Data

What’s in This Dataset This dataset includes 5,000 realistic fake Shopify order records in CSV format, designed to mirror real-world export data from Shopify. Each record contains essential fields like order_id, customer_email, customer_name, product_name, sku, price, discount_amount, shipping_address, order_status, and order_date. The structure matches actual Shopify CSV exports, making it ideal for testing tools and systems that expect real data formats. With columns covering everything from transactional details to customer demographics, this dataset offers a complete snapshot of e-commerce activity for development and analysis....

synthetic patient records are essential for testing healthcare applications, but manually creating them is a tedious task. You end up copying data, fudging dates, or using outdated tools that don’t meet industry standards. The process is slow, error-prone, and often fails to maintain privacy compliance, especially when working with HIPAA-safe datasets. The Manual Way (And Why It Breaks) Creating synthetic patient records manually means copying and pasting from templates or writing out data by hand....

MLS property listings are often scattered across multiple sources, and manually compiling them into a usable dataset can be tedious and error-prone. If you’re working on real estate data projects, you’ve probably encountered the time-consuming task of gathering and structuring property information from various public or private feeds. That’s where automation tools like the 500 Synthetic MLS Property Listings come in. The Manual Way (And Why It Breaks) Manually collecting MLS property listings involves a lot of clicking, copying, and pasting....

The manual process of creating employee records for testing HR systems, database seeding, or payroll applications is tedious and error-prone. You end up copying and pasting data, guessing realistic salary ranges, or worse — reusing the same names over and over. A proper employee record generator can automate this and make your development workflow more efficient. The Manual Way (And Why It Breaks) Manually creating employee data is a time sink....

Synthetic patient data is essential for healthcare software testing, but manually crafting it is tedious and error-prone. Without proper tools, developers often fall back to copying real records or creating fake data by hand — both of which risk privacy violations and inaccurate simulations. The result? Flawed applications that fail in real-world use. The Manual Way (And Why It Breaks) Creating healthcare datasets by hand is a painstaking process. You start with basic demographics like names, dates of birth, and addresses — but then you need to build realistic medical histories....

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....

This tool processes and optimizes raw scraped data from Amazon.in free gift promotions. It’s for Python developers and data analysts who need to clean, deduplicate, and structure messy scraped data into a usable format. The key benefit is turning unstructured scraped output into clean, analysis-ready CSV or JSON files. Features Deduplicates entries based on product ID and title Standardizes inconsistent date and price formats Extracts and validates product URLs from raw HTML snippets Filters out-of-stock or expired promotions based on timestamps Exports cleaned data to CSV or JSON with configurable schemas Usage import amazon_gift_optimizer optimizer....

We just released 10,000 Synthetic Patient Records (HIPAA-safe) — . What it does Usage Download CSV: oddshop.work/downloads/synthetic-patient-records-10k.zip Get it Download 10,000 Synthetic Patient Records (HIPAA-safe) for $39 → Built by OddShop — Python automation tools for developers and small businesses.