feat(python): make Permutation fork-safe for PyTorch DataLoader workers (#3339)

## Summary

PyTorch's `DataLoader` uses fork-based multiprocessing by default on
Linux, but threads do not survive `fork()`. LanceDB's Python bindings
drive async work through two threaded layers, both of which become inert
in a forked child:

- `BackgroundEventLoop` runs an asyncio loop on a Python
`threading.Thread`.
- `pyo3-async-runtimes::tokio` holds a global multi-threaded tokio
runtime whose worker threads also die on fork — and its runtime lives in
a `OnceLock` that cannot be replaced after first use.

As a result, any `Permutation` (or other async API) used inside a
fork-based `DataLoader` worker hangs indefinitely. This PR makes both
layers fork-safe so `Permutation` works as a `torch.utils.data.Dataset`
with `num_workers > 0`.

## Approach

### Rust — new `python/src/runtime.rs`

Mirrors the pattern used in [Lance's Python
bindings](456198cd6f/python/src/lib.rs (L139)),
adapted for the async-bridge use case.

- `LanceRuntime` implements `pyo3_async_runtimes::generic::Runtime +
ContextExt`, backed by an `AtomicPtr<tokio::runtime::Runtime>` we own
(sidestepping `pyo3-async-runtimes`'s frozen `OnceLock` global).
- A `pthread_atfork(after_in_child)` handler nulls the pointer; the next
`spawn` rebuilds the runtime in the child. The previous runtime is
intentionally **leaked** — calling `Drop` would try to join now-dead
worker threads and hang.
- `runtime::future_into_py` is a drop-in for
`pyo3_async_runtimes::tokio::future_into_py`. All ~80 call sites in
`arrow.rs` / `connection.rs` / `permutation.rs` / `query.rs` /
`table.rs` are updated to route through it.
- `python/Cargo.toml` adds `libc = "0.2"` and the tokio
`rt-multi-thread` feature.

### Python — `lancedb/background_loop.py`

- Refactors `BackgroundEventLoop.__init__` to a reusable `_start()`
method.
- An `os.register_at_fork(after_in_child=…)` hook calls `LOOP._start()`
to give the singleton a fresh asyncio loop and thread **in place**. This
matters because the rest of the codebase imports `LOOP` via `from
.background_loop import LOOP` — rebinding the module attribute would
leave those references holding the dead loop.

### Python — `lancedb/__init__.py`

Removes the `__warn_on_fork` pre-fork warning (and the now-unused
`import warnings`). Fork is supported.

## Test plan

- [x] New `test_permutation_dataloader_fork_workers` in
`python/tests/test_torch.py`: runs a `Permutation` through
`torch.utils.data.DataLoader(num_workers=2,
multiprocessing_context="fork")` inside a spawn-isolated child with a
30s hang detector. **Pre-fix**: timed out at 36s. **Post-fix**: passes
in ~3.6s.
- [x] New `test_remote_connection_after_fork` in
`python/tests/test_remote_db.py`: forks a child that creates a fresh
`lancedb.connect(...)` against a mock HTTP server and calls
`table_names()`; passes in <1s, validates the runtime reset is
sufficient for fresh remote clients.
- [x] All 62 tests in `test_torch.py` + `test_permutation.py` pass.
- [x] All 35 tests in `test_remote_db.py` pass.
- [x] `test_table.py` (87) + `test_db.py` + `test_query.py` (157, minus
one unrelated `sentence_transformers` import skip) — 244 passing.
- [x] `cargo clippy -p lancedb-python --tests` clean.
- [x] `cargo fmt`, `ruff check`, `ruff format` all clean.

## Known limitation (follow-up)

This PR makes a **freshly-built** `lancedb.connect(...)` work in a
forked child. An **inherited** `Connection` from the parent still
carries an inherited `reqwest::Client` whose hyper connection pool
references socket FDs and TCP/TLS state shared with the parent — using
it from the child after fork is unsafe (especially with HTTP/1.1
keep-alive). The recommended pattern for fork-based `DataLoader` workers
that hit a remote DB is to construct a new connection inside the worker.
Auto-clearing inherited HTTP client pools on fork would require tracking
live `Connection` instances in `lancedb` core and is left for a
follow-up PR.

🤖 Generated with [Claude Code](https://claude.com/claude-code)

---------

Co-authored-by: Claude Opus 4.7 (1M context) <noreply@anthropic.com>

python/python/tests/test_torch.py

@@ -2,13 +2,15 @@
 # SPDX-FileCopyrightText: Copyright The LanceDB Authors
 
 import functools
+import multiprocessing as mp
 import pickle
+import sys
 
 import lancedb
 import pyarrow as pa
 import pytest
-from lancedb.util import tbl_to_tensor
 from lancedb.permutation import Permutation, Permutations, permutation_builder
+from lancedb.util import tbl_to_tensor
 
 torch = pytest.importorskip("torch")
 
@@ -146,3 +148,63 @@ def test_permutation_with_builder_is_picklable(tmp_db):
 
     assert len(restored) == len(permutation)
     assert restored.__getitems__(indices) == expected
+
+
+def _multiworker_dataloader_target(db_uri: str, result_queue):
+    import lancedb
+    from lancedb.permutation import Permutation
+
+    db = lancedb.connect(db_uri)
+    table = db.open_table("test_table")
+    permutation = Permutation.identity(table)
+
+    dataloader = torch.utils.data.DataLoader(
+        permutation,
+        batch_size=10,
+        num_workers=2,
+        multiprocessing_context="fork",
+    )
+    count = 0
+    for batch in dataloader:
+        assert batch["a"].size(0) == 10
+        count += 1
+    result_queue.put(count)
+
+
+@pytest.mark.skipif(
+    sys.platform != "linux",
+    reason=(
+        "fork() is unavailable on Windows and unsafe on macOS "
+        "(Apple frameworks/TLS are not fork-safe)"
+    ),
+)
+def test_permutation_dataloader_fork_workers(tmp_path):
+    """A Permutation used by a fork-based DataLoader should not hang.
+
+    PyTorch's DataLoader uses fork-based multiprocessing by default on Linux.
+    LanceDB drives async work through a background asyncio thread that does
+    not survive a fork, so any LOOP.run() in a worker blocks forever.
+    """
+    import lancedb
+
+    db_uri = str(tmp_path / "db")
+    db = lancedb.connect(db_uri)
+    db.create_table("test_table", pa.table({"a": list(range(1000))}))
+
+    ctx = mp.get_context("spawn")
+    queue = ctx.Queue()
+    proc = ctx.Process(target=_multiworker_dataloader_target, args=(db_uri, queue))
+    proc.start()
+    proc.join(timeout=30)
+
+    if proc.is_alive():
+        proc.terminate()
+        proc.join(timeout=5)
+        if proc.is_alive():
+            proc.kill()
+            proc.join()
+        pytest.fail("Permutation hung when iterated in a fork-based DataLoader worker")
+
+    assert proc.exitcode == 0, f"child exited with code {proc.exitcode}"
+    assert not queue.empty(), "child produced no batches"
+    assert queue.get() == 100