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Start by identifying every process and thread involved, then compare their states over time. Use /proc and wait channels for a quick snapshot, strace to see system calls across workers, and GDB or Python traceback dumps for call stacks. A blocked process or thread shows where it is waiting; it does not, by itself, prove a deadlock. To diagnose one, establish which dependency or missing event prevents the participants from progressing.

1. Establish which processes and threads are involved

Record the command, start time, parent PID, child PIDs, thread counts, and CPU use. Also check whether logs or output are still changing. Take at least two snapshots a short interval apart: one snapshot cannot show whether a process has stopped making progress.

Linux exposes each running process through /proc/PID. Its task directory contains one subdirectory per thread, named with that thread’s TID. The following commands provide a useful starting view; replace PID in the second command with the process ID you are investigating.

ps -eo pid,ppid,tid,stat,wchan:24,etime,pcpu,comm --forest
ls /proc/PID/task

The ps columns available can vary with the procps version. If a column is unavailable, inspect the corresponding kernel interface under /proc/PID/task/TID.

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2. Read wait channels as clues, not explanations

Inspect /proc/PID/wchan or a thread’s /proc/PID/task/TID/wchan to see the symbolic kernel location where that task is sleeping. A wait channel can help distinguish a thread asleep in a kernel wait from one actively consuming CPU. It does not identify the application-level lock, queue, or condition involved.

Access to wchan is subject to a ptrace access check. Your user permissions or container policy may prevent reading it. Treat the value as a clue to correlate with traces, stacks, and application state—not as a diagnosis on its own.

3. Trace system calls across the parent and workers

Use strace when you need to see what processes and threads are doing at the system-call level. Attaching with -f follows processes created through fork, vfork, and clone, and also attaches to threads of a multithreaded target. With -ff, trace output is written to separate files for each process.

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strace -ff -tt -T -p PID -o /tmp/trace

Replace PID with the parent process ID. Correlate each resulting trace file with its PID and with application logs. Look for an unfinished system call or repeated waits involving operations such as read, write, futex, or wait. This can reveal where progress is blocked—for example, a worker waiting for input or a parent waiting for a child—but the trace still needs to be interpreted in the context of the program’s dependencies.

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Tracing is somewhat intrusive and can alter timing. Use it deliberately on performance-sensitive production workloads. The strace(1) manual describes the tool as useful for diagnosis, instruction, and debugging.

4. Capture native stacks when syscall traces are not enough

A system-call trace may show that a thread is waiting without revealing the code path that led there. GDB can attach to a running process and show its current call stack.

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gdb -p PID

After attaching, use bt to display a backtrace. Inspect relevant threads and compare stacks across worker processes. A stack can show a thread waiting inside application or library code, including a synchronization routine, but one stack snapshot generally does not establish who owns a lock or why that owner cannot proceed. Compare it with peer stacks and application-level ownership or event information.

5. Capture Python thread tracebacks for intermittent hangs

For Python multiprocessing programs, faulthandler.dump_traceback_later(timeout) can schedule a traceback dump after a timeout and repeat it if requested. Configure it before a failure when a hang is intermittent or difficult to reproduce at the console.

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import faulthandler
faulthandler.dump_traceback_later(60, repeat=True)

Keep the output file open until the dump has been written, or cancel the scheduled dump when it is no longer needed. Use this in a diagnostic build or guarded startup path. These dumps show Python frames; if a thread is blocked in native code, use syscall tracing or GDB as well. In the Python 3.14 documentation, free-threaded operation with the GIL disabled has a special case: to avoid data races, the dump includes only the current thread.

6. Check Python multiprocessing joins and queues

Drain queued data before waiting for a child to finish

The Python multiprocessing documentation describes a deadlock pattern in which a child puts a large payload on a queue and the parent calls join() before reading the queued data. The child may be unable to finish flushing its queue item while the parent waits for the child. Drain the queue before joining, or remove the premature join, so the child can complete its work.

Check the outcome of timed joins explicitly

Process.join(timeout) returns None both when the process has ended and when the timeout expires. Do not treat the return value as an outcome code: check exitcode or is_alive() afterward. For each process, review its liveness, exit code, and whether joins have a timeout.

Capture evidence before terminating workers

Terminating a process while it owns a lock or semaphore can leave other processes deadlocked. Termination can also corrupt a pipe or queue that is in use. Before killing a worker, capture the available traces or stacks and check which shared resources it may hold.

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7. Decide whether the evidence supports a deadlock diagnosis

A hang means expected progress is not occurring. A deadlock is a more specific causal diagnosis: participants are waiting on conditions that cannot be satisfied because of their dependency relationships. A stable blocked state is evidence of waiting, not proof of that cycle.

Consider other explanations before concluding that a deadlock exists:

  • Work is slow but still progressing.
  • A worker is blocked on an external service.
  • The process has exhausted file descriptors.
  • A queue has lost its consumer.
  • A child crashed while the parent is waiting for it.
  • A worker is waiting for a resource held by a task that is still progressing.

Build the causal picture by comparing repeated snapshots, traces, and stacks with application-level ownership or event logs. Look for the specific dependency cycle or unmet event that prevents progress. No single tool in this workflow automatically establishes that cause.

Which diagnostic method should you use?

Method Evidence Best use Limit
/proc/PID/task/TID and wchan Thread inventory and symbolic kernel sleep location Quick host-side snapshot Access may be restricted; the wait location does not explain the application-level cause. (Linux procfs documentation)
strace -f System-call and signal history across descendants and threads Finding kernel waits, missing reads or writes, and process wait patterns Tracing can affect timing and performance. (The strace(1) manual)
GDB backtrace Native call stacks in a running process Seeing where threads are blocked in application or library code Attachment permissions and symbols matter; a stack is a snapshot, not a causal graph. (GDB documentation)
Python faulthandler Python thread tracebacks after a timeout Capturing intermittent Python-level stalls Native waits may need other tools; behavior differs in free-threaded configurations. (Python 3.14 documentation)

Choose the least intrusive method that can answer the question you have. A process-and-thread snapshot can identify the participants; syscall traces can reveal kernel interactions; stacks can show code paths; and application logs or instrumentation can help establish ownership and event dependencies. Commands and interface details may vary by distribution and tool release, and debugger or tracer access may be restricted by user identity, ptrace settings, or container policy.

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