add logs and some bugs fixes

src/gpt.py

@@ -12,20 +12,65 @@ from langchain_core.prompt_values import StringPromptValue
 from langchain_core.prompts import ChatPromptTemplate
 from langchain_openai import ChatOpenAI
 from Levenshtein import distance
+import time
+from functools import wraps
+from openai import RateLimitError, OpenAIError, APIError
+
 
 import src.strings as strings
+from src.utils import logger
 
 load_dotenv()
 
+# Global timestamp for rate limiting
+last_call_time = 0
+
+
+def global_rate_limiter(min_interval):
+    def decorator(func):
+        @wraps(func)
+        def wrapper(*args, **kwargs):
+            global last_call_time
+            elapsed = time.time() - last_call_time
+            if elapsed < min_interval:
+                logger.debug("Rate limit hit, sleeping for %s seconds", min_interval - elapsed)
+                time.sleep(min_interval - elapsed)
+            last_call_time = time.time()
+            return func(*args, **kwargs)
+
+        return wrapper
+
+    return decorator
+
+def parse_wait_time_from_error_message(error_message: str) -> int:
+    logger.debug("Parsing wait time from error message: %s", error_message)
+    match = re.search(r"Please try again in (\d+)([smhd])", error_message)
+    if match:
+        value, unit = int(match.group(1)), match.group(2)
+        logger.debug("Extracted wait time: %d %s", value, unit)
+        if unit == 's':
+            return value
+        elif unit == 'm':
+            return value * 60
+        elif unit == 'h':
+            return value * 3600
+        elif unit == 'd':
+            return value * 86400
+    logger.debug("Default wait time applied: 30 seconds")
+    return 30  # По умолчанию ждать 30 секунд, если не удалось разобрать время
+
 
 class LLMLogger:
     
     def __init__(self, llm: ChatOpenAI):
         self.llm = llm
+        logger.debug("LLMLogger initialized with LLM: %s", llm)
 
     @staticmethod
     def log_request(prompts, parsed_reply: Dict[str, Dict]):
+        logger.debug("Logging request with prompts: %s", prompts)
         calls_log = os.path.join(Path("data_folder/output"), "open_ai_calls.json")
+
         if isinstance(prompts, StringPromptValue):
             prompts = prompts.text
         elif isinstance(prompts, Dict):
@@ -41,6 +86,7 @@ class LLMLogger:
             }
 
         current_time = datetime.now().strftime("%Y-%m-%d %H:%M:%S")
+        logger.debug("Current time: %s", current_time)
 
         # Extract token usage details from the response
         token_usage = parsed_reply["usage_metadata"]
@@ -48,7 +94,8 @@ class LLMLogger:
         input_tokens = token_usage["input_tokens"]
         total_tokens = token_usage["total_tokens"]
 
-        # Extract model details from the response
+        logger.debug("Token usage - Input: %d, Output: %d, Total: %d", input_tokens, output_tokens, total_tokens)
+
         model_name = parsed_reply["response_metadata"]["model_name"]
         prompt_price_per_token = 0.00000015
         completion_price_per_token = 0.0000006
@@ -58,7 +105,8 @@ class LLMLogger:
             output_tokens * completion_price_per_token
         )
 
-        # Create a log entry with all relevant information
+        logger.debug("Total cost calculated: %f", total_cost)
+
         log_entry = {
             "model": model_name,
             "time": current_time,
@@ -70,26 +118,41 @@ class LLMLogger:
             "total_cost": total_cost,
         }
 
-        # Write the log entry to the log file in JSON format
+        logger.debug("Log entry created: %s", log_entry)
+
         with open(calls_log, "a", encoding="utf-8") as f:
             json_string = json.dumps(log_entry, ensure_ascii=False, indent=4)
             f.write(json_string + "\n")
+            logger.debug("Log entry written to file: %s", calls_log)
 
 
 class LoggerChatModel:
 
     def __init__(self, llm: ChatOpenAI):
         self.llm = llm
+        logger.debug("LoggerChatModel initialized with LLM: %s", llm)
 
     def __call__(self, messages: List[Dict[str, str]]) -> str:
-        # Call the LLM with the provided messages and log the response.
+        logger.debug("Calling LoggerChatModel with messages: %s", messages)
+        while True:
+            try:
+                # Попытка вызвать модель
                 reply = self.llm(messages)
+                logger.debug("Model reply received: %s", reply)
                 parsed_reply = self.parse_llmresult(reply)
                 LLMLogger.log_request(prompts=messages, parsed_reply=parsed_reply)
                 return reply
+            except RateLimitError as err:
+                # Handle RateLimitError
+                wait_time = self.parse_wait_time_from_error_message(str(err))
+                logger.warning("Rate limit exceeded. Waiting for %d seconds before retrying...", wait_time)
+                time.sleep(wait_time)
+            except Exception as e:
+                logger.error("Unexpected error occurred: %s", str(e))
+                raise
 
     def parse_llmresult(self, llmresult: AIMessage) -> Dict[str, Dict]:
-        # Parse the LLM result into a structured format.
+        logger.debug("Parsing LLM result: %s", llmresult)
         content = llmresult.content
         response_metadata = llmresult.response_metadata
         id_ = llmresult.id
@@ -109,61 +172,93 @@ class LoggerChatModel:
                 "total_tokens": usage_metadata.get("total_tokens", 0),
             },
         }
+        logger.debug("Parsed LLM result: %s", parsed_result)
         return parsed_result
 
+    def parse_wait_time_from_error_message(self, error_message: str) -> int:
+        logger.debug("Parsing wait time from error message: %s", error_message)
+        match = re.search(r"Please try again in (\d+)([smhd])", error_message)
+        if match:
+            value, unit = match.groups()
+            value = int(value)
+            logger.debug("Extracted wait time: %d %s", value, unit)
+            if unit == "s":
+                return value
+            elif unit == "m":
+                return value * 60
+            elif unit == "h":
+                return value * 3600
+            elif unit == "d":
+                return value * 86400
+        logger.debug("Default wait time applied: 30 seconds")
+        return 30
+
 
 class GPTAnswerer:
     def __init__(self, openai_api_key):
         self.llm_cheap = LoggerChatModel(
             ChatOpenAI(model_name="gpt-4o-mini", openai_api_key=openai_api_key, temperature=0.4)
         )
+        logger.debug("GPTAnswerer initialized with API key")
+
     @property
     def job_description(self):
         return self.job.description
 
     @staticmethod
     def find_best_match(text: str, options: list[str]) -> str:
+        logger.debug("Finding best match for text: '%s' in options: %s", text, options)
         distances = [
             (option, distance(text.lower(), option.lower())) for option in options
         ]
         best_option = min(distances, key=lambda x: x[1])[0]
+        logger.debug("Best match found: %s", best_option)
         return best_option
 
     @staticmethod
     def _remove_placeholders(text: str) -> str:
+        logger.debug("Removing placeholders from text: %s", text)
         text = text.replace("PLACEHOLDER", "")
         return text.strip()
 
     @staticmethod
     def _preprocess_template_string(template: str) -> str:
-        # Preprocess a template string to remove unnecessary indentation.
+        logger.debug("Preprocessing template string")
         return textwrap.dedent(template)
 
     def set_resume(self, resume):
+        logger.debug("Setting resume: %s", resume)
         self.resume = resume
 
     def set_job(self, job):
+        logger.debug("Setting job: %s", job)
         self.job = job
         self.job.set_summarize_job_description(self.summarize_job_description(self.job.description))
 
     def set_job_application_profile(self, job_application_profile):
+        logger.debug("Setting job application profile: %s", job_application_profile)
         self.job_application_profile = job_application_profile
 
+    @global_rate_limiter(25)
     def summarize_job_description(self, text: str) -> str:
+        logger.debug("Summarizing job description: %s", text)
         strings.summarize_prompt_template = self._preprocess_template_string(
             strings.summarize_prompt_template
         )
         prompt = ChatPromptTemplate.from_template(strings.summarize_prompt_template)
         chain = prompt | self.llm_cheap | StrOutputParser()
         output = chain.invoke({"text": text})
+        logger.debug("Summary generated: %s", output)
         return output
             
     def _create_chain(self, template: str):
+        logger.debug("Creating chain with template: %s", template)
         prompt = ChatPromptTemplate.from_template(template)
         return prompt | self.llm_cheap | StrOutputParser()
 
