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https://github.com/christabor/job_scraper

[NOT MAINTAINED] Job/Occupation data scraping tool that uses scrapy and pyquery
https://github.com/christabor/job_scraper

careerbuilder jobs onetonline pyquery scraper scrapy

Last synced: 2 months ago
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[NOT MAINTAINED] Job/Occupation data scraping tool that uses scrapy and pyquery

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README 

        
jobScraper

==========



Scraping tool that uses scrapy, pyquery and more

**What can it do?**

With the CareerBuilder scaper, I was able to execute a very large dataset of urls and automatically process them via command line. The tool will run a given set of urls, follow those, crawl each child page, and dump the results into JSON format. So, give A-Z, you will get all job categories from A-Z, with all job listings, and all job listing details, as JSON -- a very large dataset indeed!



With the Onet scraper, I scraped the entirety of Onet's job categories, then automatically, and recursively, scrape all category job pages. It took several hours with respectful request settings, but I was still able to both scrape, save to json, and load via Mongo **1,073 job types** and detailed information for each!



## Current Scrapers



#### CareerBuilder



Scrapes all categories and jobs from CareerBuilder.com. The details can be inconsistent for specific jobs, since the site HTML structure for each job page is unique for each company, making it very inconsistent and harder to parse.



#### OnetOnline



Scrapes all categories and occupation types form OnetOnline.org. This scraper

is the preferred one, since the site structure is more consistent and job data is more detailed. This site does not offer listings however, whereas CareerBuilder does. These can be use together to get a more comprehensive look at the job landscape.



## Command line structure



While the makefile provides some commands to quickly run scrapy jobs, the `run.py` file provides all command line access. All helper code for interacting with the user is provided here.



Each scraper job provides its own class for dealing with command line parsing of the structured data that was scraped. The general idea is that large JSON datasets are downloaded once, then parsed by the CLI and traversed directly, allowing programmatic access to the raw JSON itself, for future use.



## Persistence



By default, jobScraper is setup to handle storage to Mongo, as well as the default json flatfile. These can be used interchangeably, and a few helper scripts have been added for munging and backfilling data into mongo. The run script also allows navigating the downloaded json files and using them as options for the command line tool. The idea is to allow moving between raw json files, command line, and high-level persistence like Mongo.



## More...



I'll probably add some D3js visualizations once I've fine tuned it all and figured out exactly what I want to do with it. It's mostly a project with no clear vision, but I have been slowly tweaking it to become a pretty respectable scraper for all things job related.