
YData SDK
Improve data quality with smart synthetic data
What it does
The YData SDK allows users to profile their datasets 📊 and use synthetic data 📈 to boost data augmentation, reduce bias, foster data sharing, and alleviate data privacy concerns. It can be used on a simple Python script or Jupyter/Google Colab Notebook! 🪐
Does a similar job
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Dear HN, I am Riwaj, the cofounder of dstack.ai (https://github.com/dstackai). A few months ago, we built an online service that allows users to publish data visualizations from Python or R. The idea was to build a tool that did not require additional programming or front-end development for publishing data visualizations. Such a code can be invoked from either Jupyter notebook, RMarkdown, Python, or R scripts. Once the data is pushed, it can be accessed via a browser. Open-sourcing dstack: During our customer discovery phase, we realized that dstack.ai should integrate a lot…

- MSMisata – synthetic data engine using LLM and Vectorized NumPyDec 2025 · github.com · ▲24
Hey HN, I’m the author. I built Misata because existing tools (Faker, Mimesis) are great for random rows but terrible for relational or temporal integrity. I needed to generate data for a dashboard where "Timesheets" must happen after "Project Start Date," and I wanted to define these rules via natural language. How it works: LLM Layer: Uses Groq/Llama-3.3 to parse a "story" into a JSON schema constraint config. Simulation Layer: Uses Vectorized NumPy (no loops) to generate data. It builds a DAG of tables to ensure parent rows exist before child rows (referential integrity).…

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Source: Product Hunt launch ↗
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