Data Extraction

Resumable Listing Extraction to CSV and JSONL

A Python batch extractor collects listing details with progress tracking, incremental exports and restart support.

Illustration of listing extraction; synthetic example, not a delivered-product screenshot
Workflow illustration with synthetic data; not a screenshot of the delivered product.

The problem

The client needed a structured dataset from many listing pages. A long run could fail midway, so the process needed to retain progress and avoid restarting completed work. The output also needed to be usable before the final page had finished.

What I built

  • Separate URL-collection and listing-detail extraction stages.

  • Concurrent processing with controlled delays and retry handling.

  • A record of completed listings to support restart and resume.

  • Incremental JSONL and CSV output during extraction.

  • Progress reporting and configurable execution settings.

The workflow supports review of the extracted dataset and recovery from interrupted runs.

The outcome

The project delivers a repeatable batch-extraction process with visible progress and reusable output files. Website changes and source-access requirements still need maintenance. README timing and volume claims are not presented here as independently verified benchmarks, and this story does not promise unrestricted extraction from arbitrary websites.

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