Tool

This tool processes video files in bulk based on a metadata file. It’s for content creators and media managers who need to organize large video libraries. It saves hours by automating repetitive file renaming and tagging tasks. Features Batch rename video files using patterns from a CSV Set or update MP4/MOV metadata tags (title, artist, comment) Generate organized folder structures by date or category Create a JSON/CSV report of all processed files and changes Dry-run mode to preview changes before executing Usage video-processor --input metadata....

This tool processes Instagram data you’ve exported to JSON files and converts it into clean, structured Excel workbooks. It’s for analysts and marketers who need to analyze Instagram insights, posts, or audience data offline. The key benefit is turning messy JSON exports into ready-to-use Excel sheets with charts and tables. Features Parse Instagram JSON export files (posts, profile, insights) Generate separate Excel sheets for posts, followers, and engagement metrics Auto-calculate summary statistics (likes, comments, engagement rate) Create pivot tables and basic charts for visual analysis Export to XLSX with custom formatting and date filters Usage instagram_to_excel --input exported_data....

This tool converts exported bank statement CSV files into Tally Prime XML import format. It’s for accountants and businesses who manually enter bank transactions, saving hours of data entry. It handles multiple bank formats and maps transactions to ledger accounts. Features Parse CSV bank statements from major banks (HDFC, ICICI, SBI, etc.) Map CSV columns to Tally voucher fields (date, narration, amount, type) Generate Tally-compatible XML files for direct import Configurable ledger account mapping for debits and credits Handle multiple transaction types (payment, receipt, contra, journal) Usage import bank_to_tally bank_to_tally....

A Python CLI tool that automates downloading PDFs from a list of URLs. It’s for developers and data analysts who need to archive or process many documents. Handles errors, retries, and organizes files locally. Features Read PDF URLs from CSV, JSON, or Excel input files Configurable concurrent downloads with rate limiting Automatic retry on failed downloads with custom attempts Save files with original names or custom naming patterns Log all download results and errors to a detailed report Usage bulk_pdf_downloader --input urls....

This tool automates lead generation by taking a list of LinkedIn profile or company page URLs and extracting publicly available email addresses from their associated websites. It’s for sales teams and recruiters who need to build targeted outreach lists quickly. It works entirely from exported LinkedIn data and avoids any platform scraping. Features Parse CSV/JSON files containing LinkedIn profile or company URLs Extract company website domains from LinkedIn URLs Scrape company ‘Contact’ pages for email patterns Validate extracted emails with syntax and domain checks Output clean lead list with name, company, and email to CSV Usage linkedin_leads --input leads....

This tool reads buy/sell orders from an Excel file and executes them via the StoxKart trading API. It’s for Python developers who automate trading strategies. Key benefit is moving from manual Excel planning to automated trade execution. Features Reads trade orders from Excel (.xlsx, .xls) files Validates order parameters like symbol, quantity, and type Sends authenticated orders to StoxKart REST API Logs all execution results and errors to a CSV file Supports market and limit order types from spreadsheet Usage python execute_trades....

Usage Download CSV: oddshop.work/downloads/synthetic-bank-transactions-1yr.zip Requirements Python 3.8+. Install dependencies: pip install -r requirements.txt Download Buy for $39 → Buy once, download immediately. ZIP includes the full script, README, and usage examples. License Personal & Commercial Use. You may use this tool in your own personal and commercial projects. Redistribution or resale of the source code is not permitted.

Usage Download CSV: oddshop.work/downloads/synthetic-patient-records-10k.zip Requirements Python 3.8+. Install dependencies: pip install -r requirements.txt Download Buy for $39 → Buy once, download immediately. ZIP includes the full script, README, and usage examples. License Personal & Commercial Use. You may use this tool in your own personal and commercial projects. Redistribution or resale of the source code is not permitted.

Usage Download CSV: oddshop.work/downloads/synthetic-mls-listings-500.zip Requirements Python 3.8+. Install dependencies: pip install -r requirements.txt Download Buy for $29 → Buy once, download immediately. ZIP includes the full script, README, and usage examples. License Personal & Commercial Use. You may use this tool in your own personal and commercial projects. Redistribution or resale of the source code is not permitted.

Generates synthetic employee records for testing applications, database seeding, and development environments. Creates realistic data including personal information, job details, and organizational structure. Perfect for HR systems, payroll applications, and employee management software testing. Features Generate thousands of realistic employee records with proper names and demographics Create structured data with departments, job titles, salary ranges, and reporting chains Export to CSV, JSON, or Excel formats with customizable field mappings Control data distribution patterns for realistic organizational hierarchies Include realistic employee attributes like hire dates, contact info, and location data Usage python generate_employees....

Generates realistic fake real estate property listing records as CSV for app testing. Creates property data with MLS-style IDs, addresses, prices, square footage, bedrooms, bathrooms, and agent info. Features Generate MLS-style listing IDs and dates Property addresses with city and state Bedrooms, bathrooms, and square footage Listing price and days on market Agent name, brokerage, and contact info Configurable record count via –records argument Usage python fake-real-estate-listing-generator.py --records 500 --output listings....

Generates realistic fake Shopify order records as CSV for app testing. Creates order data with customer info, product names, SKUs, quantities, prices, and order status using only Python standard library. Features Generate fake order IDs and timestamps Random customer names, emails, and shipping addresses Product names, SKUs, variants, and quantities Prices, discounts, taxes, and order totals Order status distribution (fulfilled, pending, refunded) Configurable record count via –records argument Usage python fake-shopify-order-data-generator....