Most Python exceptions come with a traceback that points you toward the problem. A segmentation fault is different: the process simply crashes with "Segmentation fault (core dumped)." For anyone who has dealt with this, what steps do you usually take to find the cause and debug it?
4 Answers
It’s also worth checking for resource or system problems, especially if the crash happens while allocating large objects. Confirm available memory and consider running a memory test, but don’t assume that every segfault is simply an out-of-memory condition. Tools such as strace can provide additional clues about what the process was doing immediately before it died.
Start by enabling Python’s built-in faulthandler module. It can print a traceback when the interpreter crashes and often shows which Python call led into the failing native code.
If faulthandler doesn’t narrow it down, use a native debugger such as GDB. Python’s GDB integration is useful for identifying the Python frame and the underlying C function that crashed, although it can take some patience to work through.
A Python-level segfault usually points to something outside ordinary Python code: a C extension, a native dependency, Cython, or occasionally an interpreter bug or stack overflow. Libraries involving numerical computing, graphics, and vendor-specific integrations are common suspects. Valgrind or similar memory-checking tools can help find invalid or freed-memory accesses.
That matches my experience too—when this happens, I’d first isolate or disable native extensions rather than looking for a normal Python exception.