linkedIn_auto_jobs_applier_with_AI/main.py

import re
from pathlib import Path
import yaml
from selenium import webdriver
from selenium.webdriver.chrome.service import Service as ChromeService
from webdriver_manager.chrome import ChromeDriverManager
import click

from utils import chromeBrowserOptions
from gpt import GPTAnswerer
from linkedIn_authenticator import LinkedInAuthenticator
from linkedIn_bot_facade import LinkedInBotFacade
from linkedIn_job_manager import LinkedInJobManager
from resume import Resume

class ConfigError(Exception):
    """Custom exception for configuration errors."""
    pass

class ConfigValidator:
    @staticmethod
    def validate_email(email: str) -> bool:
        email_regex = r'^[a-zA-Z0-9._%+-]+@[a-zA-Z0-9.-]+\.[a-zA-Z]{2,}$'
        return re.match(email_regex, email) is not None

    @staticmethod
    def validate_config(config_yaml_path: Path) -> dict:
        try:
            with open(config_yaml_path, 'r') as stream:
                parameters = yaml.safe_load(stream)
        except yaml.YAMLError as exc:
            raise ConfigError(f"Error reading config file: {exc}")
        except FileNotFoundError:
            raise ConfigError(f"Config file not found: {config_yaml_path}")

        mandatory_params = [
            'remote', 'experienceLevel',
            'jobTypes', 'date', 'positions', 'locations', 'distance'
        ]

        for param in mandatory_params:
            if param not in parameters:
                raise ConfigError(f"Missing parameter in config file: {param}")

        if not isinstance(parameters['remote'], bool):
            raise ConfigError("'remote' must be a boolean value.")

        experience_level = parameters.get('experienceLevel', {})
        job_types = parameters.get('jobTypes', {})
        date = parameters.get('date', {})

        if not experience_level or not any(experience_level.values()):
            raise ConfigError("At least one experience level must be selected.")
        if not job_types or not any(job_types.values()):
            raise ConfigError("At least one job type must be selected.")
        if not date or not any(date.values()):
            raise ConfigError("At least one date filter must be selected.")

        approved_distances = {0, 5, 10, 25, 50, 100}
        if parameters['distance'] not in approved_distances:
            raise ConfigError(f"Invalid distance value. Must be one of: {approved_distances}")
        if not parameters['positions']:
            raise ConfigError("'positions' list cannot be empty.")
        if not parameters['locations']:
            raise ConfigError("'locations' list cannot be empty.")
        return parameters

    @staticmethod
    def validate_secrets(secrets_yaml_path: Path) -> tuple:
        try:
            with open(secrets_yaml_path, 'r') as stream:
                secrets = yaml.safe_load(stream)
        except yaml.YAMLError as exc:
            raise ConfigError(f"Error reading secrets file: {exc}")
        except FileNotFoundError:
            raise ConfigError(f"Secrets file not found: {secrets_yaml_path}")

        mandatory_secrets = ['email', 'password', 'openai_api_key']

        for secret in mandatory_secrets:
            if secret not in secrets:
                raise ConfigError(f"Missing secret: {secret}")
           
        if not ConfigValidator.validate_email(secrets['email']):
            raise ConfigError("Invalid email format in secrets file.")
        if not secrets['password']:
            raise ConfigError("Password cannot be empty in secrets file.")
        if not secrets['openai_api_key']:
            raise ConfigError("OpenAI API key cannot be empty in secrets file.")

        return secrets['email'], str(secrets['password']), secrets['openai_api_key']

class FileManager:
    @staticmethod
    def find_file(name_containing: str, with_extension: str, at_path: Path) -> Path:
        for file in at_path.iterdir():
            if name_containing.lower() in file.name.lower() and file.suffix.lower() == with_extension.lower():
                return file
        return None

    @staticmethod
    def validate_data_folder(app_data_folder: Path) -> tuple:
        if not app_data_folder.exists() or not app_data_folder.is_dir():
            raise FileNotFoundError(f"Data folder not found: {app_data_folder}")

        secrets_file = app_data_folder / 'secrets.yaml'
        config_file = app_data_folder / 'config.yaml'
        plain_text_resume_file = app_data_folder / 'plain_text_resume.yaml'
        
        missing_files = []
        if not config_file.exists():
            missing_files.append('config.yaml')
        if not plain_text_resume_file.exists():
            missing_files.append('plain_text_resume.yaml')
        
        if missing_files:
            raise FileNotFoundError(f"Missing files in the data folder: {', '.join(missing_files)}")
        
        output_folder = app_data_folder / 'output'
        output_folder.mkdir(exist_ok=True)
        return secrets_file, config_file, plain_text_resume_file, output_folder

    @staticmethod
    def file_paths_to_dict(resume_file: Path | None, plain_text_resume_file: Path) -> dict:
        if not plain_text_resume_file.exists():
            raise FileNotFoundError(f"Plain text resume file not found: {plain_text_resume_file}")
        
        result = {'plainTextResume': plain_text_resume_file}
        
        if resume_file is not None:
            if not resume_file.exists():
                raise FileNotFoundError(f"Resume file not found: {resume_file}")
            result['resume'] = resume_file
        
        return result

def init_browser():
    try:
        options = chromeBrowserOptions()
        service = ChromeService(ChromeDriverManager().install())
        return webdriver.Chrome(service=service, options=options)
    except Exception as e:
        raise RuntimeError(f"Failed to initialize browser: {str(e)}")

def create_and_run_bot(email: str, password: str, parameters: dict, openai_api_key: str):
    try:
        browser = init_browser()
        login_component = LinkedInAuthenticator(browser)
        apply_component = LinkedInJobManager(browser)
        gpt_answerer_component = GPTAnswerer(openai_api_key)

        with open(parameters['uploads']['plainTextResume'], "r") as file:
            plain_text_resume_file = file.read()
        
        resume_object = Resume(plain_text_resume_file)
        bot = LinkedInBotFacade(login_component, apply_component)
        bot.set_secrets(email, password)
        bot.set_resume(resume_object)
        bot.set_gpt_answerer(gpt_answerer_component)
        bot.set_parameters(parameters)
        bot.start_login()
        bot.start_apply()
    except Exception as e:
        raise RuntimeError(f"Error running the bot: {str(e)}")

@click.command()
@click.option('--resume', type=click.Path(exists=True, file_okay=True, dir_okay=False, path_type=Path), help="Path to the resume PDF file")
def main(resume: Path = None):
    try:
        data_folder = Path("data_folder")
        secrets_file, config_file, plain_text_resume_file, output_folder = FileManager.validate_data_folder(data_folder)
        parameters = ConfigValidator.validate_config(config_file)
        email, password, openai_api_key = ConfigValidator.validate_secrets(secrets_file)
        parameters['uploads'] = FileManager.file_paths_to_dict(resume, plain_text_resume_file)
        parameters['outputFileDirectory'] = output_folder

        create_and_run_bot(email, password, parameters, openai_api_key)
    except ConfigError as ce:
        print(f"Configuration error: {str(ce)}")
    except FileNotFoundError as fnf:
        print(f"File not found: {str(fnf)}")
    except RuntimeError as re:
        print(f"Runtime error: {str(re)}")
    except Exception as e:
        print(f"An unexpected error occurred: {str(e)}")

if __name__ == "__main__":
    main()