NOTE:
speedysvc's status is alpha - it should be functional and don't intend to make major changes, but the web management and configuration interface API might be changed later. It's actively maintained and am using it for my https://langlynx.com service but there may well be bugs!Mac OSX is not currently supported, though there I plan to investigate whether this is feasible.
This module for python 3.6+ on Linux and Windows allows separating larger, more complex applications into smaller components (microservices). For example, you could build a text-to-speech service, an optical character recognition service, etc. Then, you could have web frontends or other clients communicate with these services. This can often require less RAM, as there is no need to load the components in every web worker process.
Unlike other similar modules for client-server communication (which typically use sockets or HTTP REST), this module uses local shared memory, which typically performs around 10-30 times faster with much lower latency. speedysvc servers can also be remotely communicated with over the network using TCP sockets. The TCP protocol is fast and efficient, and optionally compresses traffic using snappy/zlib to minimise bandwidth.
In order to work around limitations of python's Global Interpreter Lock which normally restricts applications from using more than a single CPU core, services can have multiple worker processes. They optionally can increase or decrease worker processes as needed, depending on CPU usage. This helps to make sure server resources are more effectively used. While this is possible with the multiprocessing module, multiprocessing on Linux uses pipe2 for communication between processes, which is much slower than using shared memory.
There is a service management web interface that shows logs/performance data for each service and allows stopping/starting services individually. Each service is started separately in individual processes with individual logs so as to be able to track down events and errors without being overwhelmed with too much information.
See also Implementation Considerations.
The following are needed prior to installation:
- OS: Windows or Linux (tested on Ubuntu 18.04 LTS, other POSIX systems other than Mac OS X may also be supported)
- Python: version 3.6 or above
- Dependencies for Windows only: You must first download the "Visual Studio Build Tools 2019" from https://visualstudio.microsoft.com/downloads/
speedysvc also has the below dependencies, but these should be installed automatically with the pip3 install command in the "install" section.
- Module Dependencies: cython, msgpack, cherrypy, psutil
- Module Dependencies for Linux/POSIX only: posix_ipc
Then, for both Windows or Linux, type the following commands into a command prompt/terminal window:
pip3 install --upgrade pip
pip3 install Cython
pip3 install git+https://github.com/mcyph/speedysvcSee also Install/Dependencies.
echoserver.py:
from speedysvc import ServerMethodsBase, json_method
from speedysvc.client_server.base_classes.ServerMethodsBase import ServerMethodsBase
class EchoServer(ServerMethodsBase):
port = 5555
name = 'echo_serv'
@json_method
def echo_json(self, data):
return dataechoclient.py:
from speedysvc import connect
from speedysvc.client_server.base_classes.ClientMethodsBase import ClientMethodsBase
from echoserver import EchoServer
class EchoClient(ClientMethodsBase):
def echo_json(self, data):
return self.send(EchoServer.echo_json, [data])
if __name__ == '__main__':
# Note: Replace 'shm://' with 'tcp://(host)' for remote services
methods = EchoClient(connect(EchoServer, 'shm://'))
print(methods.echo_json("Hello World!"))service.ini:
[defaults]
# Uncomment this line to listen on the network
#bind_tcp=(host adaptor)
log_dir=/tmp/test_server_logs/
[EchoServer]
import_from=echoserver
max_proc_num=3
min_proc_num=3Then type python3 -m speedysvc.service service.ini & from the same directory to start the server. The web management interface will start on http://127.0.0.1:5155, where you can monitor the status and logs of the server.
Then, type python3 echoclient.py to test a connection to the server.
See Example for a a more complex example.
Similar projects:
- Ray (for running distributed applications)
- Allow running services as Docker containers
- Better log searching/filtering
- REST requests
Licensed under the MIT License.
Copyright 2020 Dave Morrissey
Permission is hereby granted, free of charge, to any person obtaining a copy of this software and associated documentation files (the "Software"), to deal in the Software without restriction, including without limitation the rights to use, copy, modify, merge, publish, distribute, sublicense, and/or sell copies of the Software, and to permit persons to whom the Software is furnished to do so, subject to the following conditions:
The above copyright notice and this permission notice shall be included in all copies or substantial portions of the Software.
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