+    @global_rate_limiter(25)
     def answer_question_textual_wide_range(self, question: str) -> str:
-        # Define chains for each section of the resume
+        logger.debug("Answering textual question: %s", question)
         chains = {
             "personal_information": self._create_chain(strings.personal_information_template),
             "self_identification": self._create_chain(strings.self_identification_template),
@@ -270,47 +365,66 @@ class GPTAnswerer:
         prompt = ChatPromptTemplate.from_template(section_prompt)
         chain = prompt | self.llm_cheap | StrOutputParser()
         output = chain.invoke({"question": question})
+        logger.debug("Section determined from question: %s", output)
         section_name = output.lower().replace(" ", "_")
         if section_name == "cover_letter":
             chain = chains.get(section_name)
             output = chain.invoke({"resume": self.resume, "job_description": self.job_description})
+            logger.debug("Cover letter generated: %s", output)
             return output
         resume_section = getattr(self.resume, section_name, None) or getattr(self.job_application_profile, section_name, None)
         if resume_section is None:
+            logger.error("Section '%s' not found in either resume or job_application_profile.", section_name)
             raise ValueError(f"Section '{section_name}' not found in either resume or job_application_profile.")
         chain = chains.get(section_name)
         if chain is None:
+            logger.error("Chain not defined for section '%s'", section_name)
             raise ValueError(f"Chain not defined for section '{section_name}'")
-        return chain.invoke({"resume_section": resume_section, "question": question})
+        output = chain.invoke({"resume_section": resume_section, "question": question})
+        logger.debug("Question answered: %s", output)
+        return output
 
+    @global_rate_limiter(25)
     def answer_question_numeric(self, question: str, default_experience: int = 3) -> int:
+        logger.debug("Answering numeric question: %s", question)
         func_template = self._preprocess_template_string(strings.numeric_question_template)
         prompt = ChatPromptTemplate.from_template(func_template)
         chain = prompt | self.llm_cheap | StrOutputParser()
         output_str = chain.invoke({"resume_educations": self.resume.education_details,"resume_jobs": self.resume.experience_details,"resume_projects": self.resume.projects , "question": question})
+        logger.debug("Raw output for numeric question: %s", output_str)
         try:
             output = self.extract_number_from_string(output_str)
+            logger.debug("Extracted number: %d", output)
         except ValueError:
+            logger.warning("Failed to extract number, using default experience: %d", default_experience)
             output = default_experience
         return output
 
     def extract_number_from_string(self, output_str):
+        logger.debug("Extracting number from string: %s", output_str)
         numbers = re.findall(r"\d+", output_str)
         if numbers:
+            logger.debug("Numbers found: %s", numbers)
             return int(numbers[0])
         else:
+            logger.error("No numbers found in the string")
             raise ValueError("No numbers found in the string")
 
+    @global_rate_limiter(25)
     def answer_question_from_options(self, question: str, options: list[str]) -> str:
+        logger.debug("Answering question from options: %s", question)
         func_template = self._preprocess_template_string(strings.options_template)
         prompt = ChatPromptTemplate.from_template(func_template)
         chain = prompt | self.llm_cheap | StrOutputParser()
         output_str = chain.invoke({"resume": self.resume, "question": question, "options": options})
+        logger.debug("Raw output for options question: %s", output_str)
         best_option = self.find_best_match(output_str, options)
+        logger.debug("Best option determined: %s", best_option)
         return best_option
 
+    @global_rate_limiter(25)
     def resume_or_cover(self, phrase: str) -> str:
-        # Define the prompt template
+        logger.debug("Determining if phrase refers to resume or cover letter: %s", phrase)
         prompt_template = """
         Given the following phrase, respond with only 'resume' if the phrase is about a resume, or 'cover' if it's about a cover letter. Do not provide any additional information or explanations.
         
@@ -319,6 +433,7 @@ class GPTAnswerer:
         prompt = ChatPromptTemplate.from_template(prompt_template)
         chain = prompt | self.llm_cheap | StrOutputParser()
         response = chain.invoke({"phrase": phrase})
+        logger.debug("Response for resume_or_cover: %s", response)
         if "resume" in response:
             return "resume"
         elif "cover" in response:

src/job.py

@@ -1,5 +1,8 @@
 from dataclasses import dataclass
 
+from src.utils import logger
+
+
 @dataclass
 class Job:
     title: str
@@ -13,18 +16,22 @@ class Job:
     recruiter_link: str = ""
 
     def set_summarize_job_description(self, summarize_job_description):
+        logger.debug("Setting summarized job description: %s", summarize_job_description)
         self.summarize_job_description = summarize_job_description
 
     def set_job_description(self, description):
+        logger.debug("Setting job description: %s", description)
         self.description = description
 
     def set_recruiter_link(self, recruiter_link):
+        logger.debug("Setting recruiter link: %s", recruiter_link)
         self.recruiter_link = recruiter_link
 
     def formatted_job_information(self):
         """
         Formats the job information as a markdown string.
         """
+        logger.debug("Formatting job information for job: %s at %s", self.title, self.company)
         job_information = f"""
         # Job Description
         ## Job Information 
@@ -36,4 +43,6 @@ class Job:
         ## Description
         {self.description or 'No description provided.'}
         """
-        return job_information.strip()
+        formatted_information = job_information.strip()
+        logger.debug("Formatted job information: %s", formatted_information)
+        return formatted_information

src/job_application_profile.py

@@ -2,6 +2,9 @@ from dataclasses import dataclass
 from typing import Dict, List
 import yaml
 
+from src.utils import logger
+
+
 @dataclass
 class SelfIdentification:
     gender: str
@@ -47,86 +50,122 @@ class JobApplicationProfile:
     salary_expectations: SalaryExpectations
 
     def __init__(self, yaml_str: str):
+        logger.debug("Initializing JobApplicationProfile with provided YAML string")
         try:
             data = yaml.safe_load(yaml_str)
+            logger.debug("YAML data successfully parsed: %s", data)
         except yaml.YAMLError as e:
+            logger.error("Error parsing YAML file: %s", e)
             raise ValueError("Error parsing YAML file.") from e
         except Exception as e:
+            logger.error("Unexpected error occurred while parsing the YAML file: %s", e)
             raise RuntimeError("An unexpected error occurred while parsing the YAML file.") from e
 
         if not isinstance(data, dict):
+            logger.error("YAML data must be a dictionary, received: %s", type(data))
             raise TypeError("YAML data must be a dictionary.")
 
         # Process self_identification
         try:
+            logger.debug("Processing self_identification")
             self.self_identification = SelfIdentification(**data['self_identification'])
+            logger.debug("self_identification processed: %s", self.self_identification)
         except KeyError as e:
+            logger.error("Required field %s is missing in self_identification data.", e)
             raise KeyError(f"Required field {e} is missing in self_identification data.") from e
         except TypeError as e:
+            logger.error("Error in self_identification data: %s", e)
             raise TypeError(f"Error in self_identification data: {e}") from e
         except AttributeError as e:
+            logger.error("Attribute error in self_identification processing: %s", e)
             raise AttributeError("Attribute error in self_identification processing.") from e
         except Exception as e:
+            logger.error("An unexpected error occurred while processing self_identification: %s", e)
             raise RuntimeError("An unexpected error occurred while processing self_identification.") from e
 
         # Process legal_authorization
         try:
+            logger.debug("Processing legal_authorization")
             self.legal_authorization = LegalAuthorization(**data['legal_authorization'])
+            logger.debug("legal_authorization processed: %s", self.legal_authorization)
         except KeyError as e:
+            logger.error("Required field %s is missing in legal_authorization data.", e)
             raise KeyError(f"Required field {e} is missing in legal_authorization data.") from e
         except TypeError as e:
+            logger.error("Error in legal_authorization data: %s", e)
             raise TypeError(f"Error in legal_authorization data: {e}") from e
         except AttributeError as e:
+            logger.error("Attribute error in legal_authorization processing: %s", e)
             raise AttributeError("Attribute error in legal_authorization processing.") from e
         except Exception as e:
+            logger.error("An unexpected error occurred while processing legal_authorization: %s", e)
             raise RuntimeError("An unexpected error occurred while processing legal_authorization.") from e
 
