Hyper-fast queue for Python

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Project description

HyperQ

⚠️ Warning: This package is not ready for production usage yet. It's currently in active development and may have bugs, especially with multiprocessing scenarios using the spawn start method in macOS.

Hyper-fast queue for Python - A high-performance queue implementation using Cython and C++ for inter-process communication.

🚀 Features

Lightning Fast: Optimized C++ implementation with Python bindings
Inter-Process Communication: Shared memory-based queues for high-performance IPC
Ring Buffer Architecture: Uses a ring buffer with double virtual memory mapping to the same physical memory.
Two Queue Types:
- HyperQ: General-purpose queue for Python objects
- BytesHyperQ: Specialized queue for bytes data (even faster)
Thread-Safe: Safe for concurrent access
Unix-like Systems: Works on Linux and macOS (POSIX-compliant systems)
Python 3.10+: Modern Python support

📋 TODO

Fix multiprocessing spawn start method bug in macOS - Critical issue with multiple consumers/producers
- Queue doesn't work properly when multiprocessing.set_start_method('spawn') is used
- Affects scenarios with multiple consumers and producers
Add __getstate__ and __setstate__ methods to make queue objects picklable
- Allow passing queue objects directly to multiprocessing functions
- Serialize only the shared memory name/descriptor, not the entire queue state
- Enable seamless integration with multiprocessing.Pool and other parallel processing tools
Add timeout support for put() and get() operations
Add non-blocking operations (put_nowait(), get_nowait())
- put_nowait(): Non-blocking put that raises queue.Full if queue is full
- get_nowait(): Non-blocking get that raises queue.Empty if queue is empty
- Useful for polling scenarios where you don't want to block the thread
Add batch operations for better performance
- put_many(items): Put multiple items in a single operation
- get_many(count): Get multiple items in a single operation
- get_all(): Get all available items at once
- Reduces synchronization overhead for bulk operations
Design decision: Queue name management
- Option A: Encapsulate queue names (auto-generate, hide from client)
- Option B: Client specifies queue names (current approach)
- Option C: Hybrid approach (auto-generate with optional override)
Add Windows support (requires different shared memory implementation)
Add more comprehensive tests including stress tests and edge cases
Add documentation for advanced usage patterns
- orjson + BytesHyperQ for JSON: Use orjson.dumps() + BytesHyperQ for fastest JSON serialization and transfer.

⚠️ Platform Support

Currently supported:

✅ Linux
⚠️ macOS (There is an issue when start method is set to spawn and there are multiple producers/consumers)

Not supported:

❌ Windows (uses POSIX-specific APIs)
❌ PyPy

🔧 Technical Details

Ring Buffer Implementation

HyperQ uses a ring buffer with double virtual memory mapping to the same physical memory. This eliminates the need for 2 memcpy operations when data wraps around the buffer boundaries.

Shared Memory Architecture

Header segment: Contains queue metadata, synchronization primitives, and buffer information
Buffer segment: The actual data storage with double virtual memory mapping
POSIX shared memory: Uses shm_open() and mmap() for cross-process memory sharing
Synchronization: Uses POSIX mutexes and condition variables for thread/process safety

📦 Installation

From PyPI

pip install hyperq

From Source

git clone https://github.com/martinmkhitaryan/hyperq.git
cd hyperq
pip install -e .

Development Installation

git clone https://github.com/martinmkhitaryan/hyperq.git
cd hyperq
pip install -e ".[test]"

🎯 Quick Start

Basic Usage

import multiprocessing as mp
from hyperq import HyperQ, BytesHyperQ

# Create a queue with 1MB capacity
queue = HyperQ(1024 * 1024, name="my_queue")

# Put data
queue.put("Hello, World!")
queue.put(42)
queue.put({"key": "value"})

# Get data
data = queue.get()  # "Hello, World!"
number = queue.get()  # 42
obj = queue.get()  # {"key": "value"}

Inter-Process Communication

import multiprocessing as mp
from hyperq import HyperQ

def producer(queue_name):
    queue = HyperQ(queue_name)
    for i in range(1000):
        queue.put(f"Message {i}")

def consumer(queue_name):
    queue = HyperQ(queue_name)
    for _ in range(1000):
        message = queue.get()
        print(f"Received: {message}")

if __name__ == "__main__":
    # Create queue in main process
    queue = HyperQ(1024 * 1024, name="shared_queue")
    queue_name = queue.shm_name

    # Start producer and consumer processes
    p1 = mp.Process(target=producer, args=(queue_name,))
    p2 = mp.Process(target=consumer, args=(queue_name,))

    p1.start()
    p2.start()
    p1.join()
    p2.join()

Bytes-Specific Queue (Faster)

from hyperq import BytesHyperQ

# For bytes data, use BytesHyperQ for better performance
queue = BytesHyperQ(1024 * 1024, name="bytes_queue")

# Put bytes data
queue.put(b"Hello, World!")
queue.put(b"Binary data")

# Get bytes data
data = queue.get()  # b"Hello, World!"

📊 Performance Benchmarks

HyperQ is designed for high-performance scenarios. Here are some benchmark results:

Hardware:

CPU: Intel® Core™ i3-12100
Memory: 8GB
OS: Ubuntu 22.04 / Virtual Box
Python: 3.12

Benchmark bytes transfering.

