pyro3 0.3.0

A lock-free, high-concurrency task broker for Python, powered by Rust.

Pyroxide

A lock-free, high-concurrency background task broker for Python, powered by Rust.



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Pyroxide is a high-concurrency, lock-free 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.

With Pyroxide, you can seamlessly offload tasks from Python to a background native OS thread pool. Tasks block natively on the OS kernel level using signaling primitives (Condvar) rather than CPU-burning sleep loops, allowing Python to yield control instantly.

Key Features

• Bypass the Python GIL: Explicitly release the Python GIL via PyO3 thread-detaching, running heavy computations concurrently on native OS threads.
• Zero-Overhead Status Tracking: Avoids global lock contention using an atomic-state (AtomicU8) task tracking structure per task slot under a concurrent sharded/read-lock Slab architecture.
• Instant Condvar Signaling: Replaces latency-inducing polling loops (time.sleep) with native Rust Condvar waking, waking waiting Python threads in microseconds with 0% CPU consumption.
• Dynamic Task Execution: Offload Python callbacks, run sandboxed WebAssembly modules (@wasm_task), or compile and execute dynamic shared libraries on-the-fly (@dylib_task) — all completely GIL-free.
• Configurable Concurrency: Set worker thread pool size dynamically at startup via environment variables.
• Panic Safety: Wrapped task execution prevents Rust worker panics from crashing the host Python interpreter, gracefully marking tasks as Failed instead.
• Zero-Copy Byte Buffers: Easily pass byte arrays, memoryviews, and columnar buffers (e.g., Apache Arrow) across the C-ABI without copy overhead.
• Full Type-Hinting: Exposes advanced typing generic @overload signatures, offering full autocomplete support for modern IDEs.

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Installation

From PyPI (Recommended)

pip install pyro3

Build and Install locally

Ensure you have Rust, Python (3.8+), and maturin installed. Compile and install the C-extension into your active virtual environment:

# Clone the repository
git clone https://github.com/emivvvvv/pyroxide.git
cd pyroxide

# Compile and install editable build using maturin
pip install maturin
maturin develop

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Performance & Validation

We benchmarked Pyroxide against a baseline Python-based task queue using standard thread-polling loops (time.sleep(0.01)) and lock-guarded queues, isolated using a 1ms simulated execution payload to highlight broker overhead:

1. Latency (Single-Threaded Sequential Wait)

Tasks	Baseline (10ms Polling Loop)	Pyroxide (Condvar + Lock-Free)	Latency Reduction
10 Tasks	1.0180s	0.0002s (0.2ms)	~5,000x faster
50 Tasks	3.5289s	0.0008s (0.8ms)	~4,400x faster
Avg. Latency	70.58ms	0.02ms (20µs)	3,500x less overhead

2. Multi-Threaded Throughput (40 Concurrent Submissions)

Threads	Baseline (Lock Contention)	Pyroxide (Lock-Free)	Speedup
2 Threads	10.1848s	0.0032s (3.2ms)	3,180x faster
4 Threads	5.1193s	0.0013s (1.3ms)	3,930x faster
8 Threads	2.5624s	0.0015s (1.5ms)	1,700x faster

3. Automated Test Suite (Pytest)

A senior developer can inspect and run our comprehensive, production-grade automated verification suite under the tests/ directory:

# Install pytest and run the suite
pip install pytest
pytest -v tests/

The test suite covers:

• True Concurrency (GIL Bypass): Verifies that 4 concurrent native tasks running on 4 background worker threads execute in parallel in a single task duration (~100ms instead of ~400ms), proving the Python GIL is successfully released during processing.
• Main Thread Responsiveness: Asserts that long-running native background execution does not block or latency-contend the main Python thread.
• Panic Safety & Recovery: Verifies that Rust worker panics are caught gracefully, marking the task status as Failed and throwing a Python RuntimeError on result retrieval without crashing the interpreter or leaking worker thread health.
• Deterministic Slab Memory Eviction: Validates that Slab task allocations are cleanly deallocated immediately via explicit consumption (consume=True) or automatically via garbage collection destructor bindings (__del__ GC eviction) when a TaskHandle is deleted.
• High Churn Stress Testing: Runs a concurrent ThreadPoolExecutor stress test submitting 1,600 tasks across multiple client threads to verify zero lock contentions or memory leaks under heavy thread churn.

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Configuration

Pyroxide can be configured via environment variables before the engine initializes:

• PYROXIDE_WORKERS: Sets the number of background worker threads in the pool. Defaults to the number of CPU cores (available_parallelism).

export PYROXIDE_WORKERS=4
python my_app.py

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Quick Start

1. Offloading Python Callables (Default)

By default, @task runs the decorated Python function in the background pool.

from pyroxide import task

@task
def calculate_square(x: int) -> int:
    # Runs on background OS threads in the Rust pool
    return x * x

# Submit and get a handle immediately
handle = calculate_square(12)
print(f"Task status: {handle.status}")

# Blocks natively (0% CPU) until complete, then returns result
# Automatically evicts the task from the Rust Slab once retrieved (consume=True)
result = handle.result()
print(f"Result: {result}") # Output: 144

