Choosing Between C++ and Python in ROS 2: Deployment and Compilation

From the perspective of convenience, I believe Python has significant advantages. Here is a detailed analysis:

1. Python Does Not Require Compilation, Simplifying the Deployment Process

Core Advantages

• • Python is an interpreted language,<span>.py</span> code files can be run directly on devices with a Python interpreter and ROS 2 dependencies installed,completely eliminating the need for a compilation step
• • There is no need to install compilers (<span>gcc</span>, <span>g++</span>), build tools (<span>colcon</span>, <span>cmake</span>), and related libraries on the robot, reducing system complexity
• • Code written on the development machine can be directly copied to the robot for execution (given dependency compatibility), avoiding the cumbersome process of “compile → deploy”
• • Suitable for resource-constrained embedded robots, as it does not incur CPU/memory overhead from the compilation process

Comparison with C++

• • C++ must be compiled into machine code before it can run
• • If compiling on the robot: a complete toolchain must be installed, which has hardware performance requirements, and large projects can take a long time to compile
• • If cross-compiling: a complex environment must be configured, resolving library dependencies and architecture compatibility issues, which requires high developer experience
• • Code modifications require recompilation, making iteration efficiency lower than Python

2. Suitable Scenarios: Lightweight Deployment and Rapid Iteration

The “no compilation” advantage of Python is particularly prominent in the following scenarios:

• • Small Robots/Embedded Platforms: such as Raspberry Pi, Jetson Nano, etc., saving storage space and system resources
• • Rapid Validation Scenarios: algorithm prototype development, functionality demonstrations, short-term projects, etc., supporting frequent modifications and immediate testing
• • Non-Real-Time Modules: such as data logging, parameter configuration, high-level decision logic (non-millisecond response)

3. Limitations of Python (Even Without Considering Compilation Issues)

• • Performance Bottlenecks: high-frequency data processing (above 100Hz), real-time control loops may experience excessive delays due to interpreted execution
• • Dependency Management: must ensure that the Python version and libraries (such as <span>numpy</span>, <span>opencv-python</span>) on the robot are consistent with those on the development machine
• • Limited Support for ROS 2 Features: advanced features like custom memory management and zero-copy transport are not as well supported as in C++

4. Compromise Solution: Mixed Programming

ROS 2 node communication is language-agnostic, allowing the combination of the advantages of both:

• • Python: implement modules that require no compilation and allow for rapid iteration (data visualization, high-level decision-making, tool scripts)
• • C++: implement core modules with high performance/real-time requirements (sensor data processing, motion control), which can be reused after a single cross-compilation

Conclusion

If the core requirement is to “avoid setting up a compilation environment on the robot or cross-compiling,”Python is the better choice, especially suitable for lightweight and rapid iteration scenarios. For performance-sensitive modules, C++ can be combined to balance deployment complexity and system performance.

In short: “Wherever Python can run, prioritize using Python to simplify deployment; where Python cannot perform, then use C++ to solve performance issues”.