Running bytes performance benchmarks...
================================================================================

Results for 100,000 messages of 32 bytes per producer:
Total messages: 100,000 (1 producers, 1 consumers)
--------------------------------------------------------------------------------
Queue Type           Total Time (s)  Latency (ms)    Throughput (items/s)
--------------------------------------------------------------------------------
BytesHyperQ          0.018           0.000           5,528,243           
HyperQ               0.090           0.001           1,106,593           
multiprocessing.Queue 0.334           0.003           299,499             
faster-fifo          0.406           0.004           246,330             

🏆 Fastest: BytesHyperQ with 5,528,243 items/s
   5.0x faster than HyperQ
   18.5x faster than multiprocessing.Queue
   22.4x faster than faster-fifo

================================================================================
Sleeping 2 seconds before next test configuration...

Results for 100,000 messages of 64 bytes per producer:
Total messages: 100,000 (1 producers, 1 consumers)
--------------------------------------------------------------------------------
Queue Type           Total Time (s)  Latency (ms)    Throughput (items/s)
--------------------------------------------------------------------------------
BytesHyperQ          0.020           0.000           5,067,022           
HyperQ               0.090           0.001           1,105,261           
multiprocessing.Queue 0.388           0.004           257,635             
faster-fifo          0.397           0.004           251,805             

🏆 Fastest: BytesHyperQ with 5,067,022 items/s
   4.6x faster than HyperQ
   19.7x faster than multiprocessing.Queue
   20.1x faster than faster-fifo

================================================================================
Sleeping 2 seconds before next test configuration...

Results for 100,000 messages of 128 bytes per producer:
Total messages: 100,000 (1 producers, 1 consumers)
--------------------------------------------------------------------------------
Queue Type           Total Time (s)  Latency (ms)    Throughput (items/s)
--------------------------------------------------------------------------------
BytesHyperQ          0.025           0.000           3,988,545           
HyperQ               0.102           0.001           984,694             
multiprocessing.Queue 0.332           0.003           301,471             
faster-fifo          0.402           0.004           248,764             

🏆 Fastest: BytesHyperQ with 3,988,545 items/s
   4.1x faster than HyperQ
   13.2x faster than multiprocessing.Queue
   16.0x faster than faster-fifo

================================================================================
Sleeping 2 seconds before next test configuration...

Results for 100,000 messages of 256 bytes per producer:
Total messages: 100,000 (1 producers, 1 consumers)
--------------------------------------------------------------------------------
Queue Type           Total Time (s)  Latency (ms)    Throughput (items/s)
--------------------------------------------------------------------------------
BytesHyperQ          0.030           0.000           3,280,452           
HyperQ               0.098           0.001           1,024,640           
multiprocessing.Queue 0.344           0.003           290,311             
faster-fifo          0.395           0.004           253,071             

🏆 Fastest: BytesHyperQ with 3,280,452 items/s
   3.2x faster than HyperQ
   11.3x faster than multiprocessing.Queue
   13.0x faster than faster-fifo

================================================================================
Sleeping 2 seconds before next test configuration...

Results for 100,000 messages of 512 bytes per producer:
Total messages: 100,000 (1 producers, 1 consumers)
--------------------------------------------------------------------------------
Queue Type           Total Time (s)  Latency (ms)    Throughput (items/s)
--------------------------------------------------------------------------------
BytesHyperQ          0.028           0.000           3,550,212           
HyperQ               0.105           0.001           956,745             
multiprocessing.Queue 0.357           0.004           279,993             
faster-fifo          0.420           0.004           238,251             

🏆 Fastest: BytesHyperQ with 3,550,212 items/s
   3.7x faster than HyperQ
   12.7x faster than multiprocessing.Queue
   14.9x faster than faster-fifo

================================================================================
Sleeping 2 seconds before next test configuration...

Results for 100,000 messages of 1024 bytes per producer:
Total messages: 100,000 (1 producers, 1 consumers)
--------------------------------------------------------------------------------
Queue Type           Total Time (s)  Latency (ms)    Throughput (items/s)
--------------------------------------------------------------------------------
BytesHyperQ          0.042           0.000           2,390,645           
HyperQ               0.109           0.001           917,085             
multiprocessing.Queue 0.379           0.004           263,922             
faster-fifo          0.413           0.004           241,983             

🏆 Fastest: BytesHyperQ with 2,390,645 items/s
   2.6x faster than HyperQ
   9.1x faster than multiprocessing.Queue
   9.9x faster than faster-fifo

================================================================================
Sleeping 2 seconds before next test configuration...

