how to jump to next page in centaline property

[ivywze]

Troubleshooting

Describe your environment

• Operating system: ios
• Python version: 3.0
• Hardware:
• Internet access:
• Jupyter notebook or not? [Y/N]: Y
• Which chapter of book?: ch7

Describe your question

Cannot jump to the next page in centaline property, attached with the pageing source.

Describe the efforts you have spent on this issue

The URL of different pages doesn't change, also I tried to treat the '下一頁' as a button and try to click but failed.

click as a button

python:

data = []

while True:
    try:
        loadMoreButton = browser.find_element_by_class_name("pagingNext pagingA")
        time.sleep(2)
        loadMoreButton.click()
        time.sleep(5)
    except Exception as e:
        print(e)
        break

data.extend(get_articles_from_browser())
        
print("Complete")
# time.sleep(10)
browser.quit()

[hupili]

can you print the “loadMoreButton”? See if the element is correctly located and selected.

[hupili]

more details helps, eg the content of the element, its location, etc. Also, try the find elements (plural) version of the methods to see if more elements matched the CSS selector. Sometimes, you matched more. So the script clicked some other elements.

[ivywze]

can you print the “loadMoreButton”? See if the element is correctly located and selected.

It yields invalid selector: Compound class names not permitted, I follow the trick here solved this problem.

[ivywze]

But another error occured NewConnectionError('<urllib3.connection.HTTPConnection object at 0x10d9766a0>: Failed to establish a new connection: [Errno 61] Connection refused'.

I am wondering, instead of trying to click the button, is there other way to go to next page?

[hupili]

You can also try to to conduct network trace analysis —- some cases in our “advanced scraping” chapter, the open book

[hupili]

@ivyWANG958 , this is the section on network trace analysis: https://github.com/hupili/python-for-data-and-media-communication-gitbook/blob/master/notes-week-08.md#analyse-network-traces