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Python signal handlers crash when print is reentered under rapid signal bursts
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Calling `print` in a Python signal handler can trigger a runtime error if the handler is reentered during execution
Signal handlers are meant to be minimal and reentrancy-safe. While Python relaxes some C-level restrictions, this edge case shows that even simple operations like `print` can fail under extreme conditions. Engineers writing signal handlers should avoid non-atomic operations to prevent unexpected crashes.
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Python signal handlers are reentrant, meaning they can be interrupted and called again before finishing
Rapid signal bursts can cause `print` in a signal handler to trigger a `RuntimeError` due to reentrancy
The failure is rare but demonstrates that even basic I/O operations may not be safe in signal handlers
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Python signal handlers differ from C signal handlers in that they are not executed immediately within the low-level signal context. Instead, Python defers execution until the interpreter is in a consistent state. This design relaxes some of the strict restrictions imposed on C signal handlers, where only a limited set of async-signal-safe functions can be called. However, Python’s approach does not eliminate all risks, particularly around reentrancy.
The test case demonstrates that when a signal handler is called repeatedly in rapid succession, it can be reentered while still executing. If the handler contains a call to `print`, this reentrancy can lead to a `RuntimeError` because the underlying I/O operations are not atomic. The error occurs when the interpreter detects that the same `BufferedWriter` is being accessed concurrently, which violates Python’s internal consistency rules.
While this failure mode is unlikely in typical applications, it highlights a broader principle: signal handlers should remain minimal and avoid non-atomic operations. Even seemingly safe functions like `print` can introduce instability under extreme conditions. Engineers should treat signal handlers as a mechanism for setting flags or triggering deferred work, rather than performing I/O or other complex tasks directly.
The practical impact of this issue is limited, as the conditions required to trigger it, rapid, repeated signals, are uncommon in production environments. However, the behavior serves as a reminder that Python’s signal handling, while more forgiving than C’s, still has edge cases that can lead to crashes. For critical applications, it may be worth avoiding `print` in signal handlers or using thread-safe alternatives for logging.
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