Results for 100,000 messages of 4096 bytes per producer:
Total messages: 100,000 (1 producers, 1 consumers)
--------------------------------------------------------------------------------
Queue Type           Total Time (s)  Latency (ms)    Throughput (items/s)
--------------------------------------------------------------------------------
BytesHyperQ          0.077           0.001           1,296,410           
HyperQ               0.153           0.002           653,955             
multiprocessing.Queue 0.420           0.004           238,116             
faster-fifo          0.437           0.004           228,823             

🏆 Fastest: BytesHyperQ with 1,296,410 items/s
   2.0x faster than HyperQ
   5.4x faster than multiprocessing.Queue
   5.7x faster than faster-fifo

================================================================================
Sleeping 2 seconds before next test configuration...

Results for 100,000 messages of 8192 bytes per producer:
Total messages: 100,000 (1 producers, 1 consumers)
--------------------------------------------------------------------------------
Queue Type           Total Time (s)  Latency (ms)    Throughput (items/s)
--------------------------------------------------------------------------------
BytesHyperQ          0.107           0.001           936,460             
HyperQ               0.203           0.002           492,091             
multiprocessing.Queue 0.497           0.005           201,165             
faster-fifo          0.539           0.005           185,473             

🏆 Fastest: BytesHyperQ with 936,460 items/s
   1.9x faster than HyperQ
   4.7x faster than multiprocessing.Queue
   5.0x faster than faster-fifo

================================================================================
Sleeping 2 seconds before next test configuration...

Results for 100,000 messages of 16384 bytes per producer:
Total messages: 100,000 (1 producers, 1 consumers)
--------------------------------------------------------------------------------
Queue Type           Total Time (s)  Latency (ms)    Throughput (items/s)
--------------------------------------------------------------------------------
BytesHyperQ          0.189           0.002           528,889             
HyperQ               0.303           0.003           329,876             
multiprocessing.Queue 0.658           0.007           152,017             
faster-fifo          0.762           0.008           131,168             

🏆 Fastest: BytesHyperQ with 528,889 items/s
   1.6x faster than HyperQ
   3.5x faster than multiprocessing.Queue
   4.0x faster than faster-fifo

================================================================================
Sleeping 2 seconds before next test configuration...

Results for 100,000 messages of 32768 bytes per producer:
Total messages: 100,000 (1 producers, 1 consumers)
--------------------------------------------------------------------------------
Queue Type           Total Time (s)  Latency (ms)    Throughput (items/s)
--------------------------------------------------------------------------------
BytesHyperQ          0.375           0.004           266,432             
HyperQ               0.484           0.005           206,720             
faster-fifo          0.939           0.009           106,544             
multiprocessing.Queue 1.053           0.011           94,985              

🏆 Fastest: BytesHyperQ with 266,432 items/s
   1.3x faster than HyperQ
   2.5x faster than faster-fifo
   2.8x faster than multiprocessing.Queue

================================================================================
Sleeping 2 seconds before next test configuration...

Results for 100,000 messages of 32 bytes per producer:
Total messages: 400,000 (4 producers, 4 consumers)
--------------------------------------------------------------------------------
Queue Type           Total Time (s)  Latency (ms)    Throughput (items/s)
--------------------------------------------------------------------------------
BytesHyperQ          0.097           0.000           4,142,198           
HyperQ               0.313           0.001           1,276,678           
faster-fifo          0.863           0.002           463,335             
multiprocessing.Queue 2.907           0.007           137,604             

🏆 Fastest: BytesHyperQ with 4,142,198 items/s
   3.2x faster than HyperQ
   8.9x faster than faster-fifo
   30.1x faster than multiprocessing.Queue

================================================================================
Sleeping 2 seconds before next test configuration...

Results for 100,000 messages of 64 bytes per producer:
Total messages: 400,000 (4 producers, 4 consumers)
--------------------------------------------------------------------------------
Queue Type           Total Time (s)  Latency (ms)    Throughput (items/s)
--------------------------------------------------------------------------------
BytesHyperQ          0.108           0.000           3,713,089           
HyperQ               0.336           0.001           1,189,575           
faster-fifo          0.847           0.002           472,108             
multiprocessing.Queue 2.928           0.007           136,622             

🏆 Fastest: BytesHyperQ with 3,713,089 items/s
   3.1x faster than HyperQ
   7.9x faster than faster-fifo
   27.2x faster than multiprocessing.Queue

================================================================================
Sleeping 2 seconds before next test configuration...

