table =
for i in table_links:
i.click()
xx = browser.find_element_by_xpath("//TBODY[@id='aodds-tbody']")
bet365table.append(xx)
However, this fails each time with the error stating the element is not clickable.
python selenium web-scraping
asked Nov 23 '18 at 11:24
bobmanbobman
368
I am attempting to scrape the following webpage, using Selenium in Python (with Chrome Web Driver).
https://www.betexplorer.com/soccer/argentina/superliga/argentinos-jrs-talleres-cordoba/ptSIK7kB/#ah1
I only wish to collect the rows of data in which the bookmaker is Bet365.
I have been able to obtain all the rows where this is the case. However, I am struggling to scrape the information within the 'onclick' table that appears when the values are clicked:
The image above shows the table ARCHIVE ODDS, which appears when the 5.90 is clicked.
The aim is to collect the information from each table in all the rows where Bet365 is the bookmaker.
My attempt so far has been to locate all the 'onclick' links using a CSS-selector:
table_links = browser.find_elements_by_css_selector("span[onclick*='16);']")
And then to loop through each of the table_links, click each one, and scrape the data which appears using the xpath:
bet365table =
for i in table_links:
i.click()
xx = browser.find_element_by_xpath("//TBODY[@id='aodds-tbody']")
bet365table.append(xx)
However, this fails each time with the error stating the element is not clickable.
python selenium web-scraping
python selenium web-scraping
asked Nov 23 '18 at 11:24
bobmanbobman
368
asked Nov 23 '18 at 11:24
bobmanbobman
368
edited Nov 23 '18 at 11:40
bobman
asked Nov 23 '18 at 11:24
bobmanbobman
368
asked Nov 23 '18 at 11:24
bobmanbobman
368
asked Nov 23 '18 at 11:24
bobmanbobman
368
368
Update the question with the relevant HTML and your code trials
– DebanjanB
Nov 23 '18 at 11:26
@DebanjanB i've updated the post with my attempts so far - from my end the link in the post works, but please let me know if you're having difficulties reaching it!
– bobman
Nov 23 '18 at 11:41
add a comment |
Update the question with the relevant HTML and your code trials
– DebanjanB
Nov 23 '18 at 11:26
@DebanjanB i've updated the post with my attempts so far - from my end the link in the post works, but please let me know if you're having difficulties reaching it!
– bobman
Nov 23 '18 at 11:41
Update the question with the relevant HTML and your code trials
– DebanjanB
Nov 23 '18 at 11:26
Update the question with the relevant HTML and your code trials
– DebanjanB
Nov 23 '18 at 11:26
@DebanjanB i've updated the post with my attempts so far - from my end the link in the post works, but please let me know if you're having difficulties reaching it!
– bobman
Nov 23 '18 at 11:41
@DebanjanB i've updated the post with my attempts so far - from my end the link in the post works, but please let me know if you're having difficulties reaching it!
– bobman
Nov 23 '18 at 11:41
add a comment |
1 Answer
1
active
oldest
votes
You could also mimic the XHR requests and get the JSON responses. Bet365 has id of 16. You can test for qualifying rows with CSS selector
import requests
import pandas as pd
import json
from pandas.io.json import json_normalize
from selenium import webdriver
from selenium.webdriver.support.ui import WebDriverWait
from selenium.webdriver.support import expected_conditions as EC
from selenium.webdriver.common.by import By
d = webdriver.Chrome()
d.get("https://www.betexplorer.com/soccer/argentina/superliga/argentinos-jrs-talleres-cordoba/ptSIK7kB/#ah")
WebDriverWait(d,10).until(EC.visibility_of_all_elements_located((By.CSS_SELECTOR, ".in-bookmaker-logo-link.in-bookmaker-logo-link--primary.l16")))
base = 'https://www.betexplorer.com/archive-odds/'
links = d.find_elements_by_css_selector("[onclick$=', 16);']")
extracted_links = [link.get_attribute("onclick").strip("load_odds_archive(this, '").strip("', 16);") for link in links]
json_links = [base + link + '/16/?_=1' for link in extracted_links]
for link in json_links:
res = requests.get(link)
data= json.loads(res.content)
data = json_normalize(data)
print(data)
d.quit()
answered Nov 23 '18 at 12:21
QHarrQHarr
37.1k82144
Did not know this was a possible method! Can I please ask, how did you find out this is a possibility for this website?
– bobman
Nov 23 '18 at 12:53
I used dev tools (F12) to monitor the traffic when pressing to display the tables for odds. I noticed that 16 was associated with Bet365 and that a JSON response was returned. I also saw that the start of the request URL was constant, the middle part came from the existing 365 href and that the end was a constant plus an incrementing number which bore no real significance AFAICS, so I just plugged the number 1 onto the end of the request URL. I suspect they may even offer an API so worth looking into that.
