Pyroxide
A lock-free, high-concurrency background task broker for Python, powered by Rust.
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Pyroxide (pyro3) is a lightweight, ultra-high-performance background task broker designed to bridge Python and Rust. It allows CPU-bound or blocking workloads to bypass the Python Global Interpreter Lock (GIL) with minimal memory overhead and zero CPU-sleep polling.
💡 Pyroxide is the perfect fit if you want to:
- Prevent async event loops (like FastAPI) from freezing on heavy CPU calculations.
- Bypass the GIL without the slow startup and heavy pickling overhead of
multiprocessing. - Safely run untrusted user plugins in-process using isolated WASM sandboxes.
- Reuse pre-existing system libraries (
.so/.dylib/.dll) GIL-free with zero wrapper code.
Why Pyroxide?
- 🚀 GIL-Free Performance: Execute CPU-intensive tasks on background threads or isolated processes without holding the Python GIL.
- ⚡ Microsecond Latency: Dispatch and complete tasks in under 25 microseconds using OS-level signaling (
Condvar) instead of polling. - 📦 Zero Infrastructure: Run entirely in-process with no Redis, RabbitMQ, or Celery worker daemons to configure or maintain.
- 💾 Zero-Copy Transport: Route large payloads ($\ge 1\text{MB}$) via OS Shared Memory (SHM) to bypass serialization copying bottlenecks.
- 🛡️ WASM Sandbox Security: Run untrusted user plugins or SaaS workflows in a secure JIT sandbox with strict CPU/memory limits.
- 🛠️ Dynamic FFI Compilation: Compile code strings on-the-fly (Rust, C, Zig) into native libraries with persistent binary caching.
Pyroxide vs. Alternatives
| Feature / Metric | Pyroxide | Threading (std) | Multiprocessing | Celery / RQ |
|---|---|---|---|---|
| GIL Bypass | ✅ Yes (WASM/dylib) | ❌ No | ✅ Yes | ✅ Yes |
| IPC / Serialization | ✅ None (Shared Memory) | ✅ None | ❌ High (Pickling) | ❌ High (Network/Redis) |
| Infrastructure | ✅ None (Embedded) | ✅ None | ⚠️ Low (Spawns processes) | ❌ High (Redis/RabbitMQ) |
| Best For | 🔥 High-perf in-process pipelines | I/O-bound Python | CPU-heavy Python | Distributed tasks |
For a detailed analysis, check out the Library Comparison Guide.
Installation
From PyPI
pip install pyro3
Build Locally
Ensure you have Rust, Python (3.8+), and maturin installed:
git clone https://github.com/emivvvvv/pyroxide.git
cd pyroxide
pip install maturin
maturin develop
Quick Start
1. Offload Python Callables
from pyroxide import task
@task
def calculate_square(x: int) -> int:
return x * x # Runs in background OS threads
# Submit and get a handle immediately
handle = calculate_square(12)
result = handle.result() # Blocks natively (0% CPU) until complete
print(result) # 144
# Or await it non-blockingly inside an async event loop (like FastAPI)
# result = await handle.result_async()
# Pure Python tasks can fully bypass the GIL with `isolated=True`
@task(isolated=True)
def heavy_computation(x: int) -> int:
return sum(i * i for i in range(x))
2. Batch Submission & Task Groups
Submit tasks in bulk under a single lock acquisition to avoid thread contention, and manage them concurrently:
from pyroxide import task, group
@task
def calculate_square(x: int) -> int:
return x * x
payloads = [10, 20, 30, 40]
# 1. Batch submit payloads
handles = calculate_square.batch(payloads)
# 2. Bundle into a parallel TaskGroup
tg = group(handles)
print(tg.status) # "Running"
# 3. Retrieve results (consume=False preserves status metadata)
results = tg.result(consume=False)
print(results) # [100, 400, 900, 1600]
print(tg.status) # "Completed"
3. Sandboxed WebAssembly (GIL-Free)
Run computations GIL-free in a secure, virtual sandbox without compiling native code:
from pyroxide import register_wasm, wasm_task, load_wasm
# 1. Register WebAssembly bytecode
with open("rot13.wasm", "rb") as f:
register_wasm("rot13", f.read())
# 2. Execute via decorators
@wasm_task("rot13")
def rot13_cipher(payload: str) -> str:
pass
print(rot13_cipher("hello").result()) # "uryyb"
