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https://github.com/vee1e/bulk-questionnaire-upload.git
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vee1e
165b249c3d
- Introduced a CI workflow for automated testing of backend and frontend components. - Added pytest configuration for backend tests and Vitest configuration for frontend tests. - Enhanced file validation logic in the backend to improve error handling and reporting. - Created comprehensive test cases for various validation scenarios, including edge cases and incorrect formats. - Updated requirements to include necessary testing libraries and tools.
80 lines
3.2 KiB
Python
80 lines
3.2 KiB
Python
import pandas as pd
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import os
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from faker import Faker
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import random
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fake = Faker()
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output_dir = "test_xlsforms_valid" # Changed directory name
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os.makedirs(output_dir, exist_ok=True)
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VALID_INPUT_TYPES = [1, 2, 3, 4, 5, 6, 7] # Example: 1=Text, 2=Select One, 3=Select Many, etc.
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def generate_valid_xlsform(file_name_prefix, num_questions, num_options_per_question):
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forms_data = {
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"Language": [random.choice(["en", "fr", "es", "de"])],
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"Title": [fake.catch_phrase() + " Form"]
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}
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forms_df = pd.DataFrame(forms_data)
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questions_data = []
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for i in range(num_questions):
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question_order = i + 1
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question_type = random.choice(VALID_INPUT_TYPES)
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questions_data.append({
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"Order": question_order,
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"Title": fake.sentence(nb_words=6),
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"View Sequence": i + 1,
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"Input Type": question_type,
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"Optional Column 1": fake.word(), # Add some optional columns
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"Optional Column 2": fake.random_int(min=1, max=100)
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})
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questions_df = pd.DataFrame(questions_data)
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options_data = []
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for question_idx, question in questions_df.iterrows():
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if question["Input Type"] in [2, 3]: # Select One or Select Many
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# Generate 3-10 options per question
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num_options_for_question = random.randint(3, 10)
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for i in range(num_options_for_question):
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# Generate a more robust label that won't be empty
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label = fake.catch_phrase().split()[0].capitalize()
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if not label or len(label) < 2:
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label = f"Option{i+1}"
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options_data.append({
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"Order": question["Order"],
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"Id": i + 1,
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"Label": label
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})
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options_df = pd.DataFrame(options_data)
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# Validate that all labels are non-empty
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if not options_df.empty:
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# Replace any empty or null labels with fallback values
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options_df['Label'] = options_df['Label'].fillna('Default Option')
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options_df.loc[options_df['Label'] == '', 'Label'] = 'Default Option'
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options_df.loc[options_df['Label'].str.len() < 2, 'Label'] = 'Default Option'
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file_path = os.path.join(output_dir, f"{file_name_prefix}.xlsx")
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with pd.ExcelWriter(file_path, engine="openpyxl") as writer:
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forms_df.to_excel(writer, sheet_name="Forms", index=False)
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questions_df.to_excel(writer, sheet_name="Questions Info", index=False)
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options_df.to_excel(writer, sheet_name="Answer Options", index=False)
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return file_path
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# Generate 9 forms with ~400 questions each
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num_files_to_generate = 100
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generated_files = []
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for i in range(num_files_to_generate):
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file_name = f"valid_form_{i+1}"
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# Generate approximately 400 questions per form (with some variation)
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num_questions = random.randint(380, 420) # ~400 questions with ±20 variation
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path = generate_valid_xlsform(file_name, num_questions, 10) # Max 10 options, actual will be 3-10
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generated_files.append(path)
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print(f"Generated form {i+1}: {num_questions} questions")
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print(f"\nSuccessfully generated {len(generated_files)} valid test files in '{output_dir}'")
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print("Each form contains approximately 400 questions with 3-10 options per select question.")
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