archived-matedroid/docs/DEVELOPMENT.md

Development

Notes on development methodology

This project was completely vibe-coded, 100%, with the help of Claude Code and Opus 4.5. There it is, I said it, the shame is now gone.

I am/was pretty skeptical on LLM-generated code and this was born as an experiment to learn how it actually was to vibe-code something from scratch.

Turns out it's pretty awesome and easy to follow the happy path for a stock, modern Android app which just displays data consumed from a JSON REST API. I'm a DevOps guy and I have zero mobile development skills, so achieving this can be considered pretty awesome in my book. But I'm pretty sure in the eyes of a skilled Kotlin Android developer, this code might induce different feelings.

At the moment, I completely depend on CC to maintain the app, but I would like to take this opportunity as an excuse to learn more about the Android development ecosystem, beside learning how to tame an LLM agent.

Project Structure

matedroid/
├── app/src/main/java/com/matedroid/
│   ├── data/           # Data layer (API, repository, local storage)
│   ├── domain/         # Domain layer (models, use cases)
│   ├── ui/             # UI layer (screens, components, theme)
│   └── di/             # Dependency injection modules
├── gradle/             # Gradle wrapper and version catalog
├── util/               # Utility scripts
├── ASSETS.md           # Tesla car image asset documentation
└── PLAN.md             # Detailed implementation plan

Tech Stack

• Language: Kotlin
• UI: Jetpack Compose with Material Design 3
• Architecture: MVVM + Clean Architecture
• DI: Hilt
• Networking: Retrofit + OkHttp + Moshi
• Local Storage: DataStore
• Charts: Vico
• Maps: osmdroid (OpenStreetMap)

Utility Scripts

util/fetch_tesla_assets.py

Python script to download Tesla car 3D renders from Tesla's compositor service. Requires uv for dependency management.

# Download all car images (Model 3 & Y, various colors/wheels)
./util/fetch_tesla_assets.py

# Preview what would be downloaded
./util/fetch_tesla_assets.py --dry-run

# Custom output directory
./util/fetch_tesla_assets.py --output-dir /path/to/assets

See ASSETS.md for detailed documentation on Tesla compositor APIs, color/wheel code mappings, and troubleshooting.

Running Tests

# Unit tests
./gradlew test

# Instrumented tests (requires emulator/device)
./gradlew connectedAndroidTest

Releasing

Releases are automated via GitHub Actions. When a release is published, the workflow builds the APK and attaches it to the release.

# 1. Update version in app/build.gradle.kts (versionCode and versionName)
# 2. Update CHANGELOG.md with release notes
# 3. Commit and push

# 4. Create a release with GitHub CLI
gh release create v0.5.0 --generate-notes

# Or create a draft release to edit notes first
gh release create v0.5.0 --generate-notes --draft

Signing Configuration (Optional)

For release signing with a custom keystore, set these repository secrets:

• KEYSTORE_BASE64: Base64-encoded keystore file (base64 -w0 your.keystore)
• KEYSTORE_PASSWORD: Keystore password
• KEY_ALIAS: Key alias
• KEY_PASSWORD: Key password

Without secrets, the APK is signed with a debug keystore (fine for sideloading, not for Play Store).

Development Workflow

1. Start your Android emulator or connect a device
2. Build and install: make install
3. View logs: adb logcat | grep -i matedroid

Makefile Targets

Target	Description
make build	Build debug APK
make install	Build and install debug APK on connected device
make run	Build, install, and launch the app
make clean	Clean build artifacts
make test	Run unit tests

Or use Android Studio:

1. Open the project folder
2. Wait for Gradle sync
3. Click Run (green play button)

Configuration

On first launch, you'll be prompted to configure your TeslamateApi connection:

1. Server URL: Your TeslamateApi instance URL (e.g., https://teslamate-api.example.com)
2. API Token: (Optional) If your instance requires authentication