Skip to main content

Package for automatically applying to relevant jobs on popular job boards.

Project description

speedapply

Package for automatically applying to relevant jobs on popular job boards.

This package is designed to crawl job boards like Monster, LinkedIn, and Indeed and automatically apply for jobs that you want. As of now only Monster is supported and only Speed Apply jobs are applied to. Further functionality needs to be added. speedapply uses selenium to traverse these web pages.

Usage

  1. Install using pip
$ pip install speedapply

In addition to the python package requirements, speedapply requires a selenium-compatible webdriver (e.g. chromedriver).

  1. Create a new folder to house the apply bot
$ python -m speedapply new_bot

or

$ speedapply new_bot
  1. Edit new_bot/settings.py to choose jobs and locations you want.
# new_bot/settings.py
...
# job titles
TITLES = [
    'Entry Level Software Engineer',
    'Data Engineer',
    'Machine Learning Engineer'
]

# job locations
LOCATIONS = [
    'New York, Ny',
    'Atlanta, GA',
    'Los Angeles, CA'
]
...
  1. Set environment variables for your username and password that get accessed by the bot in new_bot/bots.py. For example for monster.com:
$ export MONSTER_USERNAME="..." MONSTER_PASSWORD="..."
# new_bot/bots.py
import os

from speedapply.bots import ApplyBot
from speedapply.sites import Monster


monster_bot = ApplyBot(
    site=Monster,
    auth=(
        os.environ['MONSTER_USERNAME'],
        os.environ['MONSTER_PASSWORD']
    )
)
  1. Import the bots and settings and run the start function in new_bot/run.py.
# new_bot/run.py
import bots
import settings
from speedapply import start

if __name__ == "__main__":
    start(bots, settings)
$ python new_bot/run.py

This will begin applying to each job title in each location on each job board specified.

Leave it running and easily apply to hundreds of jobs per day!

Development

There are many improvements that can be made:

  • bots for more job boards
  • faster loading and filtering of jobs (possibly from APIs instead of web-scraping)
  • multiple drivers for quicker applying
  • better logging of jobs applied to

Project details


Download files

Download the file for your platform. If you're not sure which to choose, learn more about installing packages.

Source Distribution

speedapply-0.0.1.tar.gz (5.6 kB view details)

Uploaded Source

Built Distribution

speedapply-0.0.1-py3-none-any.whl (6.3 kB view details)

Uploaded Python 3

File details

Details for the file speedapply-0.0.1.tar.gz.

File metadata

  • Download URL: speedapply-0.0.1.tar.gz
  • Upload date:
  • Size: 5.6 kB
  • Tags: Source
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/3.1.1 pkginfo/1.5.0.1 requests/2.22.0 setuptools/45.1.0 requests-toolbelt/0.9.1 tqdm/4.42.1 CPython/3.8.1

File hashes

Hashes for speedapply-0.0.1.tar.gz
Algorithm Hash digest
SHA256 f90662b63f4be23d57d356589410060c9372a2730de41d1fed93696c846f1f25
MD5 4d4bed9e2d087c1de74b269706f5ef38
BLAKE2b-256 967bbf33e260de2106cf910ea96accf49acc6359759f78ee7df30b04e87a3d9b

See more details on using hashes here.

File details

Details for the file speedapply-0.0.1-py3-none-any.whl.

File metadata

  • Download URL: speedapply-0.0.1-py3-none-any.whl
  • Upload date:
  • Size: 6.3 kB
  • Tags: Python 3
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/3.1.1 pkginfo/1.5.0.1 requests/2.22.0 setuptools/45.1.0 requests-toolbelt/0.9.1 tqdm/4.42.1 CPython/3.8.1

File hashes

Hashes for speedapply-0.0.1-py3-none-any.whl
Algorithm Hash digest
SHA256 72ac8a6dbdc18d57deee06bd31207c7ce4b44e7aa19720f8a16c2e5c56f296ef
MD5 17a8faf209e2bc012e59f2887380e183
BLAKE2b-256 7ed9bfcba477f96659392bee68c95bfa3cb137f42db60c10fb0af01a90c994da

See more details on using hashes here.

Supported by

AWS AWS Cloud computing and Security Sponsor Datadog Datadog Monitoring Fastly Fastly CDN Google Google Download Analytics Microsoft Microsoft PSF Sponsor Pingdom Pingdom Monitoring Sentry Sentry Error logging StatusPage StatusPage Status page