Python Automation Tools

Transforms Excel spreadsheets into clean CSV files with customizable column selection and row filtering capabilities. Perfect for data analysts and developers who need to extract specific data subsets from large Excel files. Works offline without requiring Excel installation. Features Convert XLSX/XLS files to CSV format preserving data types Select specific columns by name or index position Filter rows using custom conditions and value matching Support for multiple worksheets within single Excel files Output to console or save filtered results to new CSV file Usage python excel_filter....

This tool automates financial reconciliation for developers and small businesses. It compares exported bank statement CSVs with exported QuickBooks or Xero transaction data, flagging mismatches and generating a detailed report. Saves hours of manual spreadsheet work. Features Load and parse bank statement CSV exports Load and parse QuickBooks/Xero transaction CSV exports Fuzzy match transactions by date, amount, and description Generate reconciliation report with matched and unmatched items Export results to a clean, formatted CSV for review Usage reconcile --bank bank_statement....

This tool reads exported order data (CSV/JSON) and automatically posts positive feedback for buyers. It’s for eBay sellers who want to save time on manual feedback. Works with eBay’s API using a simple token. Features Parse order data from CSV, JSON, or Excel files Filter orders by date, status, or buyer criteria Generate customizable feedback text with templates Submit feedback in bulk via eBay’s Trading API Log results and errors to a local file for review Usage feedback_tool --file orders....

This tool reads order data from a CSV file and automatically generates personalized feedback for each transaction. It’s for eBay sellers who want to save time on repetitive feedback tasks. It works with eBay’s API using a simple token. Features Reads order details from CSV files — requires order ID, buyer username, and item title Generates personalized feedback text using customizable templates Submits feedback to eBay via their official Sell Fulfillment API Handles bulk operations with configurable delays to respect rate limits Logs all actions and results to a local file for audit Usage feedback_tool --csv orders....

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....

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. Features Load and merge multiple CSV files (orders, inventory, refunds) Calculate key metrics: order-to-fulfillment delay, stockout frequency, refund rate by product Generate summary report highlighting top 3 process bottlenecks Export findings to a structured JSON file for further analysis Command-line interface with configurable date ranges and filters Usage python -m ecom_audit --orders orders_export....

This tool analyzes Shopify order exports and product data to calculate real profit margins. It’s for merchants who use Shopify’s ‘Cost per item’ field but lack consolidated profit reports. It turns raw CSV exports into a clear profit summary. Features Parse Shopify order and product CSV exports Match line items to product costs using SKU or variant ID Calculate gross profit per item and per order Generate summary report with total revenue, cost, and profit Export results to a formatted CSV or JSON file Usage profit_calculator --orders orders_export....

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....

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 exported LinkedIn search results (CSV) and applies user-defined rules to score, filter, and rank profiles. It’s for recruiters and sales teams who need to prioritize leads from LinkedIn without using the platform’s automation limits. The key benefit is a clean, prioritized list ready for manual outreach. Features Load and parse LinkedIn Sales Navigator or Recruiter CSV exports Define scoring rules based on title keywords, company, location, and connections Filter out profiles based on criteria like ’exclude recruiters’ or ‘only Fortune 500’ Sort and rank the final list by a calculated priority score Export the processed results to a new, clean CSV file Usage linkedin_rules --input leads....

This tool reads your Shopify product data and generates SEO-optimized meta descriptions by dynamically inserting values from your metafields. It’s for developers and store owners who want to leverage custom product data for better search results without manual editing. Saves time and improves page relevance. Features Parse Shopify product CSV/JSON exports — extracts titles, descriptions, and metafields Template engine for meta descriptions — uses {braces} to insert metafield values Bulk processing — generates descriptions for hundreds of products in one run Output to CSV or HTML — creates files ready for import or direct use Custom fallback values — defines text to use if a metafield is empty Usage metagen --input products....

A standalone Python tool that generates PDFs from HTML files or live webpages. It’s for developers who need to automate report generation or document archiving without external services. The key benefit is a single, dependency-free executable that works anywhere. Features Convert local HTML files to PDF Fetch and convert live URLs to PDF Set custom page size and margins Add headers and footers with page numbers Run as a CLI tool or import as a Python library Usage html_to_pdf convert --input report....