"""ADR-0027 T3: Worker-wait generalization + orphan invariant.

Direct regression guard for ADR-0024 Phase B's kernel-greenlet orphan bug.
Phase 1 of ADR-0027: these tests fail against the current code (no
``_pending_worker_waits`` field, no worker-fork in ``ctx.wait``, no
scheduler drain). Phase 2 implements D0.1/D0.2/D0.4 and these pass.
"""
from __future__ import annotations

import os
import textwrap

import pytest
from greenlet import greenlet


# ── helpers ──────────────────────────────────────────────────────────


def _write_minimal_ccl_yaml(tmp_path) -> str:
    body = textwrap.dedent("""\
        defaults:
          algorithm: ring_allreduce_tcm
          buffer_kind: tcm
          backpressure: sleep
          n_slots: 4
          slot_size: 4096
          vc_chunk_size: 256
          ipcq_credit_size_bytes: 16

        algorithms:
          ring_allreduce_tcm:
            module: kernbench.ccl.algorithms.ring_allreduce
            topology: ring_1d
            buffer_kind: tcm
            n_elem: 8
    """)
    yaml_path = tmp_path / "ccl.yaml"
    yaml_path.write_text(body)
    return str(tmp_path)


def _make_ctx(topology):
    from kernbench.runtime_api.context import RuntimeContext
    from kernbench.runtime_api.types import DeviceSelector
    from kernbench.sim_engine.engine import GraphEngine

    engine = GraphEngine(topology.topology_obj, enable_data=True)
    return RuntimeContext(
        engine=engine,
        target_device=DeviceSelector("all"),
        correlation_id="test_t3",
        spec=topology.topology_obj.spec,
    )


# ── D0.1: _pending_worker_waits field exists ─────────────────────────


def test_pending_worker_waits_field_present(topology):
    """RuntimeContext must expose the deferred-wait queue (D0.1)."""
    with _make_ctx(topology) as ctx:
        assert hasattr(ctx, "_pending_worker_waits"), (
            "ADR-0027 D0.1: RuntimeContext must declare _pending_worker_waits"
        )
        assert ctx._pending_worker_waits == [], (
            "_pending_worker_waits should start empty"
        )


# ── T3.a / T3.b: wait defers + resume-after-drain contract ───────────


def test_wait_in_worker_defers_to_main_and_resumes_completed(topology):
    """T3.a + T3.b: worker ctx.wait enqueues + yields; resume → _completed.

    Direct test of D0.2 (worker-fork) + D0.3 resume invariant (handle must
    be in ctx._completed when worker resumes).
    """
    with _make_ctx(topology) as ctx:
        from kernbench.policy.placement.dp import DPPolicy

        # Worker that submits one tensor (which internally calls ctx.wait)
        # and records the pending-queue state observed before/after.
        observations: dict = {"pre_wait_len": None, "post_resume_completed": None}

        main = greenlet.getcurrent()

        def _worker():
            # Observation hook: patch ctx.wait to capture a single deferral.
            original_wait = ctx.wait

            def wrapping_wait(h, *, _meta=None):
                observations["pre_wait_len"] = len(ctx._pending_worker_waits)
                result = original_wait(h, _meta=_meta)
                observations["post_resume_completed"] = h in ctx._completed
                return result

            ctx.wait = wrapping_wait  # type: ignore[assignment]
            try:
                ctx.zeros(
                    (1, 8), dtype="f16",
                    dp=DPPolicy(cube="replicate", pe="replicate",
                                num_cubes=1, num_pes=1),
                    name="t3_defer",
                )
            finally:
                ctx.wait = original_wait  # type: ignore[assignment]

        g = greenlet(_worker)

        # Scheduler loop: run worker until it yields (or finishes), then drain.
        while not g.dead:
            g.switch()
            if not g.dead:
                # Worker yielded mid-wait → simulate D0.4 drain.
                from kernbench.runtime_api.multiprocessing import _drain_pending
                _drain_pending(ctx)

        assert observations["pre_wait_len"] is not None, "wait was not invoked"
        assert observations["post_resume_completed"] is True, (
            "D0.3 resume invariant: handle must be in ctx._completed on resume"
        )


# ── T3.c: multi-worker same-round drain ──────────────────────────────


def test_multiple_workers_resume_at_same_drain(topology):
    """T3.c: every worker yields before any drain; all resume together."""
    with _make_ctx(topology) as ctx:
        from kernbench.policy.placement.dp import DPPolicy

        dp = DPPolicy(cube="replicate", pe="replicate", num_cubes=1, num_pes=1)
        observations: list[int] = []

        def _make_worker(rank: int):
            def _entry():
                # Before its wait, observe queue state so we can assert that
                # *every* worker has enqueued before any drain happened.
                ctx.zeros((1, 4), dtype="f16", dp=dp, name=f"r{rank}")
                observations.append(rank)
            return _entry

        ws = 2
        gs = [greenlet(_make_worker(r)) for r in range(ws)]

        # Round 1: every worker runs up to its first (deferred) ctx.wait.
        for g in gs:
            g.switch()

        # After round 1, all workers should be paused (not yet dead) and
        # each should have enqueued at least one handle.
        assert all(not g.dead for g in gs), (
            "after round 1 switch, workers must be paused mid-wait, not dead"
        )
        assert len(ctx._pending_worker_waits) >= ws, (
            f"expected >= {ws} pending worker waits after round 1; "
            f"got {len(ctx._pending_worker_waits)}"
        )

