This devcontainer configuration enables running FastLED development in the cloud using GitHub Codespaces or Gitpod.

1. Navigate to the FastLED repository
2. Click Code → Codespaces → Create codespace on main
3. Wait 2-3 minutes for the container to build
4. Start developing! All dependencies are pre-installed

Click this button or visit https://gitpod.io/#https://github.com/FastLED/FastLED:

• Python 3.11 with uv package manager
• PlatformIO for embedded development
• C++ toolchain (clang, gcc, ninja, meson)
• QEMU for ESP32 emulation
• VS Code extensions:
  • PlatformIO IDE
  • Python + Pylance
  • C/C++ tools

All commands from the main repo work in the cloud environment:

# Run unit tests
uv run test.py

# Run C++ tests only
uv run test.py --cpp

# Run QEMU emulation tests
uv run test.py --qemu esp32s3

# Compile for specific platforms
uv run ci/ci-compile.py uno --examples Blink
uv run ci/ci-compile.py esp32s3 --examples Blink

# Lint code
bash lint

# Compile WASM
uv run ci/wasm_compile.py examples/Blink --just-compile

Cloud environments cannot access physical USB devices, so:

• ✅ Full compilation support for all 50+ platforms
• ✅ Unit tests run perfectly
• ✅ QEMU emulation for ESP32 testing
• ✅ WASM compilation and testing
• ❌ Physical device flashing requires local setup

For FastLED development, QEMU emulation provides excellent hardware validation without physical devices.

• Build speed: Cloud instances use 2-4 cores (free tier)
• Caching: PlatformIO cache is mounted for faster rebuilds
• First build: May take 5-10 minutes for initial dependency downloads
• Subsequent builds: Much faster due to caching

• Free tier: 120 core-hours/month (60 hours on 2-core)
• Paid tier: $0.18/hour for 4-core after free tier

• Free tier: 50 hours/month
• Paid tier: $0.36/hour for standard workspace

• Check that Python 3.11 feature is properly specified
• Ensure Dockerfile has correct base image

• Run pio --version to verify installation
• Try reinstalling: pip install --upgrade platformio

• First build takes longer - wait for complete dependency installation
• Check internet connection for package downloads
• Review test output for specific errors

To use this devcontainer locally with VS Code:

1. Install Docker Desktop
2. Install "Dev Containers" VS Code extension
3. Open FastLED folder in VS Code
4. Press F1 → "Dev Containers: Reopen in Container"

This devcontainer configuration is designed for cloud-based FastLED development. If you encounter issues or have improvements, please open an issue or PR on the FastLED repository.