Results for 100,000 messages of 128 bytes per producer:
Total messages: 400,000 (4 producers, 4 consumers)
--------------------------------------------------------------------------------
Queue Type           Total Time (s)  Latency (ms)    Throughput (items/s)
--------------------------------------------------------------------------------
BytesHyperQ          0.104           0.000           3,838,310           
HyperQ               0.293           0.001           1,365,044           
faster-fifo          0.880           0.002           454,557             
multiprocessing.Queue 2.968           0.007           134,779             

🏆 Fastest: BytesHyperQ with 3,838,310 items/s
   2.8x faster than HyperQ
   8.4x faster than faster-fifo
   28.5x faster than multiprocessing.Queue

================================================================================
Sleeping 2 seconds before next test configuration...

Results for 100,000 messages of 256 bytes per producer:
Total messages: 400,000 (4 producers, 4 consumers)
--------------------------------------------------------------------------------
Queue Type           Total Time (s)  Latency (ms)    Throughput (items/s)
--------------------------------------------------------------------------------
BytesHyperQ          0.121           0.000           3,306,829           
HyperQ               0.346           0.001           1,156,464           
faster-fifo          0.848           0.002           471,452             
multiprocessing.Queue 3.024           0.008           132,281             

🏆 Fastest: BytesHyperQ with 3,306,829 items/s
   2.9x faster than HyperQ
   7.0x faster than faster-fifo
   25.0x faster than multiprocessing.Queue

================================================================================
Sleeping 2 seconds before next test configuration...

Results for 100,000 messages of 512 bytes per producer:
Total messages: 400,000 (4 producers, 4 consumers)
--------------------------------------------------------------------------------
Queue Type           Total Time (s)  Latency (ms)    Throughput (items/s)
--------------------------------------------------------------------------------
BytesHyperQ          0.139           0.000           2,870,961           
HyperQ               0.413           0.001           968,493             
faster-fifo          0.892           0.002           448,522             
multiprocessing.Queue 3.143           0.008           127,257             

🏆 Fastest: BytesHyperQ with 2,870,961 items/s
   3.0x faster than HyperQ
   6.4x faster than faster-fifo
   22.6x faster than multiprocessing.Queue

================================================================================
Sleeping 2 seconds before next test configuration...

Results for 100,000 messages of 1024 bytes per producer:
Total messages: 400,000 (4 producers, 4 consumers)
--------------------------------------------------------------------------------
Queue Type           Total Time (s)  Latency (ms)    Throughput (items/s)
--------------------------------------------------------------------------------
BytesHyperQ          0.209           0.001           1,918,401           
HyperQ               0.546           0.001           732,611             
faster-fifo          0.929           0.002           430,677             
multiprocessing.Queue 3.299           0.008           121,240             

🏆 Fastest: BytesHyperQ with 1,918,401 items/s
   2.6x faster than HyperQ
   4.5x faster than faster-fifo
   15.8x faster than multiprocessing.Queue

================================================================================
Sleeping 2 seconds before next test configuration...

Results for 100,000 messages of 4096 bytes per producer:
Total messages: 400,000 (4 producers, 4 consumers)
--------------------------------------------------------------------------------
Queue Type           Total Time (s)  Latency (ms)    Throughput (items/s)
--------------------------------------------------------------------------------
BytesHyperQ          0.400           0.001           1,001,018           
HyperQ               0.745           0.002           536,564             
faster-fifo          1.176           0.003           340,031             
multiprocessing.Queue 4.032           0.010           99,196              

🏆 Fastest: BytesHyperQ with 1,001,018 items/s
   1.9x faster than HyperQ
   2.9x faster than faster-fifo
   10.1x faster than multiprocessing.Queue

================================================================================
Sleeping 2 seconds before next test configuration...

Results for 100,000 messages of 8192 bytes per producer:
Total messages: 400,000 (4 producers, 4 consumers)
--------------------------------------------------------------------------------
Queue Type           Total Time (s)  Latency (ms)    Throughput (items/s)
--------------------------------------------------------------------------------
BytesHyperQ          0.679           0.002           589,081             
HyperQ               1.111           0.003           359,917             
faster-fifo          1.554           0.004           257,363             
multiprocessing.Queue 4.742           0.012           84,353              

🏆 Fastest: BytesHyperQ with 589,081 items/s
   1.6x faster than HyperQ
   2.3x faster than faster-fifo
   7.0x faster than multiprocessing.Queue

================================================================================
Sleeping 2 seconds before next test configuration...

Results for 100,000 messages of 16384 bytes per producer:
Total messages: 400,000 (4 producers, 4 consumers)
--------------------------------------------------------------------------------
Queue Type           Total Time (s)  Latency (ms)    Throughput (items/s)
--------------------------------------------------------------------------------
BytesHyperQ          1.278           0.003           313,053             
HyperQ               1.765           0.004           226,633             
faster-fifo          2.442           0.006           163,817             
multiprocessing.Queue 6.288           0.016           63,613              

🏆 Fastest: BytesHyperQ with 313,053 items/s
   1.4x faster than HyperQ
   1.9x faster than faster-fifo
   4.9x faster than multiprocessing.Queue

================================================================================
Sleeping 2 seconds before next test configuration...