         # Process work_preferences
         try:
+            logger.debug("Processing work_preferences")
             self.work_preferences = WorkPreferences(**data['work_preferences'])
+            logger.debug("work_preferences processed: %s", self.work_preferences)
         except KeyError as e:
+            logger.error("Required field %s is missing in work_preferences data.", e)
             raise KeyError(f"Required field {e} is missing in work_preferences data.") from e
         except TypeError as e:
+            logger.error("Error in work_preferences data: %s", e)
             raise TypeError(f"Error in work_preferences data: {e}") from e
         except AttributeError as e:
+            logger.error("Attribute error in work_preferences processing: %s", e)
             raise AttributeError("Attribute error in work_preferences processing.") from e
         except Exception as e:
+            logger.error("An unexpected error occurred while processing work_preferences: %s", e)
             raise RuntimeError("An unexpected error occurred while processing work_preferences.") from e
 
         # Process availability
         try:
+            logger.debug("Processing availability")
             self.availability = Availability(**data['availability'])
+            logger.debug("availability processed: %s", self.availability)
         except KeyError as e:
+            logger.error("Required field %s is missing in availability data.", e)
             raise KeyError(f"Required field {e} is missing in availability data.") from e
         except TypeError as e:
+            logger.error("Error in availability data: %s", e)
             raise TypeError(f"Error in availability data: {e}") from e
         except AttributeError as e:
+            logger.error("Attribute error in availability processing: %s", e)
             raise AttributeError("Attribute error in availability processing.") from e
         except Exception as e:
+            logger.error("An unexpected error occurred while processing availability: %s", e)
             raise RuntimeError("An unexpected error occurred while processing availability.") from e
 
         # Process salary_expectations
         try:
+            logger.debug("Processing salary_expectations")
             self.salary_expectations = SalaryExpectations(**data['salary_expectations'])
+            logger.debug("salary_expectations processed: %s", self.salary_expectations)
         except KeyError as e:
+            logger.error("Required field %s is missing in salary_expectations data.", e)
             raise KeyError(f"Required field {e} is missing in salary_expectations data.") from e
         except TypeError as e:
+            logger.error("Error in salary_expectations data: %s", e)
             raise TypeError(f"Error in salary_expectations data: {e}") from e
         except AttributeError as e:
+            logger.error("Attribute error in salary_expectations processing: %s", e)
             raise AttributeError("Attribute error in salary_expectations processing.") from e
         except Exception as e:
+            logger.error("An unexpected error occurred while processing salary_expectations: %s", e)
             raise RuntimeError("An unexpected error occurred while processing salary_expectations.") from e
 
-        # Process additional fields
+        logger.debug("JobApplicationProfile initialization completed successfully.")
-
-
 
     def __str__(self):
+        logger.debug("Generating string representation of JobApplicationProfile")
         def format_dataclass(obj):
             return "\n".join(f"{field.name}: {getattr(obj, field.name)}" for field in obj.__dataclass_fields__.values())
 
-        return (f"Self Identification:\n{format_dataclass(self.self_identification)}\n\n"
+        formatted_str = (f"Self Identification:\n{format_dataclass(self.self_identification)}\n\n"
                          f"Legal Authorization:\n{format_dataclass(self.legal_authorization)}\n\n"
                          f"Work Preferences:\n{format_dataclass(self.work_preferences)}\n\n"
                          f"Availability: {self.availability.notice_period}\n\n"
                          f"Salary Expectations: {self.salary_expectations.salary_range_usd}\n\n")
+        logger.debug("String representation generated: %s", formatted_str)
+        return formatted_str

src/linkedIn_authenticator.py

@@ -1,77 +1,142 @@
+import random
 import time
 from selenium.common.exceptions import NoSuchElementException, TimeoutException
 from selenium.webdriver.common.by import By
 from selenium.webdriver.support.ui import WebDriverWait
 from selenium.webdriver.support import expected_conditions as EC
 
+from src.utils import logger
+
+
 class LinkedInAuthenticator:
     
     def __init__(self, driver=None):
         self.driver = driver
         self.email = ""
         self.password = ""
+        logger.debug("LinkedInAuthenticator initialized with driver: %s", driver)
 
     def set_secrets(self, email, password):
         self.email = email
         self.password = password
+        logger.debug("Secrets set with email: %s", email)
 
     def start(self):
-        print("Starting Chrome browser to log in to LinkedIn.")
+        logger.info("Starting Chrome browser to log in to LinkedIn.")
-        self.driver.get('https://www.linkedin.com')
+        self.driver.get('https://www.linkedin.com/feed')
         self.wait_for_page_load()
         if not self.is_logged_in():
             self.handle_login()
 
     def handle_login(self):
-        print("Navigating to the LinkedIn login page...")
+        logger.info("Navigating to the LinkedIn login page...")
         self.driver.get("https://www.linkedin.com/login")
         try:
             self.enter_credentials()
             self.submit_login_form()
-        except NoSuchElementException:
+        except NoSuchElementException as e:
-            print("Could not log in to LinkedIn. Please check your credentials.")
+            logger.error("Could not log in to LinkedIn. Element not found: %s", e)
-        time.sleep(35) #TODO fix better
+        time.sleep(random.uniform(3, 5))
         self.handle_security_check()
 
     def enter_credentials(self):
         try:
+            logger.debug("Entering credentials...")
             email_field = WebDriverWait(self.driver, 10).until(
                 EC.presence_of_element_located((By.ID, "username"))
             )
             email_field.send_keys(self.email)
+            logger.debug("Email entered: %s", self.email)
             password_field = self.driver.find_element(By.ID, "password")
             password_field.send_keys(self.password)
+            logger.debug("Password entered.")
         except TimeoutException:
+            logger.error("Login form not found. Aborting login.")
             print("Login form not found. Aborting login.")
 
     def submit_login_form(self):
         try:
+            logger.debug("Submitting login form...")
             login_button = self.driver.find_element(By.XPATH, '//button[@type="submit"]')
             login_button.click()
+            logger.debug("Login form submitted.")
         except NoSuchElementException:
+            logger.error("Login button not found. Please verify the page structure.")
             print("Login button not found. Please verify the page structure.")
 
     def handle_security_check(self):
         try:
+            logger.debug("Handling security check...")
             WebDriverWait(self.driver, 10).until(
                 EC.url_contains('https://www.linkedin.com/checkpoint/challengesV2/')
             )
+            logger.warning("Security checkpoint detected. Please complete the challenge.")
             print("Security checkpoint detected. Please complete the challenge.")
             WebDriverWait(self.driver, 300).until(
                 EC.url_contains('https://www.linkedin.com/feed/')
             )
+            logger.info("Security check completed")
             print("Security check completed")
         except TimeoutException:
+            logger.error("Security check not completed within the timeout.")
             print("Security check not completed. Please try again later.")
 
     def is_logged_in(self):
-        self.driver.get('https://www.linkedin.com/')
+        target_url = 'https://www.linkedin.com/feed'
-        return self.driver.current_url == 'https://www.linkedin.com/feed/'
+
+        # Navigate to the target URL if not already there
+        if self.driver.current_url != target_url:
+            logger.debug("Navigating to target URL: %s", target_url)
+            self.driver.get(target_url)
+
+        try:
+            # Increase the wait time for the page elements to load
+            logger.debug("Checking if user is logged in...")
+            WebDriverWait(self.driver, 10).until(
+                EC.presence_of_element_located((By.CLASS_NAME, 'share-box-feed-entry__trigger'))
+            )
+
+            # Check for the presence of the "Start a post" button
+            buttons = self.driver.find_elements(By.CLASS_NAME, 'share-box-feed-entry__trigger')
+            if any(button.text.strip() == 'Start a post' for button in buttons):
+                logger.info("User is already logged in.")
+
+                try:
+                    # Wait for the profile picture and name to load
+                    profile_img = WebDriverWait(self.driver, 10).until(
+                        EC.presence_of_element_located((By.XPATH, "//img[contains(@alt, 'Photo of')]"))
+                    )
+                    profile_name = WebDriverWait(self.driver, 10).until(
+                        EC.presence_of_element_located((By.XPATH, "//div[@class='t-16 t-black t-bold']"))
+                    )
+
+                    if profile_img and profile_name:
+                        logger.info("Profile picture found for user: %s", profile_name.text)
+                        return True
+                except NoSuchElementException:
+                    logger.warning("Profile picture or name not found.")
+                    print("Profile picture or name not found.")
+                    return False
+                except TimeoutException:
+                    logger.warning("Profile picture or name took too long to load.")
+                    print("Profile picture or name took too long to load.")
+                    return False
+
+        except TimeoutException:
+            logger.error("Page elements took too long to load or were not found.")
+            print("Page elements took too long to load or were not found.")
+            return False
+
+        return False
+
 
     def wait_for_page_load(self, timeout=10):
         try:
+            logger.debug("Waiting for page to load with timeout: %s seconds", timeout)
             WebDriverWait(self.driver, timeout).until(
                 lambda d: d.execute_script('return document.readyState') == 'complete'
             )
+            logger.debug("Page load completed.")
         except TimeoutException:
+            logger.error("Page load timed out.")
             print("Page load timed out.")

