AutoScraper: A Smart, Automatic, Fast and Lightweight Web Scraper for Python
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.
Installation
It's compatible with python 3.
- Install latest version from git repository using pip:
$ pip install git+https://github.com/alirezamika/autoscraper.git
$ pip install autoscraper
$ python setup.py install
How to use
Getting similar results
Say we want to fetch all related post titles in a stackoverflow page:
from autoscraper import AutoScraper
url = 'https://stackoverflow.com/questions/2081586/web-scraping-with-python'
wanted_list = ["What are metaclasses in Python?"]
scraper = AutoScraper()
result = scraper.build(url, wanted_list)
print(result)
Here's the output:
[
'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 “1000000000000000 in range(1000000000000001)” so fast in Python 3?'
]
Now you can use the scraper
object to get related topics of any stackoverflow page:
scraper.get_result_similar('https://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 = 'https://finance.yahoo.com/quote/AAPL/'
wanted_list = ["124.81"]
scraper = AutoScraper()
result = scraper.build(url, wanted_list)
print(result)
Note that you should update the wanted_list
if you want to copy this code, as the content of the page dynamically changes.
You can also pass any custom requests
module parameter. for example you may want to use proxies or custom headers:
proxies = {
"http": 'http://127.0.0.1:8001',
"https": 'https://127.0.0.1:8001',
}
result = scraper.build(url, wanted_list, request_args=dict(proxies=proxies))
Now we can get the price of any symbol:
scraper.get_result_exact('https://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.
Another example: Say we want to scrape the about text, number of stars and the link to issues of Github repo pages:
from autoscraper import AutoScraper
url = 'https://github.com/alirezamika/autoscraper'
wanted_list = ['A Smart, Automatic, Fast and Lightweight Web Scraper for Python', '2.5k', 'https://github.com/alirezamika/autoscraper/issues']
scraper = AutoScraper()
scraper.build(url, wanted_list)
Simple, right?
Saving the model
We can now save the built model to use it later. To save:
scraper.save('yahoo-finance')
And to load:
scraper.load('yahoo-finance')
Tutorials
Issues
Feel free to open an issue if you have any problem using the module.
Support the project
Happy Coding ♥️