whatisgithub

What is dataset-zero-obstacle-high-density-z01?

zalo/dataset-zero-obstacle-high-density-z01 — explained in plain English

Analysis updated 2026-07-15 · repo last pushed 2026-02-26

TypeScriptAudience · developerComplexity · 3/5MaintainedSetup · moderate

In one sentence

Generates practice routing puzzles and solutions for software that automatically wires connections on circuit boards. It creates random puzzle examples with visual diagrams and correct answers, useful for training AI autorouting tools.

Mindmap

mindmap
  root((repo))
    What it does
      Generates routing puzzles
      Solves connection paths
      Saves visual diagrams
    Outputs
      Data file of solutions
      Vector image format
      Pixel image format
    Use cases
      Train AI autorouters
      Test routing algorithms
      Bulk dataset generation
    Tech stack
      TypeScript
      Cloudflare edge network
    Audience
      PCB designers
      Routing software developers
      AI training researchers
Click or tap to explore — scroll the page freely

Code map

Detail Auto

An interactive map of this repo's files and how they connect — its source is parsed live in your browser. Click Visualize to build it.

filefunction / class

What do people build with it?

USE CASE 1

Generate thousands of routing puzzle examples to train an AI autorouter for circuit boards.

USE CASE 2

Test a PCB routing algorithm against known puzzle-and-solution pairs.

USE CASE 3

Deploy a web service to mass-produce training datasets across parallel requests.

USE CASE 4

Create visual before-and-after diagrams of board connections for documentation or debugging.

What is it built with?

TypeScriptCloudflare Workers

How does it compare?

zalo/dataset-zero-obstacle-high-density-z01agg23/runelite-gameplay-analyticsairirang/airirang-builder
Stars0
LanguageTypeScriptTypeScriptTypeScript
Last pushed2026-02-262025-01-02
MaintenanceMaintainedStale
Setup difficultymoderatemoderatemoderate
Complexity3/53/53/5
Audiencedevelopergeneraldeveloper

Figures from each repo's GitHub metadata at analysis time.

How do you get it running?

Difficulty · moderate Time to first run · 30min

Requires deploying to Cloudflare's edge network for at-scale generation, though local generation is also possible.

So what is it?

This project generates practice problems and solutions for software that automatically routes electrical connections on printed circuit boards (PCBs). It creates random connection puzzles on a 10x10 millimeter square board, where connections need to be made between points on the edges without any obstacles in the way. For each puzzle, it saves the solution and an image showing both the required connections and the final routed paths. The code works by randomly generating a set of boundary connection pairs, then attempting to solve the routing problem using a built-in solver. When it successfully finds a solution, it saves the results into a data file and creates images showing the initial connections and the completed routing. If the solver cannot solve a specific puzzle, it simply skips that one and logs the failure. The output includes a structured data file with all the successful solutions, along with visual representations in both vector and pixel image formats. PCB designers and developers working on circuit board autorouting software would find this useful for training or testing their routing algorithms. For example, if someone is building AI tools to automatically lay out circuit board wiring, they need thousands of examples to train their system. This project provides those examples automatically, each one containing a specific routing challenge alongside its correct solution, along with visual diagrams showing what the board looks like before and after the paths are drawn. The project also includes a web service component that can be deployed to Cloudflare's edge network, allowing you to generate these datasets at scale across multiple concurrent requests. This is useful if you need to produce large volumes of training data quickly, since you can request thousands of samples from a remote endpoint instead of generating them all on your local machine. You can control how many samples to generate and how many requests to run in parallel.

Copy-paste prompts

Prompt 1
Set up this project locally and generate 100 PCB routing puzzles with their solutions and images. Walk me through the commands step by step.
Prompt 2
Deploy this dataset generator to Cloudflare's edge network and configure it to produce 5000 samples with 10 parallel requests. Explain how to call the endpoint.
Prompt 3
Use the data files this project generates to train a simple neural network that predicts routing paths from boundary connections. Start with loading the JSON data.
Prompt 4
Modify the generator to create puzzles on a 20x20mm board instead of 10x10mm and show me what changes are needed in the code.

Frequently asked questions

What is dataset-zero-obstacle-high-density-z01?

Generates practice routing puzzles and solutions for software that automatically wires connections on circuit boards. It creates random puzzle examples with visual diagrams and correct answers, useful for training AI autorouting tools.

What language is dataset-zero-obstacle-high-density-z01 written in?

Mainly TypeScript. The stack also includes TypeScript, Cloudflare Workers.

Is dataset-zero-obstacle-high-density-z01 actively maintained?

Maintained — commit in last 6 months (last push 2026-02-26).

How hard is dataset-zero-obstacle-high-density-z01 to set up?

Setup difficulty is rated moderate, with roughly 30min to a first successful run.

Who is dataset-zero-obstacle-high-density-z01 for?

Mainly developer.

Open on GitHub → Ask about another repo

This repo across BitVibe Labs

Verify against the repo before relying on details.