import streamlit as st import json def load_json_data(file_path): """Utility function to load JSON data from a specified file path.""" try: with open(file_path, 'r') as file: return json.load(file) except FileNotFoundError: st.error(f"File {file_path} not found. Please ensure data has been saved.") return None def display_core_values(): """Displays the user's core values.""" core_values = load_json_data('core_values_responses.json') if core_values: st.header("Your Core Values") for question, answer in core_values.items(): st.text(f"{question}: {answer}") def display_strength_responses(): """Displays the user's responses to the strength exercises.""" strength_responses = load_json_data('strength_responses.json') if strength_responses: st.header("Your Strength Responses") for key, value in strength_responses.items(): st.text(f"{key}: {value}") def display_dynamic_strength_responses(): """Displays dynamic strength responses (Exercise 3) from the network.""" network_feedback_list = load_json_data('dynamic_strength_responses.json') if network_feedback_list: st.header("Dynamic Strength Responses (Exercise 3)") for feedback in network_feedback_list: st.subheader(f"Feedback from {feedback['name']} ({feedback['role']})") for question, response in feedback['responses'].items(): st.markdown(f"- **{question}:** {response}") def display_skills_and_experience(): """Displays the user's skills and experience responses.""" skills_and_experience_sets = load_json_data('skills_and_experience_sets.json') if skills_and_experience_sets: st.header("Your Skills and Experience") for i, skills_set in enumerate(skills_and_experience_sets, start=1): st.subheader(f"Skills and Experience Set {i}") for question, answer in skills_set.items(): st.markdown(f"**{question}:** {answer}") def display_preferences(): """Displays the user's career preferences.""" preferences_sets = load_json_data('preferences_sets.json') if preferences_sets: st.header("Your Career Preferences") for i, preferences_set in enumerate(preferences_sets, start=1): st.subheader(f"Preferences Set {i}") for preference, answer in preferences_set.items(): st.markdown(f"**{preference}:** {answer}") def display_dream_job_info(): """Displays the saved dream job information.""" try: with open('dream_job_info.json', 'r') as file: dream_job_info = json.load(file) st.header("Your Dream Job Information") st.markdown(f"**Dream Job Description:** {dream_job_info['dream_job_description']}") st.markdown(f"**Is it a realistic possibility?** {dream_job_info['dream_job_realism']}") if dream_job_info['dream_job_realism'] == "Yes": st.markdown(f"**Explanation:** {dream_job_info['dream_job_explanation']}") st.markdown(f"**Attributes:** {dream_job_info['dream_job_attributes']}") st.markdown(f"**Feelings:** {dream_job_info['feel_sentence']}") st.markdown(f"**Needs:** {dream_job_info['need_sentence']}") st.markdown(f"**Goals:** {dream_job_info['goal_sentence']}") except FileNotFoundError: st.error("Dream Job Information not found.") def display_priorities(): """Display saved career priorities.""" try: with open('career_priorities_data.json', 'r') as file: priorities_data = json.load(file) st.header("Your Career Priorities") for aspect, data in priorities_data.items(): st.subheader(aspect) st.markdown(f"**Priority Rating:** {data['rating']}") st.markdown(f"**Reason:** {data['reason']}") except FileNotFoundError: st.error("Career Priorities data not found.") # Ensure the app() function calls display_dream_job_info() # Ensure the app() function calls display_preferences() # Ensure the app() function calls display_skills_and_experience() def app(): display_core_values() display_strength_responses() display_dynamic_strength_responses() display_skills_and_experience() display_preferences() display_dream_job_info() display_priorities() if __name__ == "__main__": app()