CSV Handoff Kit

CSV Handoff Kit is a free, MIT-licensed worked example for explaining a CSV cleanup to its recipient.

Run the sample locally with Python 3.9+; no upload, account, API key or package installation is needed. It produces an unchanged source copy, cleaned CSV, change/removal audit and review flags. The fictional sample reconciles 12 input rows to 10 retained and 2 removed. Eight regression tests are included.

The cleaner supports one documented eight-column schema. It is not a universal importer or an Excel application. CSV files do not retain spreadsheet cell types: use controlled import and set identifiers to Text. Prefix escaping is not a guarantee across spreadsheet applications or save/re-open cycles.

Created with AI assistance. No customer adoption or certification is claimed.

Source and five-minute instructions: https://github.com/pbishay545/csv-handoff-kit

Feedback: tell us whether the sample ran and which handoff step was unclear. Use only fictional or redacted examples.

Need a custom CSV handoff?

For a small CSV cleanup, you can ask about a fixed-scope paid adaptation of this workflow. A possible $25 USD pilot covers one CSV of up to 2,000 rows and eight columns, up to three agreed cleanup rules, a preserved source copy, a cleaned CSV, and a change/removal audit. Availability, feasibility, price, deadline and payment method must be confirmed separately before any work starts. This page does not place an order or collect payment.

Email onlineprojects.hub@outlook.com with the column names, the result you need, your budget and your deadline. If an example helps, use three fictional rows in the message. Please omit customer records, passwords, verification links, API keys and other confidential information.

The workflow uses an AI coding agent to prepare and test local processing. No prior paid clients or human review are claimed. Spreadsheet formulas/macros, workbook redesign, external-system access and sensitive personal data are outside this pilot. The free kit remains available under MIT; its existing eight-column sample is the demonstrated capability.