first commit v2
This commit is contained in:
feder-cr
parent
2dcd7943e8
commit
d8b7e7fda6
18 changed files with 663 additions and 1398 deletions
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@ -1,4 +1,3 @@
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import csv
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import os
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import random
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import time
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@ -10,6 +9,7 @@ from selenium.webdriver.common.by import By
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import utils
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from job import Job
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from linkedIn_easy_applier import LinkedInEasyApplier
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import json
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class EnvironmentKeys:
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@ -45,15 +45,15 @@ class LinkedInJobManager:
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self.resume_dir = None
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self.output_file_directory = Path(parameters['outputFileDirectory'])
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self.env_config = EnvironmentKeys()
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self.old_question()
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#self.old_question()
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def set_gpt_answerer(self, gpt_answerer):
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self.gpt_answerer = gpt_answerer
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def old_question(self):
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"""
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Load old answers from a CSV file into a dictionary.
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"""
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def set_resume_generator_manager(self, resume_generator_manager):
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self.resume_generator_manager = resume_generator_manager
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""" def old_question(self):
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self.set_old_answers = {}
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file_path = 'data_folder/output/old_Questions.csv'
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if os.path.exists(file_path):
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@ -62,13 +62,11 @@ class LinkedInJobManager:
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for row in csv_reader:
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if len(row) == 3:
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answer_type, question_text, answer = row
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self.set_old_answers[(answer_type.lower(), question_text.lower())] = answer
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self.set_old_answers[(answer_type.lower(), question_text.lower())] = answer"""
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def start_applying(self):
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self.easy_applier_component = LinkedInEasyApplier(
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self.driver, self.resume_dir, self.set_old_answers, self.gpt_answerer
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)
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self.easy_applier_component = LinkedInEasyApplier(self.driver, self.resume_dir, self.set_old_answers, self.gpt_answerer, self.resume_generator_manager)
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searches = list(product(self.positions, self.locations))
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random.shuffle(searches)
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page_sleep = 0
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@ -127,50 +125,50 @@ class LinkedInJobManager:
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job_results = self.driver.find_element(By.CLASS_NAME, "jobs-search-results-list")
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utils.scroll_slow(self.driver, job_results)
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utils.scroll_slow(self.driver, job_results, step=300, reverse=True)
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job_list_elements = self.driver.find_elements(By.CLASS_NAME, 'scaffold-layout__list-container')[0].find_elements(By.CLASS_NAME, 'jobs-search-results__list-item')
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if not job_list_elements:
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raise Exception("No job class elements found on page")
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job_list = [Job(*self.extract_job_information_from_tile(job_element)) for job_element in job_list_elements]
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job_list = [Job(*self.extract_job_information_from_tile(job_element)) for job_element in job_list_elements]
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for job in job_list:
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if self.is_blacklisted(job.title, job.company, job.link):
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utils.printyellow(f"Blacklisted {job.title} at {job.company}, skipping...")
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self.write_to_file(job.company, job.location, job.title, job.link, "skipped")
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self.write_to_file(job, "skipped")
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continue
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try:
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if job.apply_method not in {"Continue", "Applied", "Apply"}:
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self.easy_applier_component.job_apply(job)
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self.write_to_file(job, "success")
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except Exception as e:
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utils.printred(traceback.format_exc())
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self.write_to_file(job.company, job.location, job.title, job.link, "failed")
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continue
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self.write_to_file(job.company, job.location, job.title, job.link, "success")
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self.write_to_file(job, "failed")
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continue
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except Exception as e:
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traceback.format_exc()
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raise e
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def write_to_file(self, company, job_title, link, job_location, file_name):
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to_write = [company, job_title, link, job_location]
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file_path = self.output_file_directory / f"{file_name}.csv"
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with open(file_path, 'a', newline='', encoding='utf-8') as f:
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writer = csv.writer(f)
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writer.writerow(to_write)
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def record_gpt_answer(self, answer_type, question_text, gpt_response):
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to_write = [answer_type, question_text, gpt_response]
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file_path = self.output_file_directory / "registered_jobs.csv"
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try:
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with open(file_path, 'a', newline='', encoding='utf-8') as f:
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writer = csv.writer(f)
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writer.writerow(to_write)
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except Exception as e:
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utils.printred(f"Error writing registered job: {e}")
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utils.printred(f"Details: Answer type: {answer_type}, Question: {question_text}")
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def write_to_file(self, job, file_name):
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data = {
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"company": job.company,
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"job_title": job.title,
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"link": job.link,
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"job_location": job.location,
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"pdf_path": job.pdf_path
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}
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file_path = self.output_file_directory / f"{file_name}.json"
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if not file_path.exists():
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with open(file_path, 'w', encoding='utf-8') as f:
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json.dump([data], f, indent=4)
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else:
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with open(file_path, 'r+', encoding='utf-8') as f:
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try:
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existing_data = json.load(f)
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except json.JSONDecodeError:
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existing_data = []
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existing_data.append(data)
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f.seek(0)
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json.dump(existing_data, f, indent=4)
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f.truncate()
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def get_base_search_url(self, parameters):
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url_parts = []
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@ -205,12 +203,6 @@ class LinkedInJobManager:
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company = job_tile.find_element(By.CLASS_NAME, 'job-card-container__primary-description').text
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except:
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pass
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try:
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hiring_line = job_tile.find_element(By.XPATH, '//span[contains(.,\' is hiring for this\')]')
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hiring_line_text = hiring_line.text
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name_terminating_index = hiring_line_text.find(' is hiring for this')
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except:
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pass
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try:
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job_location = job_tile.find_element(By.CLASS_NAME, 'job-card-container__metadata-item').text
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except:
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