jobs_scraper

jobs_scraper is a simple job postings scraper for the website Indeed, it is written in Python and is based on the requests and BeautifulSoup libraries.

Installation

Run the following to install the package:

pip install jobs_scraper

Usage

To use jobs_scraper you need to create a new JobsScraper object and provide the following attributes to its constructor:

• country: prefix country.
• position: job position.
• location: job location.
• pages: number of pages to be scraped.

from jobs_scraper import JobsScraper

# Let's create a new JobsScraper object and perform the scraping for a given query.
scraper = JobsScraper(country="nl", position="Data Engineer", location="Amsterdam", pages=3)
df = scraper.scrape()

In this way, the first three pages for the example query "Data Engineer" based in "Amsterdam" on the Dutch version of the portal Indeed get scraped. The scrape method returns a Pandas dataframe, therefore it is possible to export it into a csv file.

Additional Parameters

• max_delay: bearing in mind that this package is meant only for educational purposes, a delay in the requests can be provided. By setting max_delay in the constructor, every job posting will be randomly scraped in an interval between 0 and max_delay seconds.

  scraper = JobsScraper(country="...", position="...", location="...", pages=..., max_delay=5)
  

• full_urls: since most of the scraped job urls are pretty long, the returned Pandas dataframe will truncate them, making it not simple to access. Setting full_urls to True, the scraped urls will not be truncated.

  scraper = JobsScraper(country="...", position="...", location="...", pages=..., full_urls=True)
  

TODO

• Add rotating proxies to prevent the scraper from being blocked once too many requests are sent.