from dataclasses import dataclass

from typing import List, Dict, Any

import csv

import json

import statistics

class SurveyCollector:

survey_id: str

title: str

blocks: List['Block']

responses: List[Dict[str, Any]] = None

def __init__(self, survey_id, title):

self.survey_id = survey_id

self.title = title

self.blocks = []

self.responses = []

def add_block(self, block):

self.blocks.append(block)

def collect_response(self, response):

self.responses.append(response)

def get_block(self, block_id):

for block in self.blocks:

if block.block_id == block_id:

return block

raise ValueError("Block not found")

def process_responses(self):

results = {}

for response in self.responses:

for question_id, answer in response.items():

if question_id not in results:

results[question_id] = []

results[question_id].append(answer)

processed_results = {}

for question_id, answers in results.items():

if isinstance(answers[0], list): # For multi-select questions

processed_results[question_id] = {option: answers.count([option]) for option in set(answer for answer_list in answers for answer in answer_list)}

elif isinstance(answers[0], str): # For single choice or open-ended

processed_results[question_id] = {option: answers.count(option) for option in set(answers)}

elif isinstance(answers[0], int) or isinstance(answers[0], float): # For scale or numerical questions

processed_results[question_id] = {

'mean': statistics.mean(answers),

'median': statistics.median(answers),

'mode': statistics.mode(answers) if len(set(answers)) > 1 else answers[0],

'count': len(answers)

}

else: # For other types, just count occurrences

processed_results[question_id] = {answer: answers.count(answer) for answer in set(answers)}

return processed_results

def export_results(self, filename='results', format='csv'):

results = self.process_responses()

if format == 'csv':

with open(f"{filename}.csv", 'w', newline='') as csvfile:

writer = csv.writer(csvfile)

for question_id, data in results.items():

writer.writerow([question_id])

if isinstance(data, dict):

for option, count in data.items():

writer.writerow([option, count])

else:

writer.writerow([data])

elif format == 'json':

with open(f"{filename}.json", 'w') as jsonfile:

json.dump(results, jsonfile, indent=4)

else:

raise ValueError("Unsupported format. Please use 'csv' or 'json'.")

class Block:

block_id: str

questions: List['Question']

def add_question(self, question):

self.questions.append(question)

class Question:

question_id: str

question_text: str

question_type: str

options: List[str] = None

def validate_response(self, response):

if self.question_type == 'multiple_choice':

if isinstance(response, list):

if not all(r in self.options for r in response):

raise ValueError(f"Invalid response for question: {self.question_text}. Must be one of {self.options}")

elif response not in self.options:

raise ValueError(f"Invalid response for question: {self.question_text}. Must be one of {self.options}")

elif self.question_type == 'open_ended':

if not response:

raise ValueError(f"Response cannot be empty for question: {self.question_text}")

elif self.question_type == 'likert_scale' or self.question_type == 'scale':

if not isinstance(response, int) or response < 0 or response > 10: # Adjust range as needed

raise ValueError(f"Response must be an integer between 0 and 10 for question: {self.question_text}")

return True

demographics = Block("Demographics", [])

demographics.add_question(Question("Age", "What is your age?", "open_ended"))

demographics.add_question(Question("Year", "What year are you in college?", "multiple_choice",

["First Year (1)", "Sophomore (2)", "Junior (3)", "Senior (4)", "5+ Years (5)"]))

demographics.add_question(Question("Ethnicity", "Are you of Spanish, Hispanic, or Latino origin?", "multiple_choice",

["Yes (1)", "No (2)"]))

demographics.add_question(Question("Race", "Choose one or more races that you consider yourself to be", "multiple_choice",

["White or Caucasian (1)", "Black or African American (2)",

"American Indian/Native American or Alaska Native (3)", "Asian (4)",

"Native Hawaiian or Other Pacific Islander (5)", "Other (6)",

"Prefer not to say (7)"]))

demographics.add_question(Question("Household_Income", "What was your total household income before taxes during the past 12 months?", "multiple_choice",

["Less than $25,000 (1)", "$25,000-$49,999 (2)", "$50,000-$74,999 (3)",

"$75,000-$99,999 (4)", "$100,000-$149,999 (5)", "$150,000 or more (6)",

"Prefer not to say (7)"]))

demographics_political = Block("Demographics Political", [])

demographics_political.add_question(Question("Election", "Do you plan to vote in the upcoming 2024 election?", "multiple_choice",

["Yes (1)", "No (2)"]))

demographics_political.add_question(Question("Party_Affiliation", "Generally speaking, do you usually think of yourself as a Republican, a Democrat, an Independent, or something else?", "multiple_choice",

["Republican (1)", "Democrat (2)", "Independent (3)", "Other (4)", "No preference (5)"]))

demographics_political.add_question(Question("R_Strength", "Would you call yourself a strong Republican or a not very strong Republican?", "multiple_choice",

["Strong (1)", "Not very strong (2)"]))

demographics_political.add_question(Question("D_Strength", "Would you call yourself a strong Democrat or a not very strong Democrat?", "multiple_choice",

