Python for Embedded Systems

Exploring Python's Role in Embedded Systems: Applications, Benefits, and How It Complements C and C++ for Efficient Embedded Development
Python is a popular programming language known for its simplicity and versatility. Python is the go-to language for Machine Learning (ML) and Generative AI developers. Python has developed over the years into a language that supports all the required constructs from higher-level languages like Java. In its initial days, it was mostly used for scripting, but with extensive library support, frameworks like Django, and support for object-oriented programming, it is now used in a wide variety of applications—from scripting, automation, ML applications, to web applications, to name a few. However, its role in embedded systems is a topic of interest for many aspiring engineers. In this blog, we’ll explore whether Python is required for embedded systems and its applications in this field.

Role of Python in Embedded Systems

Python is not traditionally the primary language for embedded systems, which often rely on languages like C or C++ due to their low-level capabilities and efficiency. Python runs on an interpreter, which does not need any compilation to run the code, whereas languages like C, C++ need a compiler toolchain to generate machine code that runs on a system. However, Python has found its place in certain aspects of embedded systems development. MicroPython or Python is available in almost all the embedded systems that run Linux or most Linux flavors.

  • Prototyping: Python is excellent for rapid prototyping and testing ideas before implementing them in a higher performance-oriented language. Its simplicity and readability make it ideal for quickly developing and iterating on concepts. You could partition the functionality into Python and C/C++, such that Python code could call on C/C++ for time-critical parts of the application.

  • Scripting: Python is used for writing scripts to automate tasks, test hardware, and manage system configurations. These scripts can simplify the development process and enhance productivity.

  • High-Level Applications: Python is suitable for developing high-level applications that interact with embedded systems, such as user interfaces, web applications, and data processing tools. These applications can run on external devices or systems that communicate with the embedded device.

  • Tiny ML Applications: Python, being the goo language for ML developers, is used in applications where ML models are customized to run on low-end microcontrollers.

Advantages of Python

Using Python in embedded systems offers several advantages:

  • Ease of Use: Python’s simple syntax and readability make it accessible for beginners and efficient for experienced developers, reducing development time and effort. With high-performance compute and memory becoming cheaper, you might still be able to meet the required speed with Python code. An appropriate analysis is required to verify this.

  • Large Libraries: Python has a vast ecosystem of libraries and frameworks that can speed up development, including libraries for data analysis, machine learning, and hardware interfacing.

  • Community Support: Python’s large community provides extensive resources, tutorials, and support, making it easier to find solutions to common problems and learn new techniques.

Limitations of Python

Despite its benefits, Python has some limitations in embedded systems:

  • Performance: Python is an interpreted language and may not offer the same performance as compiled languages like C or C++, especially in resource-constrained environments where execution speed is critical.

  • Memory Usage: Python’s higher memory footprint can be a concern in resource-constrained embedded environments, where efficient memory usage is essential.

When to Use Python

Python is ideal for certain scenarios in embedded systems:

  • Development Boards: Platforms like Raspberry Pi and MicroPython-compatible boards leverage Python for educational and prototyping purposes. These boards are often used in hobbyist projects, education, and initial product development.

  • Testing and Automation: Python is effective for writing test scripts and automation tools in embedded systems development. These tools can streamline testing processes, simulate various scenarios, and ensure reliability.

  • High-Level Interfaces: Python can be used for creating user interfaces or data processing/analytics required in IoT or managing communication between the embedded system and other applications. For example, a Python-based GUI might control an embedded system via a serial interface or network connection.

Conclusion

Python offers valuable benefits in specific use cases like prototyping, scripting, and high-level application development. While traditional languages like C and C++ remain dominant in embedded systems, Python’s ease of use and versatility make it a useful tool for certain aspects of development. Over the long term, as compute and memory become cheaper, Python might become the go-to language in embedded systems as well. Understanding when and how to use Python can enhance productivity and efficiency in embedded systems projects. As the field evolves, the role of Python in embedded systems may continue to grow, particularly in areas where its strengths align with project requirements.