''' Author: Sai Vignesh Golla LinkedIn: https://www.linkedin.com/in/saivigneshgolla/ Copyright (c) 2024-2026 Sai Vignesh Golla License: MIT License https://opensource.org/license/mit GitHub: https://github.com/GodsScion/Auto_job_applier_linkedIn Support me: https://github.com/sponsors/GodsScion version: 26.01.20.5.08 ''' ###################################################### LINKEDIN SEARCH PREFERENCES ###################################################### # These Sentences are Searched in LinkedIn # Enter your search terms inside '[ ]' with quotes ' "searching title" ' for each search followed by comma ', ' Eg: ["Software Engineer", "Software Developer", "Selenium Developer"] search_terms = [ "Data Analyst", "IT Specialist" , "technical consultant", "Network engineer"] # Search location, this will be filled in "City, state, or zip code" search box. If left empty as "", tool will not fill it. search_location = "United States" # Some valid examples: "", "United States", "India", "Chicago, Illinois, United States", "90001, Los Angeles, California, United States", "Bengaluru, Karnataka, India", etc. # After how many number of applications in current search should the bot switch to next search? switch_number = 15 # Only numbers greater than 0... Don't put in quotes # Do you want to randomize the search order for search_terms? randomize_search_order = False # True of False, Note: True or False are case-sensitive # >>>>>>>>>>> Job Search Filters <<<<<<<<<<< ''' You could set your preferences or leave them as empty to not select options except for 'True or False' options. Below are some valid examples for leaving them empty: This is below format: QUESTION = VALID_ANSWER ## Examples of how to leave them empty. Note that True or False options cannot be left empty! * question_1 = "" # answer1, answer2, answer3, etc. * question_2 = [] # (multiple select) * question_3 = [] # (dynamic multiple select) ## Some valid examples of how to answer questions: * question_1 = "answer1" # "answer1", "answer2", "answer3" or ("" to not select). Answers are case sensitive. * question_2 = ["answer1", "answer2"] # (multiple select) "answer1", "answer2", "answer3" or ([] to not select). Note that answers must be in [] and are case sensitive. * question_3 = ["answer1", "Random AnswER"] # (dynamic multiple select) "answer1", "answer2", "answer3" or ([] to not select). Note that answers must be in [] and need not match the available options. ''' sort_by = "Most recent" # "Most recent", "Most relevant" or ("" to not select) date_posted = "Past week" # "Any time", "Past month", "Past week", "Past 24 hours" or ("" to not select) salary = "60,000+" # "$40,000+", "$60,000+", "$80,000+", "$100,000+", "$120,000+", "$140,000+", "$160,000+", "$180,000+", "$200,000+" easy_apply_only = True # True or False, Note: True or False are case-sensitive experience_level = ["Entry level", "Associate"] # (multiple select) "Internship", "Entry level", "Associate", "Mid-Senior level", "Director", "Executive" job_type = ["Full-time", "Part-time", "Contract", "Temporary"] # (multiple select) "Full-time", "Part-time", "Contract", "Temporary", "Volunteer", "Internship", "Other" on_site = ["On-site", "Remote", "Hybrid"] # (multiple select) "On-site", "Remote", "Hybrid" companies = [] # (dynamic multiple select) make sure the name you type in list exactly matches with the company name you're looking for, including capitals. # Eg: "7-eleven", "Google","X, the moonshot factory","YouTube","CapitalG","Adometry (acquired by Google)","Meta","Apple","Byte Dance","Netflix", "Snowflake","Mineral.ai","Microsoft","JP Morgan","Barclays","Visa","American Express", "Snap Inc", "JPMorgan Chase & Co.", "Tata Consultancy Services", "Recruiting from Scratch", "Epic", and so on... location = [] # (dynamic multiple select) industry = [] # (dynamic multiple select) job_function = [] # (dynamic multiple select) job_titles = [] # (dynamic multiple select) benefits = [] # (dynamic multiple select) commitments = [] # (dynamic multiple select) under_10_applicants = False # True or False, Note: True or False are case-sensitive in_your_network = False # True or False, Note: True or False are case-sensitive fair_chance_employer = False # True or False, Note: True or False are case-sensitive ## >>>>>>>>>>> RELATED SETTING <<<<<<<<<<< # Pause after applying filters to let you modify the search results and filters? pause_after_filters = True # True or False, Note: True or False are case-sensitive ## ## >>>>>>>>>>> SKIP IRRELEVANT JOBS <<<<<<<<<<< # Avoid applying to these companies, and companies with these bad words in their 'About Company' section... about_company_bad_words = ["Crossover"] # (dynamic multiple search) or leave empty as []. Ex: ["Staffing", "Recruiting", "Name of Company you don't want to apply to"] # Skip checking for `about_company_bad_words` for these companies if they have these good words in their 'About Company' section... [Exceptions, For example, I want to apply to "Robert Half" although it's a staffing company] about_company_good_words = [] # (dynamic multiple search) or leave empty as []. Ex: ["Robert Half", "Dice"] # Avoid applying to these companies if they have these bad words in their 'Job Description' section... (In development) bad_words = ["No C2C", "No Corp2Corp", ".NET", "Embedded Programming", "PHP", "Ruby", "CNC"] # (dynamic multiple search) or leave empty as []. Case Insensitive. Ex: ["word_1", "phrase 1", "word word", "polygraph", "US Citizenship", "Security Clearance"] # Do you have an active Security Clearance? (True for Yes and False for No) security_clearance = False # True or False, Note: True or False are case-sensitive # Do you have a Masters degree? (True for Yes and False for No). If True, the tool will apply to jobs containing the word 'master' in their job description and if it's experience required <= current_experience + 2 and current_experience is not set as -1. did_masters = False # True or False, Note: True or False are case-sensitive # Avoid applying to jobs if their required experience is above your current_experience. (Set value as -1 if you want to apply to all ignoring their required experience...) current_experience = 4 # Integers > -2 (Ex: -1, 0, 1, 2, 3, 4...) ## ############################################################################################################ ''' THANK YOU for using my tool 😊! Wishing you the best in your job hunt 🙌🏻! Sharing is caring! If you found this tool helpful, please share it with your peers 🥺. Your support keeps this project alive. Support my work on . Together, we can help more job seekers. As an independent developer, I pour my heart and soul into creating tools like this, driven by the genuine desire to make a positive impact. Your support, whether through donations big or small or simply spreading the word, means the world to me and helps keep this project alive and thriving. Gratefully yours 🙏🏻, Sai Vignesh Golla ''' # --- Load user settings saved by the local control panel (user_config.json). # --- No-op if that file is absent: values fall back to the defaults above. from config import _overrides as _o _o.apply(__name__, globals()) ############################################################################################################