Design Dojo
A local, single-user interview practice studio with two tracks:
- Low-level design: write multi-file Java solutions in a browser editor, compile and test them, and get rubric-based AI feedback.
- High-level design: work through requirements, estimates, APIs and data models, draw an architecture diagram, and submit it for review.
Pick a bundled problem or type your own idea, such as Car parking system, and generate a question around it. Reviews, follow-up chats and practice history stay in your local studio.
Install and start
pip install design-dojo
design-dojo
Open http://127.0.0.1:4317. To open the browser automatically:
design-dojo --open
Requires Python 3.10+ on macOS or Linux. The Python dependency nodejs-wheel-binaries supplies Node.js 22 and npm; no separate Node installation or source checkout is needed. That dependency's available platform wheels determine supported OS versions and architectures. Windows is not supported by this release.
The first start downloads locked server dependencies from npm, including a native SQLite module. This requires internet access and can take a few minutes. If a prebuilt SQLite binary is unavailable, compilation requires the platform's C/C++ build tools. Later starts reuse a versioned local runtime cache. The UI, problem banks, prompts and Maven project template are included in the package.
For Java coding, install JDK 21+ and prepare Maven/JUnit once:
design-dojo setup --java
System design practice does not require Java. For AI features, install and sign in to Claude Code, Codex CLI or Gemini CLI, then choose the provider in Settings. Generation and reviews send your problem, submitted work and relevant results to that provider and use your subscription or explicitly configured API key.
Commands
design-dojo # start the local server
design-dojo --port 4400 # use another port
design-dojo --open # start and open the browser
design-dojo setup # download/check server dependencies
design-dojo setup --java # also prepare Maven and JUnit
design-dojo doctor # local diagnostics; no AI request
design-dojo --version
python -m design_dojo --help
Data is stored in ~/.lld-practice-studio (override with LLD_STUDIO_HOME or --data-dir). Downloaded runtimes live in ~/.cache/design-dojo (override with DESIGN_DOJO_CACHE). Upgrading the package preserves your practice data.
Java code runs as your local OS user, without a security sandbox. Run only code you trust. AI feedback is a practice assessment. This application is designed for local single-user use.
The application includes third-party open-source components. Their notices are included in the runtime's THIRD_PARTY_NOTICES.txt.
Metadata
Release files for design-dojo 0.1.0
For a detailed explanation of source distributions (sdists) and built distributions (wheels), please see the package formats documentation.
Source distribution (sdist)
| File | Size | Uploaded | |
|---|---|---|---|
| design_dojo-0.1.0.tar.gz | 18.1 MB | Details |
Built distribution (wheel)
| File | Interpreter | ABI | Platform | Reset |
|---|---|---|---|---|
| design_dojo-0.1.0-py3-none-any.whl | Python 3 | none | any | Details |
Total release size: 36.2 MB
Release files / design_dojo-0.1.0.tar.gz
| Download URL | design_dojo-0.1.0.tar.gz |
|---|---|
| Size | 18.1 MB |
| Tags | Source |
|
SHA-256 checksum How to use checksums |
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| Upload date | |
|
Uploaded using Trusted Publishing? What is trusted publishing? |
No |
| Uploaded via |
twine/7.0.0 CPython/3.14.2
|
Release files / design_dojo-0.1.0-py3-none-any.whl
| Download URL | design_dojo-0.1.0-py3-none-any.whl |
|---|---|
| Size | 18.1 MB |
| Tags | Python 3 |
|
SHA-256 checksum How to use checksums |
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BLAKE2b-256 checksum How to use checksums |
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| Upload date | |
|
Uploaded using Trusted Publishing? What is trusted publishing? |
No |
| Uploaded via |
twine/7.0.0 CPython/3.14.2
|