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A Python script can run without crashing and still produce the wrong CSV. My starting point is a tiny synthetic input and the exact expected output, then a regression test that fails before the fix and passes afterward.
I have published a fixed-scope CSV/JSON debugging service: one reproducible issue, a source patch, regression test and run instructions. Starting at $75, with a 3-day delivery window after scope and inputs are agreed.
If this matches a problem you have, message me on Contra to discuss scope first. Please keep credentials and personal records out of sample data. AI-assisted development is disclosed in the service description.
https://contra.com/s/6cscmlbE-python-csvjson-script-debugging
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I'm testing a $79 report for Shopify merchants who want to see exactly what changed between their original product CSV and a proposed price-update file. It separates intended price changes from changes to other fields, so you can review both before deciding what to do next.
Here's a simple synthetic example: a mug's price changes from $20 to $22 as intended, but the proposed CSV also blanks its Vendor and changes its Status from active to draft. The report lists those differences separately from the price change. This is an invented demonstration, not client work or a customer result.
The proposed $79 report covers up to 1,000 matching products, with one row and one default variant per product, using supported columns only. It uses deterministic comparison with AI-assisted explanations.
This is a read-only comparison. It does not access your store, execute an import, correct files or certify that an import is safe.
Have both CSV files ready for an upcoming price update? Message me on Contra with your product count and intended change, and let me know whether you would request the report at $79 if scope, availability and terms can be confirmed. Start with a description only; don't send confidential files or store access. An inquiry does not place an order or request payment.
Catching accidental changes outside the price column is the part a plain spreadsheet compare never shows clearly. How are you testing the $79 price, DMs to merchants or a landing page?
"Engineered an automated data-cleansing framework to audit, normalize, and restructure high-error transactional records. By resolving systemic data anomalies—including string irregularities, duplicate entity entries, schema mismatches, and null variances—this pipeline elevated raw, unreliable logs into clean, decision-ready assets primed for business intelligence modeling."
VentureLens — Venture Lens is an AI agent that turns your raw idea into a good investment using evidence-based sparring.
Instead of putting you through a stale 20-questions test, it asks the one question until it gets your usual answer, makes a short list of recommendations, then combines your data with Qloo’s taste intel and place profiles to create a full, top-to-bottom business brief you can read and download right away as markdown.
Check it here- https://devpost.com/software/venturelens-ne53u4
Asking one sharp question at a time instead of a 20-question form is the right call. Curious how it decides an answer is good enough to move on, since that's where most validation agents stall or rubber-stamp.