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This project is made for automatic web scraping to make scraping easy. It gets a url or the html content of a web page and a list of sample data which we want to scrape from that page. This data can be text, url or any html tag value of that page. It learns the scraping rules and returns the similar elements. Then you can use this learned object with new urls to get similar content or the exact same element of those new pages!
$ pip install git+//github.com/alirezamika/autoscraper.git
Getting similar results
Say we want to fetch all related post titles in a stackoverflow page:from autoscraper import AutoScraper
url = '//stackoverflow.com/questions/2081586/web-scraping-with-python'
# We can add one or multiple candidates here.
# You can also put urls here to retrieve urls.
wanted_list = ["How to call an external command?"]
scraper = AutoScraper()
result = scraper.build(url, wanted_list)
print(result)
[
'How do I merge two dictionaries in a single expression in Python (taking union of dictionaries)?',
'How to call an external command?',
'What are metaclasses in Python?',
'Does Python have a ternary conditional operator?',
'How do you remove duplicates from a list whilst preserving order?',
'Convert bytes to a string',
'How to get line count of a large file cheaply in Python?',
"Does Python have a string 'contains' substring method?",
'Why is “00000 in range(00001)” so fast in Python 3?'
]
Now you can use the
scraper
object to get related topics of any stackoverflow page:scraper.get_result_similar('//stackoverflow.com/questions/606191/convert-bytes-to-a-string')
Getting exact result
Say we want to scrape live stock prices from yahoo finance:from autoscraper import AutoScraper
url = '//finance.yahoo.com/quote/AAPL/'
wanted_list = ["124.81"]
scraper = AutoScraper()
# Here we can also pass html content via the html parameter instead of the url (html=html_content)
result = scraper.build(url, wanted_list)
print(result)
You can also pass any custom
requests
module parameter. for example you may want to use proxies or custom headers:proxies = {
"http": '//127.0.0.1:8001',
"https": '//127.0.0.1:8001',
}
result = scraper.build(url, wanted_list, request_args=dict(proxies=proxies))
scraper.get_result_exact('//finance.yahoo.com/quote/MSFT/')
You may want to get other info as well. For example if you want to get market cap too, you can just append it to the wanted list. By using the
get_result_exact
method, it will retrieve the data as the same exact order in the wanted list.Saving the model
We can now save the built model to use it later. To save:# Give it a file path
scraper.save('yahoo-finance')
scraper.load('yahoo-finance')
Generating the scraper python code
We can also generate a stand-alone code for the learned scraper to use it anywhere:code = scraper.generate_python_code()
print(code)
It will print the generated code. There's a class named
GeneratedAutoScraper
which has the methods get_result_similar
and get_result_exact
which you can use. You can also use get_result
method to get both.