src/linkedIn_bot_facade.py

@@ -1,8 +1,13 @@
+from src.utils import logger
+
+
 class LinkedInBotState:
     def __init__(self):
+        logger.debug("Initializing LinkedInBotState")
         self.reset()
 
     def reset(self):
+        logger.debug("Resetting LinkedInBotState")
         self.credentials_set = False
         self.api_key_set = False
         self.job_application_profile_set = False
@@ -11,12 +16,16 @@ class LinkedInBotState:
         self.logged_in = False
 
     def validate_state(self, required_keys):
+        logger.debug("Validating LinkedInBotState with required keys: %s", required_keys)
         for key in required_keys:
             if not getattr(self, key):
+                logger.error("State validation failed: %s is not set", key)
                 raise ValueError(f"{key.replace('_', ' ').capitalize()} must be set before proceeding.")
+        logger.debug("State validation passed")
 
 class LinkedInBotFacade:
     def __init__(self, login_component, apply_component):
+        logger.debug("Initializing LinkedInBotFacade")
         self.login_component = login_component
         self.apply_component = apply_component
         self.state = LinkedInBotState()
@@ -27,47 +36,65 @@ class LinkedInBotFacade:
         self.parameters = None
 
     def set_job_application_profile_and_resume(self, job_application_profile, resume):
+        logger.debug("Setting job application profile and resume")
         self._validate_non_empty(job_application_profile, "Job application profile")
         self._validate_non_empty(resume, "Resume")
         self.job_application_profile = job_application_profile
         self.resume = resume
         self.state.job_application_profile_set = True
+        logger.debug("Job application profile and resume set successfully")
 
     def set_secrets(self, email, password):
+        logger.debug("Setting secrets: email and password")
         self._validate_non_empty(email, "Email")
         self._validate_non_empty(password, "Password")
         self.email = email
         self.password = password
         self.state.credentials_set = True
+        logger.debug("Secrets set successfully")
 
     def set_gpt_answerer_and_resume_generator(self, gpt_answerer_component, resume_generator_manager):
+        logger.debug("Setting GPT answerer and resume generator")
         self._ensure_job_profile_and_resume_set()
         gpt_answerer_component.set_job_application_profile(self.job_application_profile)
         gpt_answerer_component.set_resume(self.resume)
         self.apply_component.set_gpt_answerer(gpt_answerer_component)
         self.apply_component.set_resume_generator_manager(resume_generator_manager)
         self.state.gpt_answerer_set = True
+        logger.debug("GPT answerer and resume generator set successfully")
 
     def set_parameters(self, parameters):
+        logger.debug("Setting parameters")
         self._validate_non_empty(parameters, "Parameters")
         self.parameters = parameters
         self.apply_component.set_parameters(parameters)
         self.state.parameters_set = True
+        logger.debug("Parameters set successfully")
 
     def start_login(self):
+        logger.debug("Starting login process")
         self.state.validate_state(['credentials_set'])
         self.login_component.set_secrets(self.email, self.password)
         self.login_component.start()
         self.state.logged_in = True
+        logger.debug("Login process completed successfully")
 
     def start_apply(self):
+        logger.debug("Starting apply process")
         self.state.validate_state(['logged_in', 'job_application_profile_set', 'gpt_answerer_set', 'parameters_set'])
         self.apply_component.start_applying()
+        logger.debug("Apply process started successfully")
 
     def _validate_non_empty(self, value, name):
+        logger.debug("Validating that %s is not empty", name)
         if not value:
+            logger.error("Validation failed: %s is empty", name)
             raise ValueError(f"{name} cannot be empty.")
+        logger.debug("Validation passed for %s", name)
 
     def _ensure_job_profile_and_resume_set(self):
+        logger.debug("Ensuring job profile and resume are set")
         if not self.state.job_application_profile_set:
+            logger.error("Job application profile and resume are not set")
             raise ValueError("Job application profile and resume must be set before proceeding.")
+        logger.debug("Job profile and resume are set")

src/linkedIn_easy_applier.py

@@ -10,7 +10,7 @@ from datetime import date
 from typing import List, Optional, Any, Tuple
 from reportlab.lib.pagesizes import letter
 from reportlab.pdfgen import canvas
-from selenium.common.exceptions import NoSuchElementException
+from selenium.common.exceptions import NoSuchElementException, TimeoutException
 from selenium.webdriver.common.by import By
 from selenium.webdriver.common.keys import Keys
 from selenium.webdriver.remote.webelement import WebElement
@@ -18,9 +18,10 @@ from selenium.webdriver.support import expected_conditions as EC
 from selenium.webdriver.support.ui import Select, WebDriverWait
 from selenium.webdriver import ActionChains
 import src.utils as utils
-
+from src.utils import logger
 class LinkedInEasyApplier:
     def __init__(self, driver: Any, resume_dir: Optional[str], set_old_answers: List[Tuple[str, str, str]], gpt_answerer: Any, resume_generator_manager):
+        logger.debug("Initializing LinkedInEasyApplier")
         if resume_dir is None or not os.path.exists(resume_dir):
             resume_dir = None
         self.driver = driver
@@ -29,11 +30,11 @@ class LinkedInEasyApplier:
         self.gpt_answerer = gpt_answerer
         self.resume_generator_manager = resume_generator_manager
         self.all_data = self._load_questions_from_json()
-
+        logger.debug("LinkedInEasyApplier initialized successfully")
 
     def _load_questions_from_json(self) -> List[dict]:
         output_file = 'answers.json'
-        try:
+        logger.debug("Loading questions from JSON file: %s", output_file)
         try:
             with open(output_file, 'r') as f:
                 try:
@@ -41,16 +42,21 @@ class LinkedInEasyApplier:
                     if not isinstance(data, list):
                         raise ValueError("JSON file format is incorrect. Expected a list of questions.")
                 except json.JSONDecodeError:
+                    logger.error("JSON decoding failed")
                     data = []
-            except FileNotFoundError:
+            logger.debug("Questions loaded successfully from JSON")
-                data = []
             return data
+        except FileNotFoundError:
+            logger.warning("JSON file not found, returning empty list")
+            return []
         except Exception:
             tb_str = traceback.format_exc()
+            logger.error("Error loading questions data from JSON file: %s", tb_str)
             raise Exception(f"Error loading questions data from JSON file: \nTraceback:\n{tb_str}")
 
 
     def job_apply(self, job: Any):
+        logger.debug("Starting job application for job: %s", job)
         self.driver.get(job.link)
         time.sleep(random.uniform(3, 5))
         try:
@@ -61,15 +67,19 @@ class LinkedInEasyApplier:
             actions.move_to_element(easy_apply_button).click().perform()
             self.gpt_answerer.set_job(job)
             self._fill_application_form(job)
+            logger.debug("Job application process completed for job: %s", job)
         except Exception:
             tb_str = traceback.format_exc()
+            logger.error("Failed to apply to job: %s", tb_str)
             self._discard_application()
             raise Exception(f"Failed to apply to job! Original exception: \nTraceback:\n{tb_str}")
 
     def _find_easy_apply_button(self) -> WebElement:
+        logger.debug("Searching for 'Easy Apply' button")
         attempt = 0
         while attempt < 2:
             self._scroll_page()
+            try:
                 buttons = WebDriverWait(self.driver, 10).until(
                     EC.presence_of_all_elements_located(
                         (By.XPATH, '//button[contains(@class, "jobs-apply-button") and contains(., "Easy Apply")]')
@@ -82,58 +92,78 @@ class LinkedInEasyApplier:
                                 (By.XPATH, f'(//button[contains(@class, "jobs-apply-button") and contains(., "Easy Apply")])[{index + 1}]')
                             )
                         )
+                        logger.debug("Found and clicking 'Easy Apply' button")
                         return button
                     except Exception as e:
-                    pass
+                        logger.warning("Failed to click 'Easy Apply' button on attempt %d: %s", attempt + 1, e)
+            except TimeoutException:
+                logger.warning("Timeout while searching for 'Easy Apply' button")
+
             if attempt == 0:
+                logger.debug("Refreshing page to retry finding 'Easy Apply' button")
                 self.driver.refresh()
-                time.sleep(3)  
+                time.sleep(random.randint(3, 5))
             attempt += 1
+        logger.error("No clickable 'Easy Apply' button found after 2 attempts")
         raise Exception("No clickable 'Easy Apply' button found")
 
