faster-fifo
Faster alternative to Python's standard multiprocessing.Queue (IPC FIFO queue). Up to 30x faster in some configurations.
Implemented in C++ using POSIX mutexes with PTHREAD_PROCESS_SHARED attribute. Based on a circular buffer, low footprint, brokerless.
Completely mimics the interface of the standard multiprocessing.Queue, so can be used as a drop-in replacement.
Adds get_many()
and put_many()
methods to receive/send multiple messages at once for the price of a single lock.
Requirements
- Linux or MacOS
- Python 3.6 or newer
- GCC 4.9.0 or newer
Installation
pip install faster-fifo
(on a fresh Linux installation you might need some basic compiling tools sudo apt install --reinstall build-essential gcc g++
)
Manual build instructions
pip install Cython
python setup.py build_ext --inplace
pip install -e .
Usage example
from faster_fifo import Queue
from queue import Full, Empty
q = Queue(1000 * 1000)
py_obj = dict(a=42, b=33, c=(1, 2, 3), d=[1, 2, 3], e='123', f=b'kkk')
q.put(py_obj)
assert q.qsize() == 1
retrieved = q.get()
assert q.empty()
assert py_obj == retrieved
for i in range(100):
try:
q.put(py_obj, timeout=0.1)
except Full:
log.debug('Queue is full!')
num_received = 0
while num_received < 100:
messages = q.get_many(max_messages_to_get=100)
num_received += len(messages)
try:
q.get(timeout=0.1)
assert True, 'This won\'t be called'
except Empty:
log.debug('Queue is empty')
Performance comparison (faster-fifo vs multiprocessing.Queue)
System #1 (Intel(R) Core(TM) i9-7900X CPU @ 3.30GHz, 10 cores, Ubuntu 18.04)
(measured execution times in seconds)
| multiprocessing.Queue | faster-fifo, get() | faster-fifo, get_many() |
---|
1 producer 1 consumer (200K msgs per producer) | 2.54 | 0.86 | 0.92 |
1 producer 10 consumers (200K msgs per producer) | 4.00 | 1.39 | 1.36 |
10 producers 1 consumer (100K msgs per producer) | 13.19 | 6.74 | 0.94 |
3 producers 20 consumers (100K msgs per producer) | 9.30 | 2.22 | 2.17 |
20 producers 3 consumers (50K msgs per producer) | 18.62 | 7.41 | 0.64 |
20 producers 20 consumers (50K msgs per producer) | 36.51 | 1.32 | 3.79 |
System #2 (Intel(R) Core(TM) i5-4200U CPU @ 1.60GHz, 2 cores, Ubuntu 18.04)
(measured execution times in seconds)
| multiprocessing.Queue | faster-fifo, get() | faster-fifo, get_many() |
---|
1 producer 1 consumer (200K msgs per producer) | 7.86 | 2.09 | 2.2 |
1 producer 10 consumers (200K msgs per producer) | 11.68 | 4.01 | 3.88 |
10 producers 1 consumer (100K msgs per producer) | 44.48 | 16.68 | 5.98 |
3 producers 20 consumers (100K msgs per producer) | 22.59 | 7.83 | 7.49 |
20 producers 3 consumers (50K msgs per producer) | 66.3 | 22.3 | 6.35 |
20 producers 20 consumers (50K msgs per producer) | 78.75 | 14.39 | 15.78 |
Run tests
pip install numpy
python -m unittest
(there are also C++ unit tests, should run them if C++ code was altered)
Recent PyPI releases
v1.4.6
- Added missing
<cstdio>
causing issues with newer g++. Thank you mesaglio!
v1.4.5
- Added method
data_size()
to query the total size of the messages in queue (in bytes). Thank you @LucaNicosia!
v1.4.4
- Fixed an obscure issue with the TLSBuffer ctor being called without arguments (guessing it's Cython's weirdness)
v1.4.3
- Simplified usage with "spawn" multiprocessing context. No need to use
faster_fifo_reduction
anymore. Thank you @MosBas!
v1.4.2
- Fixed an issue with the custom Queue pickler
v1.4.1
- Fixed multithreading issues using threading.local for message recv buffer (huge thanks to @brianmacy!)
- Better error reporting in Cython and C++
- Added threading tests
v1.4.0
- Increase default receive buffer size from 10 bytes to 5000 bytes.
v1.3.1
- Minor change: better debugging messages + improved C++ tests
v1.3.0
- Now support custom serializers and deserializers instead of Pickle (thank you @beasteers!):
q = Queue(max_size_bytes=100000, loads=custom_deserializer, dumps=custom_serializer)
Originally designed for SampleFactory, a high-throughput asynchronous RL codebase https://github.com/alex-petrenko/sample-factory.
Programmed by Aleksei Petrenko and Tushar Kumar at USC RESL.
Developed under MIT License, feel free to use for any purpose, commercial or not, at your own risk.
If you wish to cite this repository:
@misc{faster-fifo,
author={Petrenko, Aleksei and Kumar, Tushar},
title={A Faster Alternative to Python's multiprocessing.Queue},
publisher={GitHub},
journal = {GitHub repository},
howpublished = {\url{https://github.com/alex-petrenko/faster-fifo}},
year={2020},
}