Results for 100,000 messages of 32768 bytes per producer:
Total messages: 400,000 (4 producers, 4 consumers)
--------------------------------------------------------------------------------
Queue Type           Total Time (s)  Latency (ms)    Throughput (items/s)
--------------------------------------------------------------------------------
BytesHyperQ          2.374           0.006           168,526             
HyperQ               2.887           0.007           138,536             
faster-fifo          3.804           0.010           105,154             
multiprocessing.Queue 10.354          0.026           38,634              

🏆 Fastest: BytesHyperQ with 168,526 items/s
   1.2x faster than HyperQ
   1.6x faster than faster-fifo
   4.4x faster than multiprocessing.Queue
Running bytes performance benchmarks...
================================================================================

Results for 100,000 messages of 32 bytes per producer:
Total messages: 100,000 (1 producers, 1 consumers)
--------------------------------------------------------------------------------
Queue Type           Total Time (s)  Latency (ms)    Throughput (items/s)
--------------------------------------------------------------------------------
BytesHyperQ          0.018           0.000           5,528,243           
HyperQ               0.090           0.001           1,106,593           
multiprocessing.Queue 0.334           0.003           299,499             
faster-fifo          0.406           0.004           246,330             

🏆 Fastest: BytesHyperQ with 5,528,243 items/s
   5.0x faster than HyperQ
   18.5x faster than multiprocessing.Queue
   22.4x faster than faster-fifo

================================================================================
Sleeping 2 seconds before next test configuration...

Results for 100,000 messages of 64 bytes per producer:
Total messages: 100,000 (1 producers, 1 consumers)
--------------------------------------------------------------------------------
Queue Type           Total Time (s)  Latency (ms)    Throughput (items/s)
--------------------------------------------------------------------------------
BytesHyperQ          0.020           0.000           5,067,022           
HyperQ               0.090           0.001           1,105,261           
multiprocessing.Queue 0.388           0.004           257,635             
faster-fifo          0.397           0.004           251,805             

🏆 Fastest: BytesHyperQ with 5,067,022 items/s
   4.6x faster than HyperQ
   19.7x faster than multiprocessing.Queue
   20.1x faster than faster-fifo

================================================================================
Sleeping 2 seconds before next test configuration...

Results for 100,000 messages of 128 bytes per producer:
Total messages: 100,000 (1 producers, 1 consumers)
--------------------------------------------------------------------------------
Queue Type           Total Time (s)  Latency (ms)    Throughput (items/s)
--------------------------------------------------------------------------------
BytesHyperQ          0.025           0.000           3,988,545           
HyperQ               0.102           0.001           984,694             
multiprocessing.Queue 0.332           0.003           301,471             
faster-fifo          0.402           0.004           248,764             

🏆 Fastest: BytesHyperQ with 3,988,545 items/s
   4.1x faster than HyperQ
   13.2x faster than multiprocessing.Queue
   16.0x faster than faster-fifo

================================================================================
Sleeping 2 seconds before next test configuration...

Results for 100,000 messages of 256 bytes per producer:
Total messages: 100,000 (1 producers, 1 consumers)
--------------------------------------------------------------------------------
Queue Type           Total Time (s)  Latency (ms)    Throughput (items/s)
--------------------------------------------------------------------------------
BytesHyperQ          0.030           0.000           3,280,452           
HyperQ               0.098           0.001           1,024,640           
multiprocessing.Queue 0.344           0.003           290,311             
faster-fifo          0.395           0.004           253,071             

🏆 Fastest: BytesHyperQ with 3,280,452 items/s
   3.2x faster than HyperQ
   11.3x faster than multiprocessing.Queue
   13.0x faster than faster-fifo

================================================================================
Sleeping 2 seconds before next test configuration...

Results for 100,000 messages of 512 bytes per producer:
Total messages: 100,000 (1 producers, 1 consumers)
--------------------------------------------------------------------------------
Queue Type           Total Time (s)  Latency (ms)    Throughput (items/s)
--------------------------------------------------------------------------------
BytesHyperQ          0.028           0.000           3,550,212           
HyperQ               0.105           0.001           956,745             
multiprocessing.Queue 0.357           0.004           279,993             
faster-fifo          0.420           0.004           238,251             

🏆 Fastest: BytesHyperQ with 3,550,212 items/s
   3.7x faster than HyperQ
   12.7x faster than multiprocessing.Queue
   14.9x faster than faster-fifo

================================================================================
Sleeping 2 seconds before next test configuration...

Results for 100,000 messages of 1024 bytes per producer:
Total messages: 100,000 (1 producers, 1 consumers)
--------------------------------------------------------------------------------
Queue Type           Total Time (s)  Latency (ms)    Throughput (items/s)
--------------------------------------------------------------------------------
BytesHyperQ          0.042           0.000           2,390,645           
HyperQ               0.109           0.001           917,085             
multiprocessing.Queue 0.379           0.004           263,922             
faster-fifo          0.413           0.004           241,983             

🏆 Fastest: BytesHyperQ with 2,390,645 items/s
   2.6x faster than HyperQ
   9.1x faster than multiprocessing.Queue
   9.9x faster than faster-fifo

================================================================================
Sleeping 2 seconds before next test configuration...