["Strong (1)", "Not very strong (2)"]))

demographics_political.add_question(Question("Independent_Lean", "Do you think of yourself as closer to the Republican or Democratic party?", "multiple_choice",

["Republican (1)", "Democratic (2)"]))

demographics_political.add_question(Question("Political_Views", "Here is a 7-point scale on which the political views that people might hold are arranged from extremely liberal (left) to extremely conservative (right). Where would you place yourself on this scale?", "scale",

["0", "1", "2", "3", "4", "5", "6", "7"]))

demographics_political.add_question(Question("Party_Registration", "What political party are you registered with, if any?", "multiple_choice",

["Republican (1)", "Democratic (2)", "Independent (3)", "Other (4)", "None (5)"]))

personal_political = Block("Personal Political Characteristics", [])

personal_political.add_question(Question("P_Efficacy", "For each question below, please choose the response that best reflects how you feel.", "likert_scale",

["Strongly Disagree (1)", "Somewhat disagree (2)", "Neither agree nor disagree (3)", "Somewhat agree (4)", "Strongly agree (5)"]))

personal_political.add_question(Question("P_Knowledge_Intro", "Here are a few questions about the federal government. Many people don't know the answers to these questions, so if there are some you don't know, just provide your best guess.", "intro"))

personal_political.add_question(Question("P_Knowledge_1", "Do you happen to know what job or political office is now held by Kamala Harris?", "open_ended"))

personal_political.add_question(Question("P_Knowledge_2", "Whose responsibility is it to determine if a law is constitutional or not? Is it the president, the Congress, or the Supreme Court?", "multiple_choice",

["President", "Congress", "Supreme Court"]))

personal_political.add_question(Question("P_Knowledge_3", "How much of a majority is required for the U.S. Senate and House to override a presidential veto?", "open_ended"))

personal_political.add_question(Question("P_Knowledge_4", "Do you happen to know which party has the most members in the House of Representatives currently?", "open_ended"))

personal_political.add_question(Question("P_Knowledge_5", "Would you say that one of the parties is more conservative than the other at the national level? Which party is more conservative?", "open_ended"))

perception_news = Block("Perception of News Sources", [])

perception_news.add_question(Question("ABC_News", "ABC News", "likert_scale",

["1 (Definitely not)", "2 (Probably not)", "3 (Might or might not be)", "4 (Probably is)", "5 (Definitely is)"]))

social_media = Block("Perception of Political Information on Social Media", [])

social_media.add_question(Question("Social_Media", "Social media as a source of political information and news is...", "likert_scale",

["Does not apply at all (1)", "2", "3", "4", "5", "6", "Fully Applies (7)"]))

media_consumption = Block("Media Consumption Questions", [])

media_consumption.add_question(Question("News_1", "Where do you typically get your news?", "multiple_choice",

["Print newspapers (1)", "Television (2)", "News websites (3)", "Social media (4)", "Radio (5)", "Podcasts (6)"]))

media_consumption.add_question(Question("News_frequency", "How often do you consume news?", "multiple_choice",

["Daily", "A few times a week", "Once a week", "A few times a month", "Rarely", "Never"]))

misinformation_threat = Block("Mis_Threat", [])

misinformation_threat.add_question(Question("Disinfo_threat", "On the scale from 0 to 10, where 0 means no risk and 10 means extreme risk, how would you rate the risk of disinformation campaigns to each of the following?", "scale",

["0 (No risk)", "1", "2", "3", "4", "5", "6", "7", "8", "9", "10 (Extreme risk)"]))

misinformation_threat.add_question(Question("Disinfo_Res", "In your opinion, who is primarily responsible for combating disinformation?", "multiple_choice",

["Government", "Social Media Companies", "Educational Institutions", "News Outlets", "Individuals", "Other (Please specify)"]))

survey = SurveyCollector("PSY_492", "Election Experience Survey")

survey.add_block(demographics)

survey.add_block(demographics_political)

survey.add_block(personal_political)

survey.add_block(perception_news)

survey.add_block(social_media)

survey.add_block(media_consumption)

survey.add_block(misinformation_threat)

sample_response = {

"Age": "23",

"Year": "Junior (3)",

"Ethnicity": "No (2)",

"Race": ["White or Caucasian (1)", "Other (6)"],

"Household_Income": "Prefer not to say (7)",

"Election": "Yes (1)",

"Party_Affiliation": "Democrat (2)",

"R_Strength": "Not very strong (2)",

"D_Strength": "Strong (1)",

"Independent_Lean": "Democratic (2)",

"Political_Views": 4,

"Party_Registration": "Democratic (2)",

"P_Efficacy": 3,

"P_Knowledge_1": "Vice President",

"P_Knowledge_2": "Supreme Court",

"P_Knowledge_3": "Two-thirds",

"P_Knowledge_4": "Democratic",

"P_Knowledge_5": "Republican",

"ABC_News": 4,

"Social_Media": 5,

"News_1": "Television (2)",

"News_frequency": "A few times a week",

"Disinfo_threat": 8,

"Disinfo_Res": "Social Media Companies"

}

{if survey.collect_response(sample_response):

print("Response collected successfully")

else:

print("Failed to collect response")

survey.export_results()