save old answer for not use too much money
This commit is contained in:
feder-cr
parent
3c09856232
commit
a6d1d9fe42
@ -28,27 +28,23 @@ class LinkedInEasyApplier:
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self.set_old_answers = set_old_answers
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self.gpt_answerer = gpt_answerer
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self.resume_generator_manager = resume_generator_manager
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self.questions_data = []
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self.all_data = self._load_questions_from_json()
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def _load_questions_from_json(self) -> List[dict]:
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output_file = 'answers.json'
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try:
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# Leggi i dati esistenti dal file
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try:
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with open(output_file, 'r') as f:
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try:
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all_data = json.load(f)
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if not isinstance(all_data, list):
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data = json.load(f)
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if not isinstance(data, list):
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raise ValueError("JSON file format is incorrect. Expected a list of questions.")
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except json.JSONDecodeError:
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# Se il file è vuoto o non contiene JSON valido, inizializza come lista vuota
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all_data = []
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data = []
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except FileNotFoundError:
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# Se il file non esiste, inizializza come lista vuota
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all_data = []
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return all_data
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data = []
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return data
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except Exception:
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tb_str = traceback.format_exc()
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raise Exception(f"Error loading questions data from JSON file: \nTraceback:\n{tb_str}")
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@ -245,13 +241,22 @@ class LinkedInEasyApplier:
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if radios:
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question_text = section.text.lower()
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options = [radio.text.lower() for radio in radios]
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existing_answer = None
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for item in self.all_data:
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if self._sanitize_text(question_text) in item['question'] and item['type'] == 'radio':
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existing_answer = item
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break
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if existing_answer:
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self._select_radio(radios, existing_answer['answer'])
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return True
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answer = self.gpt_answerer.answer_question_from_options(question_text, options)
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self._select_radio(radios, answer)
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self._save_questions_to_json({'type': 'radio', 'question': question_text, 'answer': answer})
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self._select_radio(radios, answer)
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return True
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return False
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def _find_and_handle_textbox_question(self, section: WebElement) -> bool:
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text_fields = section.find_elements(By.TAG_NAME, 'input') + section.find_elements(By.TAG_NAME, 'textarea')
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if text_fields:
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@ -259,13 +264,23 @@ class LinkedInEasyApplier:
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question_text = section.find_element(By.TAG_NAME, 'label').text.lower()
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is_numeric = self._is_numeric_field(text_field)
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if is_numeric:
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answer = self.gpt_answerer.answer_question_numeric(question_text)
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question_type = 'numeric'
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answer = self.gpt_answerer.answer_question_numeric(question_text)
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else:
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answer = self.gpt_answerer.answer_question_textual_wide_range(question_text)
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question_type = 'textbox'
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self._enter_text(text_field, answer)
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answer = self.gpt_answerer.answer_question_textual_wide_range(question_text)
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existing_answer = None
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for item in self.all_data:
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if item['question'] == self._sanitize_text(question_text) and item['type'] == question_type:
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existing_answer = item
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break
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if existing_answer:
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self._enter_text(text_field, existing_answer['answer'])
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return True
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self._save_questions_to_json({'type': question_type, 'question': question_text, 'answer': answer})
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self._enter_text(text_field, answer)
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return True
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return False
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@ -273,9 +288,22 @@ class LinkedInEasyApplier:
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date_fields = section.find_elements(By.CLASS_NAME, 'artdeco-datepicker__input ')
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if date_fields:
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date_field = date_fields[0]
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question_text = section.text.lower()
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answer_date = self.gpt_answerer.answer_question_date()
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self._enter_text(date_field, answer_date.strftime("%Y-%m-%d"))
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self._save_questions_to_json({'type': 'date', 'question': section.text.lower(), 'answer': answer_date.strftime("%Y-%m-%d")})
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answer_text = answer_date.strftime("%Y-%m-%d")
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existing_answer = None
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for item in self.all_data:
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if self._sanitize_text(question_text) in item['question'] and item['type'] == 'date':
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existing_answer = item
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break
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if existing_answer:
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self._enter_text(date_field, existing_answer['answer'])
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return True
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self._save_questions_to_json({'type': 'date', 'question': question_text, 'answer': answer_text})
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self._enter_text(date_field, answer_text)
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return True
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return False
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@ -287,9 +315,19 @@ class LinkedInEasyApplier:
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if dropdown:
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select = Select(dropdown)
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options = [option.text for option in select.options]
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existing_answer = None
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for item in self.all_data:
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if self._sanitize_text(question_text) in item['question'] and item['type'] == 'dropdown':
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existing_answer = item
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break
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if existing_answer:
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self._select_dropdown_option(dropdown, existing_answer['answer'])
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return True
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answer = self.gpt_answerer.answer_question_from_options(question_text, options)
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self._select_dropdown_option(dropdown, answer)
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self._save_questions_to_json({'type': 'dropdown', 'question': question_text, 'answer': answer})
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self._select_dropdown_option(dropdown, answer)
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return True
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except Exception:
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return False
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@ -323,22 +361,21 @@ class LinkedInEasyApplier:
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try:
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with open(output_file, 'r') as f:
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try:
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all_data = json.load(f)
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if not isinstance(all_data, list):
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data = json.load(f)
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if not isinstance(data, list):
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raise ValueError("JSON file format is incorrect. Expected a list of questions.")
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except json.JSONDecodeError:
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all_data = []
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data = []
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except FileNotFoundError:
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all_data = []
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all_data.append(question_data)
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data = []
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data.append(question_data)
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with open(output_file, 'w') as f:
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json.dump(all_data, f, indent=4)
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json.dump(data, f, indent=4)
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except Exception:
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tb_str = traceback.format_exc()
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raise Exception(f"Error saving questions data to JSON file: \nTraceback:\n{tb_str}")
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def _sanitize_text(self, text: str) -> str:
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sanitized_text = text.lower()
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sanitized_text = sanitized_text.strip()
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