Python CSV Automation & Verification

PHP, Python, Data Processing, Software Architecture, JSON, Scripting, Automation, Pandas · I need a clean, well-documented Python script that can pick up CSV files from a watched folder, process them according to my business rules, and then push the results to a designated output location. The workflow breaks down into three core parts.

1. File I/O handling • Automatically read incoming CSV files. • After processing, write the transformed data to a separate folder. • Rename each source file to a timestamped archive name and move it to an “_archive” sub-directory so nothing is re-processed by mistake.

2. Data processing & algorithmic checks The CSVs include a fixed header row followed by transactional records. For every row the script must: • Run field-level validation (type, range, mandatory columns). • Apply record-level business rules that I will supply as a Python dictionary of lambdas. • Flag or correct detectable data errors—e.g. wrong date formats or out-of-range numeric values—while logging any changes so I have an audit trail.

3. Reporting • Create a concise log (plain text or JSON) listing files handled, rows processed, rows corrected, and any unrecoverable errors. • Exit with a non-zero status if unrecoverable