CSV

The choice of structured data output format should match the downstream use: JSON is more suitable for consumption by front-end applications, while CSV or Excel is more direct for data analysts to use.

CSV is not a strict standard, and implementations differ in quote escaping, newline handling, and character encoding (UTF-8 versus UTF-8 BOM).

Do not put CSV password export files into emails, chat prompts, shared folders, or code repositories.

The fundamental difference between KDBX and CSV is: CSV is plaintext, and anyone can directly read the passwords; KDBX encrypts the entire vault contents with a master key and encapsulates them as a whole, so no readable fields can be seen in the file.

The OCR workflow includes steps such as starting from a clear image, extracting relevant information, converting to a suitable format (such as JSON, CSV, XML, YAML), validating the extraction results, and connecting to applications.

Standard CSV wraps fields containing delimiters in quotation marks.

When CSV field content itself contains commas, a simple find-and-replace will corrupt the data structure, causing column misalignment.

The tool flattens match details into CSV files that can be used directly for machine learning.

When troubleshooting, exporting a file from Excel format to CSV format to rule out format compatibility issues is a reasonable troubleshooting step.

CSV is a plain-text format that any program can read directly; XML is also plain text but its nested tag structure requires a dedicated parser to handle.