-
     def _get_job_description(self) -> str:
+        logger.debug("Getting job description")
+        try:
             try:
                 see_more_button = self.driver.find_element(By.XPATH, '//button[@aria-label="Click to see more description"]')
                 actions = ActionChains(self.driver)
                 actions.move_to_element(see_more_button).click().perform()
                 time.sleep(2)
+            except NoSuchElementException:
+                logger.debug("See more button not found, skipping")
+
             description = self.driver.find_element(By.CLASS_NAME, 'jobs-description-content__text').text
+            logger.debug("Job description retrieved successfully")
             return description
         except NoSuchElementException:
             tb_str = traceback.format_exc()
-            raise Exception("Job description 'See more' button not found: \nTraceback:\n{tb_str}")
+            logger.error("Job description not found: %s", tb_str)
+            raise Exception(f"Job description not found: \nTraceback:\n{tb_str}")
         except Exception:
             tb_str = traceback.format_exc()
+            logger.error("Error getting Job description: %s", tb_str)
             raise Exception(f"Error getting Job description: \nTraceback:\n{tb_str}")
 
-
     def _get_job_recruiter(self):
+        logger.debug("Getting job recruiter information")
         try:
             hiring_team_section = WebDriverWait(self.driver, 10).until(
                 EC.presence_of_element_located((By.XPATH, '//h2[text()="Meet the hiring team"]'))
             )
             recruiter_element = hiring_team_section.find_element(By.XPATH, './/following::a[contains(@href, "linkedin.com/in/")]')
             recruiter_link = recruiter_element.get_attribute('href')
+            logger.debug("Job recruiter link retrieved successfully")
             return recruiter_link
         except Exception as e:
+            logger.warning("Failed to retrieve recruiter information: %s", e)
             return ""
 
     def _scroll_page(self) -> None:
+        logger.debug("Scrolling the page")
         scrollable_element = self.driver.find_element(By.TAG_NAME, 'html')
         utils.scroll_slow(self.driver, scrollable_element, step=300, reverse=False)
         utils.scroll_slow(self.driver, scrollable_element, step=300, reverse=True)
 
     def _fill_application_form(self, job):
+        logger.debug("Filling out application form for job: %s", job)
         while True:
             self.fill_up(job)
             if self._next_or_submit():
+                logger.debug("Application form submitted")
                 break
 
     def _next_or_submit(self):
+        logger.debug("Clicking 'Next' or 'Submit' button")
         next_button = self.driver.find_element(By.CLASS_NAME, "artdeco-button--primary")
         button_text = next_button.text.lower()
         if 'submit application' in button_text:
+            logger.debug("Submit button found, submitting application")
             self._unfollow_company()
             time.sleep(random.uniform(1.5, 2.5))
             next_button.click()
@@ -146,70 +176,88 @@ class LinkedInEasyApplier:
 
     def _unfollow_company(self) -> None:
         try:
+            logger.debug("Unfollowing company")
             follow_checkbox = self.driver.find_element(
                 By.XPATH, "//label[contains(.,'to stay up to date with their page.')]")
             follow_checkbox.click()
         except Exception as e:
-            pass
+            logger.warning("Failed to unfollow company: %s", e)
 
     def _check_for_errors(self) -> None:
+        logger.debug("Checking for form errors")
         error_elements = self.driver.find_elements(By.CLASS_NAME, 'artdeco-inline-feedback--error')
         if error_elements:
+            logger.error("Form submission failed with errors: %s", [e.text for e in error_elements])
             raise Exception(f"Failed answering or file upload. {str([e.text for e in error_elements])}")
 
     def _discard_application(self) -> None:
+        logger.debug("Discarding application")
         try:
             self.driver.find_element(By.CLASS_NAME, 'artdeco-modal__dismiss').click()
             time.sleep(random.uniform(3, 5))
             self.driver.find_elements(By.CLASS_NAME, 'artdeco-modal__confirm-dialog-btn')[0].click()
             time.sleep(random.uniform(3, 5))
         except Exception as e:
-            pass
+            logger.warning("Failed to discard application: %s", e)
 
     def fill_up(self, job) -> None:
+        logger.debug("Filling up form sections for job: %s", job)
         easy_apply_content = self.driver.find_element(By.CLASS_NAME, 'jobs-easy-apply-content')
         pb4_elements = easy_apply_content.find_elements(By.CLASS_NAME, 'pb4')
         for element in pb4_elements:
             self._process_form_element(element, job)
         
     def _process_form_element(self, element: WebElement, job) -> None:
+        logger.debug("Processing form element")
         if self._is_upload_field(element):
             self._handle_upload_fields(element, job)
         else:
             self._fill_additional_questions()
 
     def _is_upload_field(self, element: WebElement) -> bool:
-        return bool(element.find_elements(By.XPATH, ".//input[@type='file']"))
+        is_upload = bool(element.find_elements(By.XPATH, ".//input[@type='file']"))
+        logger.debug("Element is upload field: %s", is_upload)
+        return is_upload
 
     def _handle_upload_fields(self, element: WebElement, job) -> None:
+        logger.debug("Handling upload fields")
         file_upload_elements = self.driver.find_elements(By.XPATH, "//input[@type='file']")
         for element in file_upload_elements:
             parent = element.find_element(By.XPATH, "..")
             self.driver.execute_script("arguments[0].classList.remove('hidden')", element)
             output = self.gpt_answerer.resume_or_cover(parent.text.lower())
             if 'resume' in output:
+                logger.debug("Uploading resume")
                 if self.resume_path is not None and self.resume_path.resolve().is_file():
                     element.send_keys(str(self.resume_path.resolve()))
                 else:
                     self._create_and_upload_resume(element, job)
             elif 'cover' in output:
+                logger.debug("Uploading cover letter")
                 self._create_and_upload_cover_letter(element)
 
     def _create_and_upload_resume(self, element, job):
+        logger.debug("Creating and uploading resume")
         folder_path = 'generated_cv'
         os.makedirs(folder_path, exist_ok=True)
         try:
-            file_path_pdf = os.path.join(folder_path, f"CV_{random.randint(0, 9999)}.pdf")
+            timestamp = int(time.time())
-            with open(file_path_pdf, "xb") as f:
+            file_path_pdf = os.path.join(folder_path, f"CV_{timestamp}.pdf")
+
+            with open(file_path_pdf, "xb") as f: # gjcvjn
                 f.write(base64.b64decode(self.resume_generator_manager.pdf_base64(job_description_text=job.description)))
+
             element.send_keys(os.path.abspath(file_path_pdf))
             job.pdf_path = os.path.abspath(file_path_pdf)
             time.sleep(2)
+            logger.debug("Resume created and uploaded successfully: %s", file_path_pdf)
         except Exception:
             tb_str = traceback.format_exc()
+            logger.error("Resume upload failed: %s", tb_str)
             raise Exception(f"Upload failed: \nTraceback:\n{tb_str}")
 
     def _create_and_upload_cover_letter(self, element: WebElement) -> None:
+        logger.debug("Creating and uploading cover letter")
         cover_letter = self.gpt_answerer.answer_question_textual_wide_range("Write a cover letter")
         with tempfile.NamedTemporaryFile(delete=False, suffix='.pdf') as temp_pdf_file:
             letter_path = temp_pdf_file.name
@@ -221,29 +269,38 @@ class LinkedInEasyApplier:
             c.drawText(text_object)
             c.save()
             element.send_keys(letter_path)
+            logger.debug("Cover letter created and uploaded successfully: %s", letter_path)
 
     def _fill_additional_questions(self) -> None:
+        logger.debug("Filling additional questions")
         form_sections = self.driver.find_elements(By.CLASS_NAME, 'jobs-easy-apply-form-section__grouping')
         for section in form_sections:
             self._process_form_section(section)
             
 
     def _process_form_section(self, section: WebElement) -> None:
+        logger.debug("Processing form section")
         if self._handle_terms_of_service(section):
+            logger.debug("Handled terms of service")
             return
         if self._find_and_handle_radio_question(section):
+            logger.debug("Handled radio question")
             return
         if self._find_and_handle_textbox_question(section):
+            logger.debug("Handled textbox question")
             return
         if self._find_and_handle_date_question(section):
+            logger.debug("Handled date question")
             return
         if self._find_and_handle_dropdown_question(section):
+            logger.debug("Handled dropdown question")
             return
 
     def _handle_terms_of_service(self, element: WebElement) -> bool:
         checkbox = element.find_elements(By.TAG_NAME, 'label')
         if checkbox and any(term in checkbox[0].text.lower() for term in ['terms of service', 'privacy policy', 'terms of use']):
             checkbox[0].click()
+            logger.debug("Clicked terms of service checkbox")
             return True
         return False
 