# 3. Or load as an Object-Oriented Proxy!
cipher = load_wasm("rot13")
print(cipher.run("hello").result()) # "uryyb"
4. Dynamic Shared Libraries (On-the-Fly Compilation)
Compile and load native code strings on-the-fly. Rust (compile_rust), C (compile_c), and Zig (compile_zig) are supported:
from pyroxide import compile_rust, dylib_task, load_dylib
RUST_SRC = """
#[no_mangle]
pub unsafe extern "C" fn pyroxide_plugin_run(ptr: *const u8, len: usize, out_len: *mut usize) -> *mut u8 {
let input = std::slice::from_raw_parts(ptr, len);
let s = std::str::from_utf8(input).unwrap_or("");
let result = s.to_uppercase().into_bytes();
*out_len = result.len();
let boxed = result.into_boxed_slice();
Box::into_raw(boxed) as *mut u8
}
#[no_mangle]
pub unsafe extern "C" fn pyroxide_plugin_free(ptr: *mut u8, len: usize) {
let _ = Box::from_raw(std::slice::from_raw_parts_mut(ptr, len));
}
"""
# Compile, register and load the Rust library on-the-fly!
compile_rust("rust_upper", RUST_SRC)
# 1. Execute via decorators
@dylib_task("rust_upper")
def to_upper_rust(payload: str) -> str:
pass
print(to_upper_rust("hello from rust").result()) # "HELLO FROM RUST"
# 2. Or load as an Object-Oriented Proxy to call any custom C-ABI symbol directly!
rust_upper = load_dylib("rust_upper")
print(rust_upper.pyroxide_plugin_run("hello from rust").result()) # "HELLO FROM RUST"
5. Universal FFI (Reusing Precompiled Libraries)
Load standard precompiled system libraries natively without compiling custom code:
import sys
from pyroxide import load_dylib
# Load system math library natively - no pyroxide_plugin_free required for primitives!
libm_name = "libm.dylib" if sys.platform == "darwin" else "libm.so.6"
libm = load_dylib(libm_name, signatures={
"cos": {"args": ["f64"], "ret": "f64"}
})
print(libm.cos(3.1415926535).result()) # -1.0
6. Programmatic Sandbox Configuration
Configure WebAssembly memory limits, execution timeouts, and queue block/drop timeouts thread-safely:
import pyroxide
# Set global default sandbox parameters
pyroxide.config.set_wasm_limits(memory_limit_bytes=50 * 1024 * 1024, timeout_ms=500)
pyroxide.config.set_queue_timeout(timeout_ms=100)
# Apply context-specific overrides (thread-safe, ideal for multi-tenant SaaS)
with pyroxide.config.scoped(wasm_timeout_ms=50, wasm_memory_limit_bytes=10 * 1024 * 1024):
handle = rot13_cipher("hello")
7. Static Stub Compilation CLI
Avoid runtime filesystem writes during application startup (which triggers FastAPI reload loops) by statically building type stubs:
# Scan Python files recursively to generate proxy .pyi stubs
pyroxide build-stubs --scan --scan-dir . --out-dir .
# Or read declarative configuration from pyproject.toml
pyroxide build-stubs
8. Environment Variable Reference
Configure Pyroxide dynamically using the following environment variables:
PYROXIDE_WORKERS: Number of background worker threads in the Rust thread pool (default: available CPU cores).PYROXIDE_SHM_THRESHOLD: Payload size threshold in bytes above which data uses Shared Memory (SHM) instead of the local socket (default:1048576= 1MB).PYROXIDE_WASM_TICK_MS: Granularity of the WASM epoch timeout tick loop in milliseconds (default:10ms).PYROXIDE_WASM_MEMORY_LIMIT_BYTES: Maximum memory allowed for a single WASM instance in bytes (default:104857600= 100MB).PYROXIDE_WASM_TIMEOUT_MS: Timeout for WASM execution in milliseconds (default:1000= 1s).PYROXIDE_MAX_TASKS_PER_WORKER: Maximum number of tasks an isolated process worker runs before it is recycled to prevent memory leaks (default:100).PYROXIDE_WORKER_STARTUP_TIMEOUT_SEC: Timeout in seconds for a new worker process to start up and connect (default:5seconds).PYROXIDE_IDLE_TIMEOUT_SEC: Idle time in seconds before an inactive isolated worker process is terminated (default:60seconds).PYROXIDE_MIN_WORKERS: Minimum number of warm worker processes to keep alive at all times (default:0).PYROXIDE_DISABLE_COMPILATION: Set to1ortrueto disable runtime compilation of C/Zig/Rust plugins for strict security compliance.
