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Guide to data tools landscape for developers
Found yourself on a data project and have no idea what they all are talking about? Feel excluded from all the fun discussions in the office kitchen? If only there were a humongous guide going over all the concepts and buzzwords...
Graphify-Labs / graphify
Turn any codebase, with its docs, SQL schemas, configs, and PDFs, into a queryable knowledge graph. A /graphify skill for Claude Code, Cursor, Codex, and Gemini CLI: local deterministic AST parsing, every edge explained, no vector store.
How To Train a Generative Kick Drum Model on Your Old Linux Desktop With 6GB of VRAM
The author trained a text-conditioned generative kick-drum model from 13,615 audio samples on a seven-year-old GPU with only 6GB of VRAM, using a VAE, latent diffusion model, and HiFi-GAN vocoder. The project shows that useful generative models can be built with modest hardware and personal datasets by compressing data into latent space, choosing practical constraints, and using serverle...
percentify
Exploratory stats and data-quality diagnostics for pandas and Polars DataFrames. One call each.
Emily2040 / seedance-2.0
Comprehensive production pipeline for quad-modal AI filmmaking with Seedance 2.0
💖 Most Popular in the Last Two Weeks
GeoSQL
Turn Claude/Codex into geospatial analytics agent.
Lucen a Python compiler that parallelizes for-loops via comment pragmas
yifanfeng97 / Hyper-Extract
Hypergraph is more powerful. Transform unstructured text into structured knowledge with LLMs. Graphs, hypergraphs, and spatio-temporal extractions — with one command.
Ossie
Apache Ossie is a vendor-neutral standard for sharing semantic metadata across analytics, AI, and BI tools. Its goal is to define metrics and business meaning once, then reuse them everywhere.
Ban commits/transactions using AST analysis and linters
The post explains why database commits and transactions should be owned only by the DB access layer, because hidden commits and leaking DB models can silently break atomicity or lose data. It shows how to enforce those boundaries with AST tests, flake8 rules, and a narrow LLM review step to catch DB models being returned where domain models should be used.
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