@@ -261,11 +318,13 @@ class LinkedInEasyApplier:
                     break
             if existing_answer:
                 self._select_radio(radios, existing_answer['answer'])
+                logger.debug("Selected existing radio answer")
                 return True
 
             answer = self.gpt_answerer.answer_question_from_options(question_text, options)
             self._save_questions_to_json({'type': 'radio', 'question': question_text, 'answer': answer})
             self._select_radio(radios, answer)
+            logger.debug("Selected new radio answer")
             return True
         return False
 
@@ -288,9 +347,11 @@ class LinkedInEasyApplier:
                     break
             if existing_answer:
                 self._enter_text(text_field, existing_answer['answer'])
+                logger.debug("Entered existing textbox answer")
                 return True
             self._save_questions_to_json({'type': question_type, 'question': question_text, 'answer': answer})
             self._enter_text(text_field, answer)
+            logger.debug("Entered new textbox answer")
             return True
         return False
 
@@ -310,10 +371,12 @@ class LinkedInEasyApplier:
                     break
             if existing_answer:
                 self._enter_text(date_field, existing_answer['answer'])
+                logger.debug("Entered existing date answer")
                 return True
 
             self._save_questions_to_json({'type': 'date', 'question': question_text, 'answer': answer_text})
             self._enter_text(date_field, answer_text)
+            logger.debug("Entered new date answer")
             return True
         return False
 
@@ -333,27 +396,31 @@ class LinkedInEasyApplier:
                         break
                 if existing_answer:
                     self._select_dropdown_option(dropdown, existing_answer['answer'])
+                    logger.debug("Selected existing dropdown answer")
                     return True
 
                 answer = self.gpt_answerer.answer_question_from_options(question_text, options)
                 self._save_questions_to_json({'type': 'dropdown', 'question': question_text, 'answer': answer})
                 self._select_dropdown_option(dropdown, answer)
+                logger.debug("Selected new dropdown answer")
                 return True
-        except Exception:
+        except Exception as e:
+            logger.warning("Failed to handle dropdown question: %s", e)
             return False
 
     def _is_numeric_field(self, field: WebElement) -> bool:
         field_type = field.get_attribute('type').lower()
-        if 'numeric' in field_type:
+        is_numeric = 'numeric' in field_type or ('id' in field.get_attribute("id") and 'numeric' in field.get_attribute("id"))
-            return True
+        logger.debug("Field is numeric: %s", is_numeric)
-        class_attribute = field.get_attribute("id")
+        return is_numeric
-        return class_attribute and 'numeric' in class_attribute
 
     def _enter_text(self, element: WebElement, text: str) -> None:
+        logger.debug("Entering text: %s", text)
         element.clear()
         element.send_keys(text)
 
     def _select_radio(self, radios: List[WebElement], answer: str) -> None:
+        logger.debug("Selecting radio option: %s", answer)
         for radio in radios:
             if answer in radio.text.lower():
                 radio.find_element(By.TAG_NAME, 'label').click()
@@ -361,12 +428,14 @@ class LinkedInEasyApplier:
         radios[-1].find_element(By.TAG_NAME, 'label').click()
 
     def _select_dropdown_option(self, element: WebElement, text: str) -> None:
+        logger.debug("Selecting dropdown option: %s", text)
         select = Select(element)
         select.select_by_visible_text(text)
 
     def _save_questions_to_json(self, question_data: dict) -> None:
         output_file = 'answers.json'
         question_data['question'] = self._sanitize_text(question_data['question'])
+        logger.debug("Saving question data to JSON: %s", question_data)
         try:
             try:
                 with open(output_file, 'r') as f:
@@ -375,23 +444,23 @@ class LinkedInEasyApplier:
                         if not isinstance(data, list):
                             raise ValueError("JSON file format is incorrect. Expected a list of questions.")
                     except json.JSONDecodeError:
+                        logger.error("JSON decoding failed")
                         data = []
             except FileNotFoundError:
+                logger.warning("JSON file not found, creating new file")
                 data = []
             data.append(question_data)
             with open(output_file, 'w') as f:
                 json.dump(data, f, indent=4)
+            logger.debug("Question data saved successfully to JSON")
         except Exception:
             tb_str = traceback.format_exc()
+            logger.error("Error saving questions data to JSON file: %s", tb_str)
             raise Exception(f"Error saving questions data to JSON file: \nTraceback:\n{tb_str}")
 
 
     def _sanitize_text(self, text: str) -> str:
-        sanitized_text = text.lower()
+        sanitized_text = text.lower().strip().replace('"', '').replace('\\', '')
-        sanitized_text = sanitized_text.strip()
+        sanitized_text = re.sub(r'[\x00-\x1F\x7F]', '', sanitized_text).replace('\n', ' ').replace('\r', '').rstrip(',')
-        sanitized_text = sanitized_text.replace('"', '')
+        logger.debug("Sanitized text: %s", sanitized_text)
-        sanitized_text = sanitized_text.replace('\\', '')
-        sanitized_text = re.sub(r'[\x00-\x1F\x7F]', '', sanitized_text)
-        sanitized_text = sanitized_text.replace('\n', ' ').replace('\r', '')
-        sanitized_text = sanitized_text.rstrip(',')
         return sanitized_text

src/linkedIn_job_manager.py

@@ -10,28 +10,39 @@ import src.utils as utils
 from src.job import Job
 from src.linkedIn_easy_applier import LinkedInEasyApplier
 import json
+from src.utils import logger
 
 
 class EnvironmentKeys:
     def __init__(self):
+        logger.debug("Initializing EnvironmentKeys")
         self.skip_apply = self._read_env_key_bool("SKIP_APPLY")
         self.disable_description_filter = self._read_env_key_bool("DISABLE_DESCRIPTION_FILTER")
+        logger.debug("EnvironmentKeys initialized: skip_apply=%s, disable_description_filter=%s",
+                     self.skip_apply, self.disable_description_filter)
 
     @staticmethod
     def _read_env_key(key: str) -> str:
-        return os.getenv(key, "")
+        value = os.getenv(key, "")
+        logger.debug("Read environment key %s: %s", key, value)
+        return value
 
     @staticmethod
     def _read_env_key_bool(key: str) -> bool:
-        return os.getenv(key) == "True"
+        value = os.getenv(key) == "True"
+        logger.debug("Read environment key %s as bool: %s", key, value)
+        return value
 
 class LinkedInJobManager:
     def __init__(self, driver):
+        logger.debug("Initializing LinkedInJobManager")
         self.driver = driver
         self.set_old_answers = set()
         self.easy_applier_component = None
+        logger.debug("LinkedInJobManager initialized successfully")
 
     def set_parameters(self, parameters):
+        logger.debug("Setting parameters for LinkedInJobManager")
         self.company_blacklist = parameters.get('companyBlacklist', []) or []
         self.title_blacklist = parameters.get('titleBlacklist', []) or []
         self.positions = parameters.get('positions', [])
@@ -39,33 +50,21 @@ class LinkedInJobManager:
         self.base_search_url = self.get_base_search_url(parameters)
         self.seen_jobs = []
         resume_path = parameters.get('uploads', {}).get('resume', None)
-        if resume_path is not None and Path(resume_path).exists():
+        self.resume_path = Path(resume_path) if resume_path and Path(resume_path).exists() else None
-            self.resume_path = Path(resume_path)
-        else:
-            self.resume_path = None
         self.output_file_directory = Path(parameters['outputFileDirectory'])
         self.env_config = EnvironmentKeys()
-        #self.old_question()
+        logger.debug("Parameters set successfully")
 
     def set_gpt_answerer(self, gpt_answerer):
+        logger.debug("Setting GPT answerer")
         self.gpt_answerer = gpt_answerer
 
     def set_resume_generator_manager(self, resume_generator_manager):
+        logger.debug("Setting resume generator manager")
         self.resume_generator_manager = resume_generator_manager
 