Results for 100,000 messages of 4096 bytes per producer:
Total messages: 100,000 (1 producers, 1 consumers)
--------------------------------------------------------------------------------
Queue Type           Total Time (s)  Latency (ms)    Throughput (items/s)
--------------------------------------------------------------------------------
BytesHyperQ          0.077           0.001           1,296,410           
HyperQ               0.153           0.002           653,955             
multiprocessing.Queue 0.420           0.004           238,116             
faster-fifo          0.437           0.004           228,823             

🏆 Fastest: BytesHyperQ with 1,296,410 items/s
   2.0x faster than HyperQ
   5.4x faster than multiprocessing.Queue
   5.7x faster than faster-fifo

================================================================================
Sleeping 2 seconds before next test configuration...

Results for 100,000 messages of 8192 bytes per producer:
Total messages: 100,000 (1 producers, 1 consumers)
--------------------------------------------------------------------------------
Queue Type           Total Time (s)  Latency (ms)    Throughput (items/s)
--------------------------------------------------------------------------------
BytesHyperQ          0.107           0.001           936,460             
HyperQ               0.203           0.002           492,091             
multiprocessing.Queue 0.497           0.005           201,165             
faster-fifo          0.539           0.005           185,473             

🏆 Fastest: BytesHyperQ with 936,460 items/s
   1.9x faster than HyperQ
   4.7x faster than multiprocessing.Queue
   5.0x faster than faster-fifo

================================================================================
Sleeping 2 seconds before next test configuration...

Results for 100,000 messages of 16384 bytes per producer:
Total messages: 100,000 (1 producers, 1 consumers)
--------------------------------------------------------------------------------
Queue Type           Total Time (s)  Latency (ms)    Throughput (items/s)
--------------------------------------------------------------------------------
BytesHyperQ          0.189           0.002           528,889             
HyperQ               0.303           0.003           329,876             
multiprocessing.Queue 0.658           0.007           152,017             
faster-fifo          0.762           0.008           131,168             

🏆 Fastest: BytesHyperQ with 528,889 items/s
   1.6x faster than HyperQ
   3.5x faster than multiprocessing.Queue
   4.0x faster than faster-fifo

================================================================================
Sleeping 2 seconds before next test configuration...

Results for 100,000 messages of 32768 bytes per producer:
Total messages: 100,000 (1 producers, 1 consumers)
--------------------------------------------------------------------------------
Queue Type           Total Time (s)  Latency (ms)    Throughput (items/s)
--------------------------------------------------------------------------------
BytesHyperQ          0.375           0.004           266,432             
HyperQ               0.484           0.005           206,720             
faster-fifo          0.939           0.009           106,544             
multiprocessing.Queue 1.053           0.011           94,985              

🏆 Fastest: BytesHyperQ with 266,432 items/s
   1.3x faster than HyperQ
   2.5x faster than faster-fifo
   2.8x faster than multiprocessing.Queue

================================================================================
Sleeping 2 seconds before next test configuration...

Results for 100,000 messages of 32 bytes per producer:
Total messages: 400,000 (4 producers, 4 consumers)
--------------------------------------------------------------------------------
Queue Type           Total Time (s)  Latency (ms)    Throughput (items/s)
--------------------------------------------------------------------------------
BytesHyperQ          0.097           0.000           4,142,198           
HyperQ               0.313           0.001           1,276,678           
faster-fifo          0.863           0.002           463,335             
multiprocessing.Queue 2.907           0.007           137,604             

🏆 Fastest: BytesHyperQ with 4,142,198 items/s
   3.2x faster than HyperQ
   8.9x faster than faster-fifo
   30.1x faster than multiprocessing.Queue

================================================================================
Sleeping 2 seconds before next test configuration...

Results for 100,000 messages of 64 bytes per producer:
Total messages: 400,000 (4 producers, 4 consumers)
--------------------------------------------------------------------------------
Queue Type           Total Time (s)  Latency (ms)    Throughput (items/s)
--------------------------------------------------------------------------------
BytesHyperQ          0.108           0.000           3,713,089           
HyperQ               0.336           0.001           1,189,575           
faster-fifo          0.847           0.002           472,108             
multiprocessing.Queue 2.928           0.007           136,622             

🏆 Fastest: BytesHyperQ with 3,713,089 items/s
   3.1x faster than HyperQ
   7.9x faster than faster-fifo
   27.2x faster than multiprocessing.Queue

================================================================================
Sleeping 2 seconds before next test configuration...

