Start by clarifying the exact output format and any edge cases, then outline a script that reads the CSV, trims fields, and prints each record as a two-line block with proper dollar formatting and delimiters. Emphasize preserving row order and handling potential issues like missing values or malformed rows.
Pro tip: Mention that you would use Python's csv module for robust parsing and explicitly test with edge cases like amounts with commas or negative values to ensure correct formatting. Also, note that you'd confirm the expected output format with the interviewer before coding.
Ask about the exact format of the two-line block, delimiter lines, dollar formatting (e.g., $1,234.56), and how to handle missing or malformed data. Confirm that row order must be preserved and fields trimmed.
Select a language and library (e.g., Python's csv module) that handles CSV parsing robustly. Plan to read the file row by row, trim each field, and store or process records in order.
For each record, format the amount as a dollar string with commas and two decimals, then construct the two-line block with specific spacing and delimiter lines. Ensure fields are trimmed before formatting.
Add checks for missing fields, non-numeric amounts, or empty lines. Decide whether to skip, log, or raise errors, and ensure the script doesn't crash on unexpected input.
Run the script on sample data, including edge cases, and compare output to the expected format. Verify row order and trimming are correct.
AI-generated suggestions, not part of the candidate's original notes. May be inaccurate — verify before relying on them.