– QHarr
Nov 23 '18 at 12:56
add a comment |
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1 Answer
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1 Answer
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active
oldest
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active
oldest
votes
active
oldest
votes
You could also mimic the XHR requests and get the JSON responses. Bet365 has id of 16. You can test for qualifying rows with CSS selector
import requests
import pandas as pd
import json
from pandas.io.json import json_normalize
from selenium import webdriver
from selenium.webdriver.support.ui import WebDriverWait
from selenium.webdriver.support import expected_conditions as EC
from selenium.webdriver.common.by import By
d = webdriver.Chrome()
d.get("https://www.betexplorer.com/soccer/argentina/superliga/argentinos-jrs-talleres-cordoba/ptSIK7kB/#ah")
WebDriverWait(d,10).until(EC.visibility_of_all_elements_located((By.CSS_SELECTOR, ".in-bookmaker-logo-link.in-bookmaker-logo-link--primary.l16")))
base = 'https://www.betexplorer.com/archive-odds/'
links = d.find_elements_by_css_selector("[onclick$=', 16);']")
extracted_links = [link.get_attribute("onclick").strip("load_odds_archive(this, '").strip("', 16);") for link in links]
json_links = [base + link + '/16/?_=1' for link in extracted_links]
for link in json_links:
res = requests.get(link)
data= json.loads(res.content)
data = json_normalize(data)
print(data)
d.quit()
answered Nov 23 '18 at 12:21
QHarrQHarr
37.1k82144
Did not know this was a possible method! Can I please ask, how did you find out this is a possibility for this website?
– bobman
Nov 23 '18 at 12:53
I used dev tools (F12) to monitor the traffic when pressing to display the tables for odds. I noticed that 16 was associated with Bet365 and that a JSON response was returned. I also saw that the start of the request URL was constant, the middle part came from the existing 365 href and that the end was a constant plus an incrementing number which bore no real significance AFAICS, so I just plugged the number 1 onto the end of the request URL. I suspect they may even offer an API so worth looking into that.
– QHarr
Nov 23 '18 at 12:56
add a comment |
You could also mimic the XHR requests and get the JSON responses. Bet365 has id of 16. You can test for qualifying rows with CSS selector
import requests
import pandas as pd
import json
from pandas.io.json import json_normalize
from selenium import webdriver
from selenium.webdriver.support.ui import WebDriverWait
from selenium.webdriver.support import expected_conditions as EC
from selenium.webdriver.common.by import By
d = webdriver.Chrome()
d.get("https://www.betexplorer.com/soccer/argentina/superliga/argentinos-jrs-talleres-cordoba/ptSIK7kB/#ah")
WebDriverWait(d,10).until(EC.visibility_of_all_elements_located((By.CSS_SELECTOR, ".in-bookmaker-logo-link.in-bookmaker-logo-link--primary.l16")))
base = 'https://www.betexplorer.com/archive-odds/'
links = d.find_elements_by_css_selector("[onclick$=', 16);']")
extracted_links = [link.get_attribute("onclick").strip("load_odds_archive(this, '").strip("', 16);") for link in links]
json_links = [base + link + '/16/?_=1' for link in extracted_links]
for link in json_links:
res = requests.get(link)
data= json.loads(res.content)
data = json_normalize(data)
print(data)
d.quit()
answered Nov 23 '18 at 12:21
QHarrQHarr
37.1k82144
Did not know this was a possible method! Can I please ask, how did you find out this is a possibility for this website?
– bobman
Nov 23 '18 at 12:53
I used dev tools (F12) to monitor the traffic when pressing to display the tables for odds. I noticed that 16 was associated with Bet365 and that a JSON response was returned. I also saw that the start of the request URL was constant, the middle part came from the existing 365 href and that the end was a constant plus an incrementing number which bore no real significance AFAICS, so I just plugged the number 1 onto the end of the request URL. I suspect they may even offer an API so worth looking into that.
