My first Python project: Excel to SQL pipeline (feedback welcome)

I’ve just made my first substantial Python project public. It’s an Excel-to-SQL pipeline focused on cleaning messy spreadsheet data and preparing it for database ingestion. This is still a work in progress, and I’m actively improving it. Problem Working with Excel data often means dealing with: Inconsistent date and time formats Mixed data types in a single column Missing or malformed values Subtle issues that only surface during database insertion I wanted a reusable way to clean and standardise this kind of data before loading it into SQL. Approach The project focuses on: Column-wise cleaning functions (dates, times, text, etc.) Configurable parsing with strict vs permissive modes Clear error reporting with row-level context Separation between cleaning logic and pipeline orchestration The goal is to make the pipeline predictable and easier to debug when something goes wrong. Example Input (Excel): Mixed date formats Numbers stored as text Invalid values scattered through columns Outp