Dive Deeper (Documentation Book)
Detailed documentation, guides, and implementation examples are available in our Documentation Book:
- Asynchronous Event Loops: Non-blockingly await tasks using
await handle.result_async()in FastAPI/asyncio. Read Chapter. - Isolated Worker Processes: Sandbox tasks in separate OS processes for crash safety and GIL bypass. Read Chapter.
- Batch Submissions: Submit multiple tasks under a single lock acquisition to avoid thread contention. Read Chapter.
- Task Cancellation: Gracefully abort long-running background tasks mid-flight. Read Chapter.
- Traceback Preservation: Capture stack traces on background worker threads and propagate them to the main thread. Read Chapter.
- Memory Footprint & GC: Learn how Slab memory is reclaimed automatically using GC destructors. Read Chapter.
Performance At-a-Glance
We benchmarked Pyroxide against CPython's standard concurrency pools using identical compute payloads (recursive Fibonacci 20 workload) on Apple M1 Pro (8 cores, 16GB RAM):
| Metric (100 Tasks) | Pyroxide @dylib_task |
Pyroxide @task(isolated=True) |
Pyroxide @task |
Threading (std) | Multiprocessing |
|---|---|---|---|---|---|
| Execution Time | 0.0034 s |
0.0157 s |
0.0842 s |
0.0751 s |
2.1925 s |
- Bypassing the Multiprocessing Bottleneck: While Python's
ProcessPoolExecutortakes over 2.1 seconds due to slow process spawning and heavypickleIPC serialization, Pyroxide's@task(isolated=True)executes in just 15 milliseconds—offering a 140x speedup with optimized single-pass pickling and zero-copy shared memory.
Real-World Odoo Enterprise Arrow Ledger Audit Benchmark
To test performance under realistic enterprise data movement workloads, we ran a simulated Odoo Ledger Audit benchmark processing a 9.62 MB Apache Arrow serialized transaction recordset (200,000 journal items) across 10 concurrent requests comparing different concurrency strategies:
- CPython ThreadPoolExecutor (GIL-Locked):
0.3453 s - Pyroxide Threaded
@task(GIL-Locked):0.3239 s(matches Python's native scheduling overhead perfectly) - ProcessPoolExecutor (Python, Pickled Pipes):
0.2625 s - Pyroxide SHM Isolated
@task(Zero-Copy SHM):0.3241 s - Pyroxide
@dylib_task(C-compiled, GIL-Free):0.0095 s(bypasses GIL entirely)
Key Takeaway: By offloading the audit logic to a dynamically compiled C/Rust plugin running on Pyroxide's background thread pool, we achieve a 36.3x speedup over CPython's standard ThreadPoolExecutor by completely bypassing the GIL.
To run the Odoo simulation suite locally:
PYTHONPATH=python:. python3 examples/odoo_poc/odoo_complex_simulation.py
To run the comparative and basic benchmark suites locally:
# 1. Run detailed comparative benchmarks against CPython concurrency pools
PYTHONPATH=python:examples/benchmarks python3 examples/benchmarks/benchmark_vs_alternatives.py
# 2. Run basic scheduling latency and asyncio benchmarks
PYTHONPATH=python python3 examples/benchmarks/benchmark.py
Contributing
Contributions are welcome! If you'd like to improve Pyroxide or add support for additional features, feel free to open an issue or submit a pull request on GitHub.
License
Pyroxide is licensed under any of:
- MIT License (LICENSE-MIT)
- Apache License, Version 2.0 (LICENSE-APACHE)
- Coffeeware License (LICENSE-COFFEE)
at your option.
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