-    """ def old_question(self):
-        self.set_old_answers = {}
-        file_path = 'data_folder/output/old_Questions.csv'
-        if os.path.exists(file_path):
-            with open(file_path, 'r', newline='', encoding='utf-8', errors='ignore') as file:
-                csv_reader = csv.reader(file, delimiter=',', quotechar='"')
-                for row in csv_reader:
-                    if len(row) == 3:
-                        answer_type, question_text, answer = row
-                        self.set_old_answers[(answer_type.lower(), question_text.lower())] = answer"""
-
-
     def start_applying(self):
+        logger.debug("Starting job application process")
         self.easy_applier_component = LinkedInEasyApplier(self.driver, self.resume_path, self.set_old_answers, self.gpt_answerer, self.resume_generator_manager)
         searches = list(product(self.positions, self.locations))
         random.shuffle(searches)
@@ -86,30 +85,40 @@ class LinkedInJobManager:
                     self.next_job_page(position, location_url, job_page_number)
                     time.sleep(random.uniform(1.5, 3.5))
                     utils.printyellow("Starting the application process for this page...")
+                    try:
                         self.apply_jobs()
+                    except Exception as e:
+                        logger.error("Error during job application: %s", e)
+                        utils.printred(f"Error during job application: {e}")
+                        continue
                     utils.printyellow("Applying to jobs on this page has been completed!")
 
                     time_left = minimum_page_time - time.time()
                     if time_left > 0:
                         utils.printyellow(f"Sleeping for {time_left} seconds.")
+                        logger.debug("Sleeping for %d seconds", time_left)
                         time.sleep(time_left)
                         minimum_page_time = time.time() + minimum_time
                     if page_sleep % 5 == 0:
                         sleep_time = random.randint(5, 34)
                         utils.printyellow(f"Sleeping for {sleep_time / 60} minutes.")
+                        logger.debug("Sleeping for %d seconds", sleep_time)
                         time.sleep(sleep_time)
                         page_sleep += 1
-            except Exception:
+            except Exception as e:
-                traceback.format_exc()
+                logger.error("Unexpected error during job search: %s", e)
-                pass
+                utils.printred(f"Unexpected error: {e}")
+                continue
             time_left = minimum_page_time - time.time()
             if time_left > 0:
                 utils.printyellow(f"Sleeping for {time_left} seconds.")
+                logger.debug("Sleeping for %d seconds", time_left)
                 time.sleep(time_left)
                 minimum_page_time = time.time() + minimum_time
             if page_sleep % 5 == 0:
                 sleep_time = random.randint(50, 90)
                 utils.printyellow(f"Sleeping for {sleep_time / 60} minutes.")
+                logger.debug("Sleeping for %d seconds", sleep_time)
                 time.sleep(sleep_time)
                 page_sleep += 1
 
@@ -117,32 +126,40 @@ class LinkedInJobManager:
         try:
             no_jobs_element = self.driver.find_element(By.CLASS_NAME, 'jobs-search-two-pane__no-results-banner--expand')
             if 'No matching jobs found' in no_jobs_element.text or 'unfortunately, things aren' in self.driver.page_source.lower():
-                raise Exception("No more jobs on this page")
+                utils.printyellow("No matching jobs found on this page, moving to next.")
+                logger.debug("No matching jobs found on this page, skipping")
+                return  # Выход из метода, если нет больше подходящих вакансий
         except NoSuchElementException:
-            pass
+            pass  # Если элемент не найден, просто продолжаем
 
         job_results = self.driver.find_element(By.CLASS_NAME, "jobs-search-results-list")
         utils.scroll_slow(self.driver, job_results)
         utils.scroll_slow(self.driver, job_results, step=300, reverse=True)
         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')
         if not job_list_elements:
-            raise Exception("No job class elements found on page")
+            utils.printyellow("No job class elements found on page, moving to next page.")
+            logger.debug("No job class elements found on page, skipping")
+            return  # Выход из метода, если нет вакансий на странице
         job_list = [Job(*self.extract_job_information_from_tile(job_element)) for job_element in job_list_elements] 
         for job in job_list:
             if self.is_blacklisted(job.title, job.company, job.link):
                 utils.printyellow(f"Blacklisted {job.title} at {job.company}, skipping...")
+                logger.debug("Job blacklisted: %s at %s", job.title, job.company)
                 self.write_to_file(job, "skipped")
                 continue
             try:
                 if job.apply_method not in {"Continue", "Applied", "Apply"}:
                     self.easy_applier_component.job_apply(job)
                     self.write_to_file(job, "success")
+                    logger.debug("Applied to job: %s at %s", job.title, job.company)
             except Exception as e:
-                utils.printred(traceback.format_exc())
+                logger.error("Failed to apply for %s at %s: %s", job.title, job.company, e)
+                utils.printred(f"Failed to apply for {job.title} at {job.company}: {e}")
                 self.write_to_file(job, "failed")
                 continue
         
     def write_to_file(self, job, file_name):
+        logger.debug("Writing job application result to file: %s", file_name)
         pdf_path = Path(job.pdf_path).resolve()
         pdf_path = pdf_path.as_uri()
         data = {
@@ -157,18 +174,22 @@ class LinkedInJobManager:
         if not file_path.exists():
             with open(file_path, 'w', encoding='utf-8') as f:
                 json.dump([data], f, indent=4)
+                logger.debug("Job data written to new file: %s", file_path)
         else:
             with open(file_path, 'r+', encoding='utf-8') as f:
                 try:
                     existing_data = json.load(f)
                 except json.JSONDecodeError:
+                    logger.error("JSON decode error in file: %s", file_path)
                     existing_data = []
                 existing_data.append(data)
                 f.seek(0)
                 json.dump(existing_data, f, indent=4)
                 f.truncate()
+                logger.debug("Job data appended to existing file: %s", file_path)
 
     def get_base_search_url(self, parameters):
+        logger.debug("Constructing base search URL")
         url_parts = []
         if parameters['remote']:
             url_parts.append("f_CF=f_WRA")
@@ -188,33 +209,45 @@ class LinkedInJobManager:
         date_param = next((v for k, v in date_mapping.items() if parameters.get('date', {}).get(k)), "")
         url_parts.append("f_LF=f_AL")  # Easy Apply
         base_url = "&".join(url_parts)
-        return f"?{base_url}{date_param}"
+        full_url = f"?{base_url}{date_param}"
+        logger.debug("Base search URL constructed: %s", full_url)
+        return full_url
     
     def next_job_page(self, position, location, job_page):
+        logger.debug("Navigating to next job page: %s in %s, page %d", position, location, job_page)
         self.driver.get(f"https://www.linkedin.com/jobs/search/{self.base_search_url}&keywords={position}{location}&start={job_page * 25}")
     
     def extract_job_information_from_tile(self, job_tile):
+        logger.debug("Extracting job information from tile")
         job_title, company, job_location, apply_method, link = "", "", "", "", ""
         try:
             job_title = job_tile.find_element(By.CLASS_NAME, 'job-card-list__title').text
             link = job_tile.find_element(By.CLASS_NAME, 'job-card-list__title').get_attribute('href').split('?')[0]
             company = job_tile.find_element(By.CLASS_NAME, 'job-card-container__primary-description').text
-        except:
+            logger.debug("Job information extracted: %s at %s", job_title, company)
-            pass
+        except NoSuchElementException:
+            utils.printyellow("Some job information (title, link, or company) is missing.")
+            logger.warning("Some job information (title, link, or company) is missing.")
         try:
             job_location = job_tile.find_element(By.CLASS_NAME, 'job-card-container__metadata-item').text
-        except:
+        except NoSuchElementException:
-            pass
+            utils.printyellow("Job location is missing.")
+            logger.warning("Job location is missing.")
         try:
             apply_method = job_tile.find_element(By.CLASS_NAME, 'job-card-container__apply-method').text
-        except:
+        except NoSuchElementException:
-            apply_method = "Applied"
+            apply_method = "Applied"  # Подразумеваем, что вакансия уже подана
+            utils.printyellow("Apply method not found, assuming 'Applied'.")
+            logger.warning("Apply method not found, assuming 'Applied'.")
 
