simloom

Deterministic simulation testing for Python's asyncio.
Find the race before it ships. Replay it forever from a seed.

Your async code is tested one interleaving at a time — the polite one your laptop happened to schedule. Races ship. Flakes get retried. "Works on my machine" is the state of the art.

simloom runs your unmodified asyncio program inside a fully simulated world — a seeded scheduler that owns every interleaving, a virtual clock, an in-memory network with injectable latency, loss, partitions, and crashes — and explores thousands of hostile schedules looking for the one that breaks your invariants. It doesn't just find crashes: it asserts safety and liveness properties, proves correctness by exhaustive systematic search, and catches wrong answers (a store that returns a stale or impossible read) with serializability checking. When it finds a problem, it hands you a seed that replays the failure byte-for-byte, forever, shrinks it to the minimal schedule that still triggers the bug, and lets you walk the causal trace of what woke what.

FAILED test_lease_exclusivity — simloom found a failing universe
  seed: 17   (re-run: pytest -k lease --simloom-seed=17)
  error: AssertionError: two holders of an exclusive lease
  shrunk: 31 draws → 29, schedule deviations 25 → 1 (106 candidate runs)
  minimal schedule: FIFO everywhere except:
    draw #0: sched.pick = 1 (of 4)
  artifacts: .sim/failures/test_lease_exclusivity-seed17.tape.json, …

The entire bug, above, is "one callback ran out of order, once." No more staring at a flake that reproduces every thousandth CI run.

Install

pip install simloom        # or: uv add simloom

Python 3.12+. Zero runtime dependencies. The pytest plugin loads automatically.

Quickstart

Write an ordinary async test, decorate it, and let simloom explore the schedule space:

import asyncio
import simloom

@simloom.test(runs=2000)          # explores 2000 schedules; pytest collects this
async def test_counter_is_atomic():
    state = {"value": 0}

    async def worker():
        for _ in range(3):
            current = state["value"]
            await asyncio.sleep(0)          # a scheduling point — the race lives here
            state["value"] = current + 1

    await asyncio.gather(*(worker() for _ in range(3)))
    assert state["value"] == 9             # a plain assert: it fires under exploration

pytest                                  # finds the lost-update race, shrinks it, prints the seed
pytest --simloom-seed=42                # replay one exact universe

Need a distributed system? Ask for a world and you get hosts, a network, and faults:

@simloom.test(runs=5000)
async def test_leader_election(world):
    nodes = [world.host(f"n{i}") for i in range(5)]
    for h in nodes:
        h.spawn(lambda h=h: run_node(h, peers=nodes))   # your real, unmodified asyncio code

    world.net.partition(nodes[:2], nodes[2:])           # faults are first-class
    await world.sleep(30)                               # virtual seconds — wall time ≈ 0
    world.net.heal()
    nodes[0].crash()                                    # a real power cut: no finally blocks
    nodes[0].restart()                                  # comes back against fsynced disk only

    await world.until(lambda: exactly_one_leader(nodes), timeout=120)

Beyond crashes

Assert what should hold, prove it can't be violated, and catch wrong answers:

@simloom.test(runs=5000)
async def test_lease_safety(world):
    cluster = start_cluster(world)
    # safety: never two leaders. liveness: one eventually emerges.
    world.always("≤1 leader", lambda: sum(n.is_leader for n in cluster) <= 1)
    world.eventually("a leader", lambda: any(n.is_leader for n in cluster), within=120)
    await world.sleep(300)

@simloom.test(systematic=True, max_delays=3)     # exhaustive, not sampled
async def test_critical_section():
    ...                                          # passes ⇒ a bounded PROOF of correctness

@simloom.test(runs=5000)
async def test_store_is_serializable(world):
    await run_transactions(world)                # records ops into world.history
    world.assert_serializable()                  # finds lost updates / write skew, with the cycle

And once it finds something, replay and walk it:

pytest --simloom-seed=17 -k lease          # replay the exact failing universe
simloom trace failure.jsonl --step 42      # reconstruct state + the happens-before stack
simloom diff run_a.jsonl run_b.jsonl       # first divergence between two universes

Why this didn't exist before

Rust has loom, turmoil, madsim, and shuttle. .NET had Coyote. FoundationDB built a company-defining simulator; Antithesis sells the methodology at the hypervisor level. Python — where a huge share of backend glue and agent orchestration is written — had nothing.

And asyncio is structurally perfect for it: every interleaving decision happens at an await, under a replaceable event loop. simloom swaps in a deterministic one — no forked interpreter, no hypervisor, no recompilation. Because the ecosystem (aiohttp, httpx, redis, the streams API) bottoms out in loop primitives, real, unmodified libraries run inside the simulation. Our CI runs an unmodified aiohttp HTTPS server against an unmodified aiohttp client over a memory-BIO TLS handshake, and an unmodified redis.asyncio.Redis against an in-sim Redis — all over the simulated network, with faults injected, replayable byte-for-byte from a seed.

What you get

Run it. Your real asyncio code, unchanged, inside the simulation.

