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as-scraper

Python library for scraping with Selenium.

  • 2.5.1
  • PyPI
  • Socket score

Maintainers
1

as-scraper

PyPI - Python Version PyPI - Downloads

Python library for scraping using Selenium

If you are looking for the library implemented inside airflow, go to https://github.com/Avila-Systems/as-scraper-airflow.

Installation

The as-scraper library uses Geckodriver (Firefox) for scraping with the Selenium library. In order to use it, you need to have an Geckodriver dependency. Check the selenium documentation for details about how to install the Firefox browser driver.

Usage

Creating a simple scraper

Lets say that we want to scrap yellowpages.com. Our target data would be the popular cities that we can find in the sitemap url.

Our output data will have two columns: name of the city and url which is linked to the city. For example, for Houston, we would want the following output:

nameurl
Houstonhttps://www.yellowpages.com/houston-tx

Declaring our Scraper Class

So first we create a scraper that extends from the Scraper class, and define the COLUMNS variable to ['name', 'url'].

Create the scrapers/yellowpages.py file and type the following code into it:

from as_scraper.scraper import Scraper


class YellowPagesScraper(Scraper):
    COLUMNS = ['name', 'url']

Deciding wether to load javascript or not

Now, there are two execution options when running scrapers. We can either load javascript which uses the Selenium library, or not load javascript and use the requests library for http requests.

For this example, let's go ahead and use the Selenium library. To configure this, simply add the following variable to your scraper:

from as_scraper.scraper import Scraper


class YellowPagesScraper(Scraper):
    COLUMNS = ['name', 'url']
    LOAD_JAVASCRIPT = True

Defining the scrape_handler

And the magic comes in the next step. We will define the scrape_handler method in our class, which will have the responsibility to scrape a given url and extract the data from it.

All scrapers must define the scrape_handler method.

from typing import Optional
from selenium.webdriver import Firefox
from selenium.webdriver.common.by import By
import pandas as pd
from as_scraper.scraper import Scraper


class YellowPagesScraper(Scraper):
    COLUMNS = ['name', 'url']
    LOAD_JAVASCRIPT = True

    def scrape_handler(self, url: str, html: Optional[str] = None, driver: Optional[Firefox] = None, **kwargs) -> pd.DataFrame:
        rows = []
        div_tag = driver.find_element(By.CLASS_NAME, "row-content")
        div_tag = div_tag.find_element(By.CLASS_NAME, "row")
        section_tags = div_tag.find_elements(By.TAG_NAME, "section")
        for section_tag in section_tags:
            a_tags = section_tag.find_elements(By.TAG_NAME, "a")
            for a_tag in a_tags:
                city_name = a_tag.text
                city_url = a_tag.get_attribute("href")
                rows.append({"name": city_name, "url": city_url})
        df = pd.DataFrame(rows, columns=self.COLUMNS)
        return df

Execution

Finally, to execute the scraper you must call the *execute method.

from typing import Optional
from selenium.webdriver import Firefox
from selenium.webdriver.common.by import By
import pandas as pd
from as_scraper.scraper import Scraper

class YellowPagesScraper(Scraper):
    COLUMNS = ['name', 'url']
    LOAD_JAVASCRIPT = True

    def scrape_handler(self, url: str, html: Optional[str] = None, driver: Optional[Firefox] = None, **kwargs) -> pd.DataFrame:
        rows = []
        div_tag = driver.find_element(By.CLASS_NAME, "row-content")
        div_tag = div_tag.find_element(By.CLASS_NAME, "row")
        section_tags = div_tag.find_elements(By.TAG_NAME, "section")
        for section_tag in section_tags:
            a_tags = section_tag.find_elements(By.TAG_NAME, "a")
            for a_tag in a_tags:
                city_name = a_tag.text
                city_url = a_tag.get_attribute("href")
                rows.append({"name": city_name, "url": city_url})
        df = pd.DataFrame(rows, columns=self.COLUMNS)
        return df

if __name__ == '__main__':
    urls = ['https://www.yellowpages.com/sitemap']
    scraper = YellowPagesScraper(urls)
    results, errors = scraper.execute()
    print(results)
    print(errors)

Now go ahead and run python scrapers/yellowpages.py. Have fun!

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