         return job_title, company, job_location, link, apply_method
     
     def is_blacklisted(self, job_title, company, link):
+        logger.debug("Checking if job is blacklisted: %s at %s", job_title, company)
         job_title_words = job_title.lower().split(' ')
         title_blacklisted = any(word in job_title_words for word in self.title_blacklist)
         company_blacklisted = company.strip().lower() in (word.strip().lower() for word in self.company_blacklist)
         link_seen = link in self.seen_jobs
-        return title_blacklisted or company_blacklisted or link_seen
+        is_blacklisted = title_blacklisted or company_blacklisted or link_seen
+        logger.debug("Job blacklisted status: %s", is_blacklisted)
+        return is_blacklisted

src/utils.py

@@ -4,76 +4,97 @@ import time
 
 from selenium import webdriver
 
+import logging
+
+# Настройка логирования
+logging.basicConfig(level=logging.DEBUG, format='%(asctime)s - %(name)s - %(levelname)s - %(message)s')
+logger = logging.getLogger(__name__)
+
+
 chromeProfilePath = os.path.join(os.getcwd(), "chrome_profile", "linkedin_profile")
 
 def ensure_chrome_profile():
+    logger.debug("Ensuring Chrome profile exists at path: %s", chromeProfilePath)
     profile_dir = os.path.dirname(chromeProfilePath)
     if not os.path.exists(profile_dir):
         os.makedirs(profile_dir)
+        logger.debug("Created directory for Chrome profile: %s", profile_dir)
     if not os.path.exists(chromeProfilePath):
         os.makedirs(chromeProfilePath)
+        logger.debug("Created Chrome profile directory: %s", chromeProfilePath)
     return chromeProfilePath
 
 def is_scrollable(element):
     scroll_height = element.get_attribute("scrollHeight")
     client_height = element.get_attribute("clientHeight")
-    return int(scroll_height) > int(client_height)
+    scrollable = int(scroll_height) > int(client_height)
+    logger.debug("Element scrollable check: scrollHeight=%s, clientHeight=%s, scrollable=%s", scroll_height, client_height, scrollable)
+    return scrollable
 
 def scroll_slow(driver, scrollable_element, start=0, end=3600, step=100, reverse=False):
+    logger.debug("Starting slow scroll: start=%d, end=%d, step=%d, reverse=%s", start, end, step, reverse)
     if reverse:
         start, end = end, start
         step = -step
     if step == 0:
+        logger.error("Step value cannot be zero.")
         raise ValueError("Step cannot be zero.")
     script_scroll_to = "arguments[0].scrollTop = arguments[1];"
     try:
         if scrollable_element.is_displayed():
             if not is_scrollable(scrollable_element):
+                logger.warning("The element is not scrollable.")
                 print("The element is not scrollable.")
                 return
             if (step > 0 and start >= end) or (step < 0 and start <= end):
+                logger.warning("No scrolling will occur due to incorrect start/end values.")
                 print("No scrolling will occur due to incorrect start/end values.")
                 return        
             for position in range(start, end, step):
                 try:
                     driver.execute_script(script_scroll_to, scrollable_element, position)
+                    logger.debug("Scrolled to position: %d", position)
                 except Exception as e:
+                    logger.error("Error during scrolling: %s", e)
                     print(f"Error during scrolling: {e}")
-                time.sleep(random.uniform(1.0, 2.6))
+                time.sleep(random.uniform(1.0, 1.6))
             driver.execute_script(script_scroll_to, scrollable_element, end)
+            logger.debug("Scrolled to final position: %d", end)
             time.sleep(1)
         else:
+            logger.warning("The element is not visible.")
             print("The element is not visible.")
     except Exception as e:
+        logger.error("Exception occurred during scrolling: %s", e)
         print(f"Exception occurred: {e}")
 
 def chromeBrowserOptions():
+    logger.debug("Setting Chrome browser options")
     ensure_chrome_profile()
     options = webdriver.ChromeOptions()
-    options.add_argument("--start-maximized")  # Avvia il browser a schermo intero
+    options.add_argument("--start-maximized")
-    options.add_argument("--no-sandbox")  # Disabilita la sandboxing per migliorare le prestazioni
+    options.add_argument("--no-sandbox")
-    options.add_argument("--disable-dev-shm-usage")  # Utilizza una directory temporanea per la memoria condivisa
+    options.add_argument("--disable-dev-shm-usage")
-    options.add_argument("--ignore-certificate-errors")  # Ignora gli errori dei certificati SSL
+    options.add_argument("--ignore-certificate-errors")
-    options.add_argument("--disable-extensions")  # Disabilita le estensioni del browser
+    options.add_argument("--disable-extensions")
-    options.add_argument("--disable-gpu")  # Disabilita l'accelerazione GPU
+    options.add_argument("--disable-gpu")
-    options.add_argument("window-size=1200x800")  # Imposta la dimensione della finestra del browser
+    options.add_argument("window-size=1200x800")
-    options.add_argument("--disable-background-timer-throttling")  # Disabilita il throttling dei timer in background
+    options.add_argument("--disable-background-timer-throttling")
-    options.add_argument("--disable-backgrounding-occluded-windows")  # Disabilita la sospensione delle finestre occluse
+    options.add_argument("--disable-backgrounding-occluded-windows")
-    options.add_argument("--disable-translate")  # Disabilita il traduttore automatico
+    options.add_argument("--disable-translate")
-    options.add_argument("--disable-popup-blocking")  # Disabilita il blocco dei popup
+    options.add_argument("--disable-popup-blocking")
-    options.add_argument("--no-first-run")  # Disabilita la configurazione iniziale del browser
+    options.add_argument("--no-first-run")
-    options.add_argument("--no-default-browser-check")  # Disabilita il controllo del browser predefinito
+    options.add_argument("--no-default-browser-check")
-    options.add_argument("--disable-logging")  # Disabilita il logging
+    options.add_argument("--disable-logging")
-    options.add_argument("--disable-autofill")  # Disabilita l'autocompletamento dei moduli
+    options.add_argument("--disable-autofill")
-    options.add_argument("--disable-plugins")  # Disabilita i plugin del browser
+    options.add_argument("--disable-plugins")
-    options.add_argument("--disable-animations")  # Disabilita le animazioni
+    options.add_argument("--disable-animations")
-    options.add_argument("--disable-cache")  # Disabilita la cache 
+    options.add_argument("--disable-cache")
-    options.add_experimental_option("excludeSwitches", ["enable-automation", "enable-logging"])  # Esclude switch della modalità automatica e logging
+    options.add_experimental_option("excludeSwitches", ["enable-automation", "enable-logging"])
 
-    # Preferenze per contenuti
     prefs = {
-        "profile.default_content_setting_values.images": 2,  # Disabilita il caricamento delle immagini
+        "profile.default_content_setting_values.images": 2,
-        "profile.managed_default_content_settings.stylesheets": 2,  # Disabilita il caricamento dei fogli di stile
+        "profile.managed_default_content_settings.stylesheets": 2,
     }
     options.add_experimental_option("prefs", prefs)
 
@@ -82,22 +103,21 @@ def chromeBrowserOptions():
         profileDir = os.path.basename(chromeProfilePath)
         options.add_argument('--user-data-dir=' + initialPath)
         options.add_argument("--profile-directory=" + profileDir)
+        logger.debug("Using Chrome profile directory: %s", chromeProfilePath)
     else:
         options.add_argument("--incognito")
+        logger.debug("Using Chrome in incognito mode")
 
     return options
 
-
 def printred(text):
-    # Codice colore ANSI per il rosso
     RED = "\033[91m"
     RESET = "\033[0m"
-    # Stampa il testo in rosso
+    logger.debug("Printing text in red: %s", text)
     print(f"{RED}{text}{RESET}")
 
 def printyellow(text):
-    # Codice colore ANSI per il giallo
     YELLOW = "\033[93m"
     RESET = "\033[0m"
-    # Stampa il testo in giallo
+    logger.debug("Printing text in yellow: %s", text)
     print(f"{YELLOW}{text}{RESET}")