This post describes Frameworks Similar to rpi-app-framework. The rpi-app-framework is a lightweight, modular framework for Raspberry Pi applications, emphasizing hardware abstraction, logging, and cross-platform compatibility between MicroPython (Pico) and Python (full RPi). Below are similar frameworks, grouped by focus, with key similarities and differences.
General IoT/Embedded Frameworks
CircuitPython
- Description: Adafruit’s MicroPython fork, optimized for hardware interaction on RPi Pico, RPi 4/5, and other boards. It includes libraries for GPIO, PWM, I2C/SPI, and hardware like NeoPixels or servos.
- Similarities: Cross-platform hardware abstraction (e.g., unified Pin/PWM API), easy logging, and simple app structure for embedded projects. Supports all RPi versions with device-specific drivers.
- Differences: More focused on libraries than app lifecycle management; no built-in logging or file rotation like RPIApp. Less emphasis on web/networking out-of-the-box.
- Use Case: Ideal for quick hardware prototypes; install via UF2 file on Pico.
MicroPython Core Libraries
- Description: The standard MicroPython libraries for RPi Pico, including machine for GPIO/PWM, network for WiFi, and uasyncio for async I/O. Extended by community packages like umqtt for MQTT.
- Similarities: Native support for all RPi Pico models, hardware managers (e.g., Pin, PWM), and async networking. Modular like DeviceManager for building custom drivers.
- Differences: No high-level app framework (no RPIApp-like lifecycle); developers build everything from scratch. Lacks cross-platform (full RPi) support without additional wrappers.
- Use Case: Bare-metal scripting; extend with your framework for structured apps.
RPi-Specific Frameworks
gpiozero
- Description: High-level Python library for RPi GPIO, supporting LEDs, motors, sensors, and buttons on full RPi models. Includes recipes for common tasks like traffic lights or robots.
- Similarities: Hardware abstraction (e.g., unified LED/Motor classes), simple object-oriented design like DeviceManager. Supports PWM and state tracking (e.g., motor speed).
- Differences: Python-only (no MicroPython/Pico support); no app lifecycle or logging framework. Less emphasis on networking/web (e.g., no WiFiManager equivalent).
- Use Case: Full RPi hardware control; integrate with RPIApp for complete apps.
pigpio
- Description: Low-level GPIO library for full RPi, providing daemon-based control for PWM, I2C, SPI, and remote GPIO access. Supports daemon mode for concurrent access.
- Similarities: Precise PWM/servo control like MotorDriverTB6612FNG; daemon for multi-process apps.
- Differences: C-based daemon with Python bindings; no high-level app structure or logging. Not for MicroPython/Pico; focused on full RPi precision timing.
- Use Case: High-precision GPIO on full RPi; wrap in DeviceManager for framework integration.
Web/Networking Frameworks for RPi
Microdot
- Description: Minimalist web framework for MicroPython (Pico) and Python, with async support via microdot_asyncio. Handles routes, JSON, and static files.
- Similarities: Lightweight web server like MicrodotManager; async for concurrent I/O. Integrates well with RPIApp for web-enabled apps.
- Differences: Web-focused only (no hardware abstraction); no logging or app lifecycle. Requires manual WiFi setup (pair with WiFiManager).
- Use Case: Embedded web interfaces; use MicrodotManager in RPIApp for full integration.
Flask (for Full RPi)
- Description: Full-featured Python web framework for full RPi, with routing, templates, and extensions for GPIO integration (e.g., Flask-Restful for APIs).
- Similarities: Route-based web apps like MicrodotManager; extensible for hardware via plugins.
- Differences: Heavyweight (not for Pico/MicroPython); no embedded hardware support out-of-the-box. Pair with gpiozero for GPIO control.
- Use Case: Complex web apps on full RPi; use RPIApp for hardware layer.
Robotics/Full-Stack Frameworks
donkeycar
- Description: Open-source framework for building self-driving cars on RPi 4/5 with Python, including motor control, camera, and ML models.
- Similarities: Motor driver abstraction (similar to MotorDriverTB6612FNG); modular hardware managers for sensors/motors.
- Differences: Robotics-specific (car focus); no MicroPython/Pico support. Heavy on ML/CV, less on logging/app lifecycle.
- Use Case: Autonomous vehicles on full RPi; extend with RPIApp for general robotics.
ROS2 for RPi (Robot Operating System)
- Description: Distributed robotics framework with Python nodes for full RPi, supporting GPIO, motors, and networking.
- Similarities: Modular nodes for hardware (like DeviceManager); pub/sub for communication.
- Differences: Complex, resource-intensive; no MicroPython/Pico support. Focuses on robotics middleware, not simple app structure.
- Use Case: Advanced robotics on full RPi; integrate RPIApp for simpler hardware control.
Summary
These frameworks complement rpi-app-framework by focusing on specific areas (e.g., web in Microdot, GPIO in gpiozero, robotics in donkeycar), but none offer the unified app lifecycle, cross-platform hardware abstraction, and logging in a single lightweight package. For Pico-focused projects, pair Microdot with your framework; for full RPi robotics, combine with gpiozero or ROS2.