Keepa-Sheets Hourly Data Sync

Goal
Set up a scalable scraping pipeline using the Keepa.com API. The pipeline must respect Keepa’s token system, run on a fixed schedule, and push cleaned data into Google Sheets until the full result set is processed.

What we need built

Python script that:

Authenticates to Keepa with our API key

Runs a Product Finder query using our filters

Paces requests based on available tokens, waits when tokens are low, then resumes

Pulls results in batches until the entire set is complete

Normalizes and writes data to Google Sheets (via Google Sheets API)

Supports incremental runs, so no duplicate rows

Scheduler on PythonAnywhere

Run every 1 hour

Auto-resume where it left off

Robust logging, basic alerts on failures, and retry logic

Data output

Write to a single Google Sheet with a “raw” tab and a “cleaned” tab

Include key fields we specify in a JSON config, for example: ASIN, title, brand, buyBox price, FBA price, totalOfferCount, current_SALES, monthlySold, BSR, lastOffersUpdate, last price change timestamps

Preserve product IDs so we can de-dupe and upsert cleanly

Config and handoff

.env for secrets

YAML or JSON for filters and field mapping

Clear README with setup, run, and recovery steps

Lightweight unit tests for at least the parser and sheet writer

Key requirements

Strong Python skills

Solid experience with token or rate-limited APIs

Keepa API experience, or equivalent marketplace APIs

Google Sheets API, service accounts, and upsert patterns

Production habits: retries, exponential backoff, idempotency, logging