– QHarr
Nov 23 '18 at 12:56
add a comment |
You could also mimic the XHR requests and get the JSON responses. Bet365 has id of 16. You can test for qualifying rows with CSS selector
import requests
import pandas as pd
import json
from pandas.io.json import json_normalize
from selenium import webdriver
from selenium.webdriver.support.ui import WebDriverWait
from selenium.webdriver.support import expected_conditions as EC
from selenium.webdriver.common.by import By
d = webdriver.Chrome()
d.get("https://www.betexplorer.com/soccer/argentina/superliga/argentinos-jrs-talleres-cordoba/ptSIK7kB/#ah")
WebDriverWait(d,10).until(EC.visibility_of_all_elements_located((By.CSS_SELECTOR, ".in-bookmaker-logo-link.in-bookmaker-logo-link--primary.l16")))
base = 'https://www.betexplorer.com/archive-odds/'
links = d.find_elements_by_css_selector("[onclick$=', 16);']")
extracted_links = [link.get_attribute("onclick").strip("load_odds_archive(this, '").strip("', 16);") for link in links]
json_links = [base + link + '/16/?_=1' for link in extracted_links]
for link in json_links:
res = requests.get(link)
data= json.loads(res.content)
data = json_normalize(data)
print(data)
d.quit()
answered Nov 23 '18 at 12:21
QHarrQHarr
37.1k82144
You could also mimic the XHR requests and get the JSON responses. Bet365 has id of 16. You can test for qualifying rows with CSS selector
import requests
import pandas as pd
import json
from pandas.io.json import json_normalize
from selenium import webdriver
from selenium.webdriver.support.ui import WebDriverWait
from selenium.webdriver.support import expected_conditions as EC
from selenium.webdriver.common.by import By
d = webdriver.Chrome()
d.get("https://www.betexplorer.com/soccer/argentina/superliga/argentinos-jrs-talleres-cordoba/ptSIK7kB/#ah")
WebDriverWait(d,10).until(EC.visibility_of_all_elements_located((By.CSS_SELECTOR, ".in-bookmaker-logo-link.in-bookmaker-logo-link--primary.l16")))
base = 'https://www.betexplorer.com/archive-odds/'
links = d.find_elements_by_css_selector("[onclick$=', 16);']")
extracted_links = [link.get_attribute("onclick").strip("load_odds_archive(this, '").strip("', 16);") for link in links]
json_links = [base + link + '/16/?_=1' for link in extracted_links]
for link in json_links:
res = requests.get(link)
data= json.loads(res.content)
data = json_normalize(data)
print(data)
d.quit()
answered Nov 23 '18 at 12:21
QHarrQHarr
37.1k82144
answered Nov 23 '18 at 12:21
QHarrQHarr
37.1k82144
answered Nov 23 '18 at 12:21
QHarrQHarr
37.1k82144
answered Nov 23 '18 at 12:21
QHarrQHarr
37.1k82144
37.1k82144
Did not know this was a possible method! Can I please ask, how did you find out this is a possibility for this website?
– bobman
Nov 23 '18 at 12:53
I used dev tools (F12) to monitor the traffic when pressing to display the tables for odds. I noticed that 16 was associated with Bet365 and that a JSON response was returned. I also saw that the start of the request URL was constant, the middle part came from the existing 365 href and that the end was a constant plus an incrementing number which bore no real significance AFAICS, so I just plugged the number 1 onto the end of the request URL. I suspect they may even offer an API so worth looking into that.
– QHarr
Nov 23 '18 at 12:56
add a comment |
Did not know this was a possible method! Can I please ask, how did you find out this is a possibility for this website?
– bobman
Nov 23 '18 at 12:53
I used dev tools (F12) to monitor the traffic when pressing to display the tables for odds. I noticed that 16 was associated with Bet365 and that a JSON response was returned. I also saw that the start of the request URL was constant, the middle part came from the existing 365 href and that the end was a constant plus an incrementing number which bore no real significance AFAICS, so I just plugged the number 1 onto the end of the request URL. I suspect they may even offer an API so worth looking into that.
– QHarr
Nov 23 '18 at 12:56
Did not know this was a possible method! Can I please ask, how did you find out this is a possibility for this website?
– bobman
Nov 23 '18 at 12:53
Did not know this was a possible method! Can I please ask, how did you find out this is a possibility for this website?
– bobman
Nov 23 '18 at 12:53
I used dev tools (F12) to monitor the traffic when pressing to display the tables for odds. I noticed that 16 was associated with Bet365 and that a JSON response was returned. I also saw that the start of the request URL was constant, the middle part came from the existing 365 href and that the end was a constant plus an incrementing number which bore no real significance AFAICS, so I just plugged the number 1 onto the end of the request URL. I suspect they may even offer an API so worth looking into that.
– QHarr
Nov 23 '18 at 12:56
I used dev tools (F12) to monitor the traffic when pressing to display the tables for odds. I noticed that 16 was associated with Bet365 and that a JSON response was returned. I also saw that the start of the request URL was constant, the middle part came from the existing 365 href and that the end was a constant plus an incrementing number which bore no real significance AFAICS, so I just plugged the number 1 onto the end of the request URL. I suspect they may even offer an API so worth looking into that.
– QHarr
Nov 23 '18 at 12:56
add a comment |
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Update the question with the relevant HTML and your code trials
– DebanjanB
Nov 23 '18 at 11:26
@DebanjanB i've updated the post with my attempts so far - from my end the link in the post works, but please let me know if you're having difficulties reaching it!
– bobman
Nov 23 '18 at 11:41