WebAssembly (Wasm) can be a powerful tool for extending Python applications, offering a more flexible approach than traditional C-based extensions. Python usually relies on native code to access functionalities beyond its built-in capabilities, but using Wasm allows for architecture-independent binaries that don't require a native toolchain on the host system. While Wasm excels in providing performance improvements, it has limitations. For instance, Wasm runs in a sandbox and cannot directly access external interfaces, which constrains its use for certain types of extensions. For practical implementation, wasmtime-py is highlighted as the most user-friendly option for running Wasm in Python. It supports major operating systems and architectures, meaning users only need a Python interpreter to get started. However, it comes with drawbacks; the library is about 18MiB in size and has an unstable API that frequently breaks. The author notes significant performance gains—3x to 10x faster than alternatives—but emphasizes the ongoing maintenance burden due to constant updates. The article also identifies common pitfalls when using wasmtime-py. For example, the interface requires passing a store parameter frequently, which can lead to confusion. There’s a risk of pointer-related errors due to the way Wasm handles memory, particularly with signed integers. A common mistake involves using negative indices when writing to memory, which can lead to buffer overflows. To mitigate these risks, the author recommends masking pointers to ensure they are treated as unsigned integers. Additionally, using Python's struct package can facilitate memory management when transferring data between Python and Wasm, but one must be cautious about endianness. Overall, while there are challenges in using Wasm with Python, the potential speed and flexibility make it a compelling option for certain applications.