LinkedIn Easy Apply Bot

repository·master·Indexed 22 days ago

https://github.com/nicolomantini/linkedin-easy-apply-bot

A Python-based automation tool for the LinkedIn 'Easy Apply' job application process. It allows users to automate applications based on specified positions, locations, and credentials via a config.yaml file, supporting custom file uploads for resumes, cover letters, and photos.

Tokens
651
Snippets
4
Records
4
Agent score
28%

What's inside linkedin-easy-apply-bot

  1. Configure the config.yaml file

    master

    Before running the bot, you must populate the config.yaml file with your LinkedIn credentials, job search preferences, and file paths.

    Important Security Note: After editing your config.yaml, save the file but do not commit it to version control to avoid leaking your credentials.

    username: # Insert your username here
    password: # Insert your password here
    phone_number: #Insert your phone number
    
    positions:
    - # positions you want to search for
    - # Another position you want to search for
    
    locations:
    - # Location you want to search for
    - # A second location you want to search in 
    
    salary: #yearly salary requirement 
    rate: #hourly rate requirement 
    
    uploads:
     Resume: # PATH TO Resume 
     Cover Letter: # PATH TO cover letter
     Photo: # PATH TO photo
    
    output_filename:
    - # PATH TO OUTPUT FILE (default output.csv)
    
    blacklist:
    - # Company names you want to ignore
  2. Configure file uploads in config.yaml

    master

    The uploads section in config.yaml allows you to specify paths for files like resumes, cover letters, and photos.

    • You can list an unlimited number of files.
    • The bot attempts to match the titles of the input boxes on LinkedIn with the keys provided in the uploads section.
    • Critical Syntax Rule: When defining keys in the uploads section, do not use dashes (-) in the file_key:file_paths mapping.
    uploads:
     Resume: /path/to/resume.pdf
     Cover Letter: /path/to/cover_letter.pdf
     Photo: /path/to/photo.jpg