2. Sandboxed WebAssembly Execution (GIL-Free & Panic-Safe)

To run computations GIL-free in a secure, sandboxed environment without compiling native code:

from pyroxide import register_wasm, wasm_task

# 1. Register compiled WebAssembly bytecode (WASM module)
with open("rot13.wasm", "rb") as f:
    register_wasm("rot13", f.read())

# 2. Decorate a stub function with @wasm_task
@wasm_task("rot13")
def rot13_cipher(payload: str) -> str:
    pass

# 3. Execute GIL-free on the background worker pool!
handle = rot13_cipher("hello")
print(handle.result()) # "uryyb"

3. Dynamic Shared Libraries (On-the-Fly Compilation)

For use cases that need full OS/system/database access but must avoid manual compilation or rebuilding Pyroxide:

from pyroxide import compile_dylib, dylib_task

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));
}
"""

# Pyroxide compiles the Rust source code on-the-fly via Cargo
# and loads it as a dynamic shared library (.so / .dylib / .dll).
compile_dylib("greeter", RUST_SRC)

# Decorate a stub to submit tasks to the compiled dylib
@dylib_task("greeter")
def native_uppercase(payload: str) -> str:
    pass

handle = native_uppercase("hello dynamic pyroxide")
print(handle.result())  # "HELLO DYNAMIC PYROXIDE"

4. Graceful Memory Reclamation & Retaining Results

By default, result() consumes and evicts the task. If you want to keep the task in the Slab (e.g. to check status or result again later), set consume=False. It will be automatically cleaned up later via the Python garbage collector when the handle reference is deleted:

import gc
from pyroxide import task
from pyroxide._pyroxide import get_slab_size

handle = calculate_square(10)
print(get_slab_size()) # Output: 1

# Retrieve result but retain task in the Slab
result = handle.result(consume=False)

# Deleting the Python TaskHandle reference forces GC eviction in the Rust Slab
del handle
gc.collect()

print(get_slab_size()) # Output: 0 (No memory leaked)

4. Asynchronous Awaiting (asyncio support)

For modern asynchronous web servers (e.g. FastAPI, Sanic), you can non-blockingly await task execution to yield control back to the event loop:

import asyncio
from pyroxide import task

@task
def calculate_square(x: int) -> int:
    return x * x

async def main():
    handle = calculate_square(12)
    # Yields control non-blockingly to the event loop while waiting
    result = await handle.result_async()
    print(f"Result: {result}") # Output: 144

asyncio.run(main())

5. Batch Task Submission

To submit multiple tasks under a single write lock (avoiding lock-contention overhead for high-churn operations), use the .batch() helper:

from pyroxide import task

@task
def calculate_square(x: int) -> int:
    return x * x

# Submits all 5 tasks under a single lock acquisition
handles = calculate_square.batch([1, 2, 3, 4, 5])

# Retrieve results
results = [h.result() for h in handles]
print(results) # Output: [1, 4, 9, 16, 25]

6. Task Cancellation

Tasks can be aborted before or during execution. Calling .cancel() transitions the task status to Cancelled and immediately terminates sleep loops in native workers:

from pyroxide import task

@task
def native_sleep(payload: str) -> None:
    import time
    if payload.startswith("SLEEP:"):
        sec = int(payload.split(":")[1]) / 1000.0
        time.sleep(sec)

# Submit long-running task
handle = native_sleep("SLEEP:5000")

# Abort task execution
cancelled = handle.cancel()
print(f"Cancelled: {cancelled} | Status: {handle.status}") 
# Output: Cancelled: True | Status: Cancelled

try:
    handle.result()
except RuntimeError as e:
    print(e) # Output: Task cancelled

7. Background Exception Tracebacks

When a background Python task fails, Pyroxide captures its traceback inside the worker thread and propagates it to the main thread's exception, ensuring clean diagnostics:

from pyroxide import task

@task
def fail_task(x: int) -> int:
    raise ValueError("Something went wrong!")

handle = fail_task(10)
try:
    handle.result()
except RuntimeError as e:
    # Prints the exception message AND the exact background stack trace!
    print(e)

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Performance & Benchmarks

Pyroxide is engineered for ultra-high throughput and low-overhead Python-to-Rust communication. To measure the exact performance under different submission models, run:

python examples/benchmark.py

Benchmark Results (CPython 3.11, Apple M3 Max)

For 200 background tasks, Pyroxide demonstrates the following performance profiles:

Submission Mode	Tasks	Total Time	Avg Latency	Overhead Highlights
Single Threaded	200	0.0028s	0.01ms (14 μs)	Standard sequential submission
Batch Submission	200	0.0017s	0.01ms (8 μs)	Lock-free batch optimization (~2x speedup)
Asyncio Non-blocking	200	0.0103s	0.05ms (50 μs)	Parallel await without blocking Python event loop
Multi-Threaded	40	0.0019s	0.04ms (47 μs)	Safe concurrent channel enqueueing

Note: Batch submissions are processed with single-acquisition write locks on the internal task slab, avoiding locking contention overhead and maximizing core utilization.

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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.