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This tool processes raw, messy scraped job data from Amazon’s careers pages. It’s for Python developers and data analysts who need stable, structured datasets for analysis. It handles common scraping inconsistencies like duplicate entries, broken HTML, and varying date formats. Features Deduplicate listings by job ID and title — removes exact and fuzzy duplicates Standardize date formats — converts various string formats to ISO 8601 Clean HTML artifacts — strips tags and normalizes whitespace from description fields Validate and structure location data — parses city, state, country into separate columns Export to clean CSV or JSON — outputs a consistent, analysis-ready file Usage amazon_job_cleaner --input messy_listings....

We just released Ecommerce Listing Data Cleaner — clean, validate, and format product data from csv/json for ebay listings. What it does A Python CLI tool for eBay sellers who export their inventory data. It cleans messy product titles, validates required fields, and formats data to meet eBay’s listing requirements, saving hours of manual editing. Works with data exported from any platform. Features CSV/JSON input validation for eBay required fields Automatic title cleaning (removes excess caps, fixes spacing) SKU and price column standardization Condition and category ID mapping from plain text Export to eBay-ready CSV or formatted JSON Usage import listing_cleaner listing_cleaner....

We just released Ecommerce Process Audit Tool — analyze your order and inventory data to find process bottlenecks before buying tools. What it does This tool reads exported order and inventory CSVs from any ecommerce platform and identifies common process failures like fulfillment delays, stockout patterns, and refund clusters. It’s for Python developers managing small to mid-sized ecommerce operations who need data-driven insights to fix their core workflow before investing in new software....

We just released Marketplace Job Listings Data Cleaner — clean and deduplicate scraped amazon job listings from csv or json files. What it does This tool processes raw, messy scraped job data from Amazon’s careers pages. It’s for Python developers and data analysts who need stable, structured datasets for analysis. It handles common scraping inconsistencies like duplicate entries, broken HTML, and varying date formats. Features Deduplicate listings by job ID and title — removes exact and fuzzy duplicates Standardize date formats — converts various string formats to ISO 8601 Clean HTML artifacts — strips tags and normalizes whitespace from description fields Validate and structure location data — parses city, state, country into separate columns Export to clean CSV or JSON — outputs a consistent, analysis-ready file Usage amazon_job_cleaner --input messy_listings....

We just released PPC Campaign Performance Analyzer — analyze and compare ppc campaign data from multiple csv exports. What it does This tool processes CSV exports from Google Ads, Microsoft Advertising, and Meta Ads. It normalizes data, calculates key metrics, and generates a unified performance report. It’s for marketers and agencies who need to compare campaigns across platforms without manual spreadsheet work. Features Merge multiple platform CSV exports into a single dataset Calculate cross-platform KPIs (ROAS, CPA, CTR) Generate summary report in JSON, CSV, and Markdown formats Filter and segment data by date range, campaign name, or status Detect data anomalies and missing required columns Usage ppc_analyzer --google ads_data....

This tool processes CSV exports from Google Ads, Microsoft Advertising, and Meta Ads. It normalizes data, calculates key metrics, and generates a unified performance report. It’s for marketers and agencies who need to compare campaigns across platforms without manual spreadsheet work. Features Merge multiple platform CSV exports into a single dataset Calculate cross-platform KPIs (ROAS, CPA, CTR) Generate summary report in JSON, CSV, and Markdown formats Filter and segment data by date range, campaign name, or status Detect data anomalies and missing required columns Usage ppc_analyzer --google ads_data....