Results for 100,000 messages of 128 bytes per producer:
Total messages: 400,000 (4 producers, 4 consumers)
--------------------------------------------------------------------------------
Queue Type           Total Time (s)  Latency (ms)    Throughput (items/s)
--------------------------------------------------------------------------------
BytesHyperQ          0.104           0.000           3,838,310           
HyperQ               0.293           0.001           1,365,044           
faster-fifo          0.880           0.002           454,557             
multiprocessing.Queue 2.968           0.007           134,779             

🏆 Fastest: BytesHyperQ with 3,838,310 items/s
   2.8x faster than HyperQ
   8.4x faster than faster-fifo
   28.5x faster than multiprocessing.Queue

================================================================================
Sleeping 2 seconds before next test configuration...

Results for 100,000 messages of 256 bytes per producer:
Total messages: 400,000 (4 producers, 4 consumers)
--------------------------------------------------------------------------------
Queue Type           Total Time (s)  Latency (ms)    Throughput (items/s)
--------------------------------------------------------------------------------
BytesHyperQ          0.121           0.000           3,306,829           
HyperQ               0.346           0.001           1,156,464           
faster-fifo          0.848           0.002           471,452             
multiprocessing.Queue 3.024           0.008           132,281             

🏆 Fastest: BytesHyperQ with 3,306,829 items/s
   2.9x faster than HyperQ
   7.0x faster than faster-fifo
   25.0x faster than multiprocessing.Queue

================================================================================
Sleeping 2 seconds before next test configuration...

Results for 100,000 messages of 512 bytes per producer:
Total messages: 400,000 (4 producers, 4 consumers)
--------------------------------------------------------------------------------
Queue Type           Total Time (s)  Latency (ms)    Throughput (items/s)
--------------------------------------------------------------------------------
BytesHyperQ          0.139           0.000           2,870,961           
HyperQ               0.413           0.001           968,493             
faster-fifo          0.892           0.002           448,522             
multiprocessing.Queue 3.143           0.008           127,257             

🏆 Fastest: BytesHyperQ with 2,870,961 items/s
   3.0x faster than HyperQ
   6.4x faster than faster-fifo
   22.6x faster than multiprocessing.Queue

================================================================================
Sleeping 2 seconds before next test configuration...

Results for 100,000 messages of 1024 bytes per producer:
Total messages: 400,000 (4 producers, 4 consumers)
--------------------------------------------------------------------------------
Queue Type           Total Time (s)  Latency (ms)    Throughput (items/s)
--------------------------------------------------------------------------------
BytesHyperQ          0.209           0.001           1,918,401           
HyperQ               0.546           0.001           732,611             
faster-fifo          0.929           0.002           430,677             
multiprocessing.Queue 3.299           0.008           121,240             

🏆 Fastest: BytesHyperQ with 1,918,401 items/s
   2.6x faster than HyperQ
   4.5x faster than faster-fifo
   15.8x faster than multiprocessing.Queue

================================================================================
Sleeping 2 seconds before next test configuration...

Results for 100,000 messages of 4096 bytes per producer:
Total messages: 400,000 (4 producers, 4 consumers)
--------------------------------------------------------------------------------
Queue Type           Total Time (s)  Latency (ms)    Throughput (items/s)
--------------------------------------------------------------------------------
BytesHyperQ          0.400           0.001           1,001,018           
HyperQ               0.745           0.002           536,564             
faster-fifo          1.176           0.003           340,031             
multiprocessing.Queue 4.032           0.010           99,196              

🏆 Fastest: BytesHyperQ with 1,001,018 items/s
   1.9x faster than HyperQ
   2.9x faster than faster-fifo
   10.1x faster than multiprocessing.Queue

================================================================================
Sleeping 2 seconds before next test configuration...

Results for 100,000 messages of 8192 bytes per producer:
Total messages: 400,000 (4 producers, 4 consumers)
--------------------------------------------------------------------------------
Queue Type           Total Time (s)  Latency (ms)    Throughput (items/s)
--------------------------------------------------------------------------------
BytesHyperQ          0.679           0.002           589,081             
HyperQ               1.111           0.003           359,917             
faster-fifo          1.554           0.004           257,363             
multiprocessing.Queue 4.742           0.012           84,353              

🏆 Fastest: BytesHyperQ with 589,081 items/s
   1.6x faster than HyperQ
   2.3x faster than faster-fifo
   7.0x faster than multiprocessing.Queue

================================================================================
Sleeping 2 seconds before next test configuration...

Results for 100,000 messages of 16384 bytes per producer:
Total messages: 400,000 (4 producers, 4 consumers)
--------------------------------------------------------------------------------
Queue Type           Total Time (s)  Latency (ms)    Throughput (items/s)
--------------------------------------------------------------------------------
BytesHyperQ          1.278           0.003           313,053             
HyperQ               1.765           0.004           226,633             
faster-fifo          2.442           0.006           163,817             
multiprocessing.Queue 6.288           0.016           63,613              

🏆 Fastest: BytesHyperQ with 313,053 items/s
   1.4x faster than HyperQ
   1.9x faster than faster-fifo
   4.9x faster than multiprocessing.Queue

================================================================================
Sleeping 2 seconds before next test configuration...

