MockNova
The 100% Client-Side Data Engine: Generate, Clean & Mock
1 follower
The 100% Client-Side Data Engine: Generate, Clean & Mock
1 follower
MockNova is a privacy-first data engine for developers. Generate up to 100k rows of complex relational data, clean messy logs with "Magic Extract," and mock APIs locally using MSW—all 100% client-side. No backend, no data leaves your machine, and zero paywalls. Perfect for frontend testing, SQL practice, and data science. Features "Chaos Mode" for dirty data testing and a built-in API mocking server. Fast, free, and built for speed. Stop fighting with limits and start building.
Major Update: Moving Beyond Faker! 🚀
Hi everyone! I’ve just rolled out a significant update to MockNova:
Real-World Datasets: MockNova no longer relies solely on Faker for random generation. I’ve started implementing real-world dictionaries. Now, when you combine fields like Country + City + Zip Code + Phone, they are logically linked and reflect real-life locations.
Smart Data Cleaning: I’m currently working on bringing this same logic to the "Smart Inference & Imputation" feature in the Data Cleaner. The goal is to let you fill gaps in your existing messy data with context-aware, realistic values (Work in Progress).
UI Overhaul: I’ve redesigned the entire interface to be cleaner, more intuitive, and less chaotic.
I’m constantly adding new regions and datasets. Check it out and let me know what you think!
MockNova Update: Data Anonymizer & Pro Cleaning Suite! 🛡️✨
Hi Product Hunt community! Since my last update, MockNova has evolved from a smart generator into a full-scale data toolkit. Here’s what’s new in this major rollout:
🚀 Brand New: Data Anonymizer
You can now securely mask or spoof sensitive PII (Personally Identifiable Information) directly in your browser. Whether it's emails, names, or addresses, you can anonymize them using our real-world dictionaries while keeping your data 100% local and private.
🧠 Smart Inference & Imputation (Now Live!)
The "Smart Filling" feature is out of the experimental phase. It now uses cross-field logic—for example, it can intelligently split a "Full Name" to fill missing "First" or "Last Name" columns before resorting to random generation. Look for the new [C], [D], and [F] markers in the preview to see exactly how your data was recovered!
🧹 New Cleaning Power-Ups
Auto Capitalize: Instantly fix messy text (e.g., "adam zawadzki" → "Adam Zawadzki") with smart detection that ignores emails and URLs.
Make Numbers Positive: A one-click fix for accounting or data entry errors, with auto-detection for numeric columns.
⚡ Performance: Background Processing
I’ve optimized the core engine to handle large datasets in the background. You can now watch the progress bar while the app stays responsive.
I’m building this to be the fastest way to handle "messy" data. Give it a spin and let me know what feature I should add next!