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Catalog Import on Prestashop with Automated Translation and Markup

1,400+ spare parts references, translated, priced at a 45% margin, and live on PrestaShop — a Python pipeline that turned a raw CSV into a fully operational catalog.

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Screenshot of the Catalog Import on Prestashop with Automated Translation and Markup project — Automation

About this project

Turning a raw 1,400-product spare parts file into a translated, margin-adjusted Prestashop store

Catalog data rarely arrives clean. In this project, the client supplied a raw feed of more than 1,400 references for 4x4 vehicle spare parts — a CSV/XML file with no proper headers, in English, with inconsistent pricing structure. The goal: turn this messy upstream feed into a fully populated French-language Prestashop store, with correct categories, local pricing logic, and search-engine-friendly titles, within a tight deadline.

The solution was a custom Python import pipeline designed to absorb complexity upstream and hand over a clean, production-ready catalog downstream.

The data challenges to solve

  • Header-less source file: the CSV/XML had no column names, requiring preliminary analysis to map each field correctly to the Prestashop schema.
  • English-only content: all product titles and descriptions had to be translated to French before publication, preserving technical accuracy for automotive parts — a domain where mistranslation is immediately spotted by mechanics and DIY customers.
  • Margin application: the supplier prices had to be marked up by 45% to produce the retail prices displayed on the store, with rounding rules for psychological pricing.
  • Prestashop 1.7.8 quirks: title length is capped, certain special characters break URL rewrites, and the import API has rate limits that must be respected.
  • Category assignment: each product needed to land in the right node of a multi-level category tree (by vehicle brand, by part family, by compatibility range).

The pipeline architecture

Stage 1: raw file ingestion and analysis The Python pipeline reads the source CSV/XML, infers the structure, detects anomalies (missing fields, duplicate SKUs, unparseable prices), and produces a cleaned intermediate dataset. Every row that cannot be confidently mapped is flagged in a report for human review, rather than silently dropped.

Stage 2: automated translation via API Each English title and description is sent to a translation API, with domain-specific prompt hints to keep automotive terminology accurate ("bush", "bearing", "suspension arm", "strut" and their French equivalents). Translated strings are cached so re-runs do not repeat calls or costs.

Stage 3: margin application and price formatting Supplier prices are parsed, the 45% markup is applied, and the final price is rounded to the client's preferred format (e.g., X.99 or X.90). VAT calculations are applied appropriately for the target market.

Stage 4: format adaptation to Prestashop 1.7.8 Titles are truncated where needed to respect the 128-character limit without losing the most important descriptive terms. Special characters that break URL rewriting are cleaned up. Category paths are normalized to match the target taxonomy exactly.

Stage 5: batch import via API Products are inserted into Prestashop in batches sized to respect the platform's limits, with transactional safety (a failure mid-batch doesn't leave the catalog in an inconsistent state). The import log captures every inserted, updated, and skipped record for later audit.

Why this kind of project is worth outsourcing

Most e-commerce teams under-estimate the complexity of a catalog migration of this scale. They try to do it in Excel, hit the Prestashop import CSV tool, and discover three weeks later that half their products are in the wrong category, translations are broken, and margins are miscalculated. A purpose-built Python pipeline removes all of that risk in a single engineered pass.

The delivered outcome

  • A fully populated Prestashop store with more than 1,400 products, ready to sell on day one.
  • Accurate French translations across all titles and descriptions.
  • Correct pricing with consistent 45% margin and psychological rounding.
  • Clean category structure aligned with the client's merchandising strategy.
  • A reusable pipeline adaptable to future supplier feed updates with minimal reconfiguration.

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Technologies used

PythonPrestashopTranslation APIData MigrationCSVXML

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