I will build a local python CSV validator for your fixed schema


Over deze dienst
Get a small, repeatable CSV validation workflow with clear results.
For $40, I will configure and deliver a local Python command-line tool for one fixed-schema CSV (up to 1,000 rows) plus one category lookup. Delivery: 3 days, including source code, tests, a usage guide and a worked example. One revision covers category-name changes only.
Input columns: sku, product_name, category_code, quantity, updated_date. The lookup contains category_code and category_name. The tool checks required fields, dates and quantities, preserves leading-zero SKUs, matches categories by exact key, and separates accepted, rejected and duplicate rows with a summary report.
Please message me with a redacted sample before ordering to confirm fit. Only non-sensitive data you are authorized to share.
Tested on Linux with Python 3.12/3.13 using synthetic examples. Windows/macOS setup, production deployment, scraping, account access, fuzzy matching, live databases and ongoing maintenance are outside this offer. AI tools assist development; results are independently checked. See FAQs for limits and source-code terms.
Maak kennis met Ethan Lee
ITSM and workflow automation specialist
- Afkomstig uitChina
- Lid sindsokt 2026
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Which CSV format does this package support?
UTF-8 CSV: sku, product_name, category_code, quantity, updated_date. Lookup: category_code,category_name. Quantity: 0-9999; date: YYYY-MM-DD. Up to 1000 input rows. The column names and validation rules are fixed; category labels come from your lookup. Send a redacted sample to confirm fit.
What will I receive and what does one revision cover?
A Python CLI with source, tests, usage guide and a worked example producing accepted.csv, rejects.csv, duplicates.csv and report.json. One consolidated revision changes category names only. New schemas, validation rules, features or platforms require a separate agreed scope.
Which environments have been tested?
Linux with Python 3.12 and 3.13, using synthetic data and 20 independent tests. Requires comfort with a terminal. No third-party Python packages or network calls. Windows/macOS, real production data, concurrent writes and large-file performance have not been validated.
What should I know about safe use and data?
Keep backups and use a new private local output folder without concurrent changes. Cleanup after failure is best-effort. Treat CSV outputs as text. Send only synthetic or redacted, non-sensitive samples, never credentials or personal/regulated data. This is a bounded tool, not production assurance.
What source-code rights are included?
You receive a non-exclusive licence to use and modify the delivered code for your own personal or business work. Pre-existing generic code may be reused in other projects. Resale or redistribution of the tool is not included. AI-assisted development is independently reviewed and tested.
