Python Proxy Checks: Why Future.cancel() Leaves Threads Running
Understand why cancelling pending futures does not stop active network checks, and bound a proxy race without claiming it proves destination health.
One worker finds a usable proxy. You return its address, call cancel on the other futures, and expect the network activity to stop. It may not.
A Future can be cancelled before its callable starts. Once a thread is already executing a request, cancelling its Future does not interrupt that socket operation. The worker needs its own bounded network operation and cleanup path.
The executor's lifetime matters too. Leaving a ThreadPoolExecutor context waits for its work to finish. Finding one quick result and then waiting for several slow workers can make the caller's total delay look nothing like the winner's reported latency.
Bound the race before starting it
- Limit the number of simultaneous checks instead of submitting an unbounded public list. The free proxy list provides candidates for the checker's input, with each endpoint's protocol kept for the worker.
- Give each request an appropriate connection and read policy.
- Give the caller an overall decision budget.
- Define who drains or closes results from workers that outlive the decision.
Waiting less for a Future is not the same as making its underlying request shorter. Likewise, abandoning the result does not release every network resource immediately.
The first successful result is also only the first successful check. It can depend on scheduling, cached connections, and the particular check destination. It does not establish that the endpoint is universally the fastest or that the real task will succeed.
Often a small retained pool with recent observations is simpler than racing the entire list before every download. Use the real operation's result to update the record, with a controlled recovery policy for failures. The preflight should earn its cost rather than doubling every task by habit.