        # Loop: drain + switch rounds until all workers complete. A single
        # ctx.zeros() call contains multiple yield points (MmuMap, then
        # MemoryWrite), so more than one round is needed.
        from kernbench.runtime_api.multiprocessing import _drain_pending
        rounds = 0
        while any(not g.dead for g in gs):
            _drain_pending(ctx)
            for g in gs:
                if not g.dead:
                    g.switch()
            rounds += 1
            assert rounds < 20, "scheduler did not converge within 20 rounds"

        assert all(g.dead for g in gs), "all workers should be dead after drain loop"
        assert sorted(observations) == list(range(ws))


# ── T3.d (핵심): kernel greenlet _parent is main ─────────────────────


def test_kernel_greenlet_parent_is_main(topology, tmp_path, monkeypatch):
    """T3.d orphan invariant: kernel_runner._parent must be main greenlet.

    This is the direct regression guard for ADR-0024 Phase B. Runs a worker
    that invokes torch.launch (which eventually spawns a kernel greenlet).
    The kernel_runner.run() captures greenlet.getcurrent() as _parent at
    spawn time — that value MUST be the main greenlet, else the orphan
    bug is back.
    """
    monkeypatch.chdir(_write_minimal_ccl_yaml(tmp_path))

    from kernbench.triton_emu import kernel_runner as kr_mod
    captured_parents: list = []
    main = greenlet.getcurrent()

    original_run = kr_mod.KernelRunner.run

    def _spy_run(self, env, kernel_fn, kernel_args, num_programs):
        gen = original_run(self, env, kernel_fn, kernel_args, num_programs)

        def _wrapping_gen():
            # yield from gen, but capture self._parent on first step
            try:
                value = next(gen)
                # First yield happens after _parent is set.
                captured_parents.append(self._parent)
                yield value
            except StopIteration:
                return
            yield from gen

        return _wrapping_gen()

    monkeypatch.setattr(kr_mod.KernelRunner, "run", _spy_run)

    # Drive a minimal ring_allreduce that launches a kernel inside a worker.
    import benches.ccl_allreduce as bench

    with _make_ctx(topology) as ctx:
        bench.run(ctx)

    assert captured_parents, "no kernel_runner.run invocations observed"
    for p in captured_parents:
        assert p is main, (
            f"ADR-0027 D0.7 / T3.d: kernel greenlet _parent must be main "
            f"greenlet; got {p!r} (main={main!r})"
        )


# ── T3.f: idempotency ────────────────────────────────────────────────


def test_wait_same_handle_twice_drives_engine_once(topology):
    """T3.f: ctx.wait(h) + ctx.wait(h) → engine.wait called once (D0.4-(3))."""
    with _make_ctx(topology) as ctx:
        from kernbench.policy.placement.dp import DPPolicy

        dp = DPPolicy(cube="replicate", pe="replicate", num_cubes=1, num_pes=1)
        call_count = {"n": 0}
        original_engine_wait = ctx.engine.wait

        def _counting_wait(h):
            call_count["n"] += 1
            return original_engine_wait(h)

        ctx.engine.wait = _counting_wait  # type: ignore[assignment]

        def _worker():
            ctx.zeros((1, 4), dtype="f16", dp=dp, name="t3f")
            # Manually pick a completed handle and wait twice.
            assert ctx._completed, "there should be at least one completed handle"
            h = next(iter(ctx._completed))
            before = call_count["n"]
            ctx.wait(h)
            ctx.wait(h)
            assert call_count["n"] == before, (
                "already-completed handle must not re-drive engine.wait"
            )

        g = greenlet(_worker)
        while not g.dead:
            g.switch()
            if not g.dead:
                from kernbench.runtime_api.multiprocessing import _drain_pending
                _drain_pending(ctx)


# ── T3.g: exception propagation + no further drain ───────────────────


def test_worker_exception_propagates_and_clears_pending(topology):
    """T3.g: worker raise → main propagates; _pending_worker_waits cleared."""
    with _make_ctx(topology) as ctx:
        from kernbench.runtime_api.multiprocessing import SpawnException

        def _bad_worker(rank: int):
            raise ValueError(f"rank {rank} intentional failure")

        with pytest.raises(SpawnException) as exc_info:
            ctx.multiprocessing.spawn(_bad_worker, args=(), nprocs=2)

        assert ctx._pending_worker_waits == [], (
            "D0.4-(4): _pending_worker_waits must be cleared on failure"
        )
        # Root-cause rank errors are present; sibling SystemExit not in dict.
        assert 0 in exc_info.value.errors or 1 in exc_info.value.errors


# ── T3.e: historical failure (pre-D0) — skipped per ADR ──────────────


@pytest.mark.skip(
    reason="ADR-0027 T3.e: historical failure mode — reproduces only "
           "pre-D0.2. Kept as documentation; not run in Phase 2."
)
def test_pre_d0_orphan_reproduction():
    """Placeholder: exercises the pre-D0.2 code path that causes GreenletExit
    from kernel_runner._parent captured in worker context. See ADR-0024
    Phase B postmortem."""
    pass