Results for 100,000 messages of 32768 bytes per producer:
Total messages: 400,000 (4 producers, 4 consumers)
--------------------------------------------------------------------------------
Queue Type           Total Time (s)  Latency (ms)    Throughput (items/s)
--------------------------------------------------------------------------------
BytesHyperQ          2.374           0.006           168,526             
HyperQ               2.887           0.007           138,536             
faster-fifo          3.804           0.010           105,154             
multiprocessing.Queue 10.354          0.026           38,634              

🏆 Fastest: BytesHyperQ with 168,526 items/s
   1.2x faster than HyperQ
   1.6x faster than faster-fifo
   4.4x faster than multiprocessing.Queue

Results may vary depending on hardware and system configuration.

🔧 API Reference

HyperQ

class HyperQ:
    def __init__(self, capacity: int, name: str = None)

    def put(self, item) -> bool
    def get(self)  # Blocks until data is available
    def empty(self) -> bool
    def full(self) -> bool
    def size(self) -> int
    def clear(self)

BytesHyperQ

class BytesHyperQ:
    def __init__(self, capacity: int, name: str = None)

    def put(self, data: bytes) -> bool
    def get(self) -> bytes  # Blocks until data is available
    def empty(self) -> bool
    def full(self) -> bool
    def size(self) -> int
    def clear(self)

Parameters

capacity: Maximum size of the queue in bytes
name: Optional name for the shared memory segment (max 28 characters)

Important Notes

Blocking operations: get() blocks indefinitely until data is available
No timeout support: Currently no timeout functionality is implemented
Queue names: Must be 28 characters or less
Platform limitation: Only works on Unix-like systems (Linux/macOS)

🧪 Running Tests

# Run all tests
pytest

# Run with coverage
pytest --cov=hyperq

📈 Running Benchmarks

# 1 producer, 1 consumer benchmark
python benchmarks/benchmark_bytes_transfering_1p_1c.py

# 10 producers, 10 consumers benchmark
python benchmarks/benchmark_bytes_transfering_10p_10c.py

🏗️ Building from Source

Prerequisites

Python 3.10+
Cython >= 0.29.0
C++ compiler with C++20 support (GCC 8+, Clang 10+)
Unix-like system (Linux or macOS)

Build Steps

# Clone the repository
git clone https://github.com/martinmkhitaryan/hyperq.git
cd hyperq

# Install build dependencies
pip install -e ".[test]"

# Build the extension
python setup.py build_ext --inplace

🤝 Contributing

Development Setup

Fork the repository
Create a virtual environment: python -m venv .venv
Activate it: source .venv/bin/activate (Linux/macOS)
Install development dependencies: pip install -e ".[test]"
Run tests: pytest
Make your changes and submit a pull request

📝 License

This project is licensed under the MIT License - see the LICENSE file for details.

🙏 Acknowledgments

Built with Cython for high-performance Python extensions
Uses POSIX shared memory and threading primitives
Inspired by the need for faster inter-process communication in Python

📞 Support

Issues: GitHub Issues
Discussions: GitHub Discussions
Email: mkhitaryan.martin@2000gmail.com

🔄 Version History

0.0.9: Updated benchmarks in README.md.
0.0.8: Updated benchmark suite, test suite, pyproject.toml configuration; optimized CI/CD release workflow.
0.0.7: Replaced is_creator logic with ref count logic for better shared memory management; identified and documented issue with multiprocessing spawn start method not working properly with multiple consumers and producers.
0.0.6: Fix cibuildwheel configurations.
0.0.5: Added platform-specific build and skip patterns for Linux and macOS; improved cibuildwheel configuration with separate build targets for manylinux and macosx wheels
0.0.4: Fixed cibuildwheel configuration for proper multi-platform wheel builds; added architecture-specific settings for Linux (x86_64/i686) and macOS (x86_64/arm64);
0.0.3: Fixed cibuildwheel configuration for proper linux wheel build;
0.0.2: Added proper PyPI wheel support for Linux and macOS using cibuildwheel; improved release workflow for multi-platform builds and C++20 compatibility
0.0.1: Initial release with HyperQ and BytesHyperQ implementations

Project details

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Release history Release notifications | RSS feed

1.0.0

Aug 24, 2025

0.1.0

Jul 5, 2025

This version

0.0.9

Jul 5, 2025

0.0.8

Jul 5, 2025

0.0.7

Jul 2, 2025

0.0.6

Jun 26, 2025

0.0.5

Jun 26, 2025

0.0.4

Jun 26, 2025

0.0.3

Jun 26, 2025

0.0.2

Jun 26, 2025

0.0.1

Jun 26, 2025

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