• 🎲 Seeded scheduling — a single choice tape (the Hypothesis trick, applied to schedules) drives every decision. One seed → one exact universe.
• ⏱ Virtual time — an hour of simulated asyncio.sleep traffic runs in milliseconds; opt-in patching makes time.time() and the stdlib RNG tape-driven too, so an unmodified library that timestamps or rolls a random timeout replays byte-for-byte.
• 🌐 A simulated network — in-memory streams (loss modeled as TCP retransmit delay — bytes never corrupt), UDP datagrams with real loss/reorder/duplication, partitions, asymmetric per-link latency/loss shaping, resets, and TLS in-sim (memory-BIO SSL, so aiohttp HTTPS just works).
• 💥 Honest crashes & disk — host.crash() is a power cut: tasks stop with no finally blocks, unsynced disk writes are lost or torn, peers see resets.
• 🧩 Stand-in services — world.run_service(SimRedis(), …) gives you an in-sim Redis (SET/GET, WATCH/MULTI/EXEC) to test your logic against, with wire faults applied.

Break it. Explore the schedules and faults your laptop never will.

• 🔬 Fault injection — simloom.sometimes("drop_cache") is tape-driven inside the sim and a constant False in production. Annotate rare branches; explore them.
• 🧭 Pluggable search — uniform random walk, pct:auto (auto-tuned Probabilistic Concurrency Testing that finds deep-ordering and starvation bugs random walk never hits), and simloom.soak (resumable, shardable continuous exploration).

Check it. Assertions far past "didn't crash."

• 🛡 Safety & liveness oracles — world.always("one leader", …), world.eventually("elects a leader", …, within=120), world.leads_to(…), plus a livelock detector and replica-convergence checks.
• ✅ Prove it — @simloom.test(systematic=True) switches from sampling seeds to exhaustive delay-bounded model checking: it finds a deep interleaving bug deterministically, or passes as a bounded proof of correctness.
• 🧾 Find wrong answers — an Elle-style serializability checker (world.check_serializable) catches a store that returns a stale or impossible read — not just one that crashes — and reports the cyclic read/write dependency.

Reproduce & debug it.

• 🪓 Automatic shrinking — failures reduce to the minimal schedule deviation, with a replayable artifact on disk.
• 🔁 Determinism guarantees — a per-test self-check (run twice, locate the first diverging event), PYTHONHASHSEED auto-pin, and a queryable boundary registry.
• 🕰 Causal trace — record with causal=True and walk it: simloom trace LOG --step N reconstructs state and the happens-before stack that woke it; --changed x is an omniscient query; simloom diff A B finds the first divergence between two universes.
• 🚨 Escape detection — touch a real socket, signal, subprocess, or (un-patched) wall clock from inside the sim and you get an EscapedSimulationError at the exact call site instead of silent nondeterminism.

It finds real bugs

A multi-year CPython race. Pre-3.12 asyncio.wait_for could swallow a delivered cancellation when the inner future completed in the same window as the cancel (bpo-42130). In production it took an exact wall-clock collision; under simloom the timeout boundary is just another scheduling choice, so exploration finds the interleaving from a seed and replays it exactly. The modern implementation survives the identical torture. → examples/bpo42130.py

The canonical demo. A toy Raft over the simulated network — persisted term/votedFor, JSON-RPC, the works — tortured with partitions, crashes, and restarts. Plant the classic double-vote bug and exploration elects two leaders in one term in ~1 seed of 5; the fixed version survives, with coverage counters proving the faults actually fired. → examples/toy_raft.py

Honesty first

A determinism claim is only as good as its disclosed limits. simloom raises a loud error when your code reaches outside the simulation, and docs/determinism.md states exactly what is and isn't deterministic — now machine-readable via simloom.boundary(). Known boundaries: blocking C-extension I/O (psycopg2, requests, grpc's C core) can't run in-sim; a from time import … alias or the C-accelerated datetime.now() isn't redirected by the clock patch; real subprocesses and external servers need stand-ins. None of these fail silently — and the per-test determinism self-check locates anything that slips through.

Status

Alpha, and built in the open. The deterministic core, the simulated world and fault matrix (streams, UDP, TLS, partitions, crashes, torn disk writes), the explorer, shrinker, property oracles, systematic verifier, serializability checker, causal-trace CLI, and the pytest plugin all exist — exercised by a 10,000-seed determinism torture on every CI run (the harness holds itself to the same hostility it applies to your code) across Python 3.12/3.13/3.14. The API may still shift before 1.0. If you try it, open an issue — early feedback shapes it.

Learn more

• docs/determinism.md — the honest boundary of the simulation
• docs/event-log.md — the versioned event-log and tape formats
• CHANGELOG.md — every capability, phase by phase
• examples/ — the toy Raft and the bpo-42130 reproduction, both runnable

Development

uv run --all-extras pytest          # tests (incl. the determinism torture)
uv run --all-extras mypy src        # strict typing
uv run --all-extras ruff check .    # lint

License

Apache-2.0. See LICENSE.