Python 进程之间的总线
Python bus between processes
我完全从我的机器人大脑开始。一切都是在 Python 中开发的。
我想尽可能保持一切模块化，并允许使用多个 CPU 核心 (Raspberry PI 2)。
我想到了使用多进程。一个用于串行通信，一个用于每个传感器，一个用于每个更高的功能。
全部通过转向 "brain" 功能连接。
我想通过消息总线连接进程。例如。如果每个传感器飞镖它自己的总线。然后更高的功能和大脑可以登录总线。在最佳情况下，我也想发送整个对象。
- 有没有好的框架提供总线？
- 整个主题是否有更好的方法？
谢谢
罗伯特
尝试nanomsg（ZeroMQ 的后续项目）：
nanomsg is a socket library that provides several common communication
patterns. It aims to make the networking layer fast, scalable, and
easy to use. Implemented in C, it works on a wide range of operating
systems with no further dependencies.
The communication patterns, also called "scalability protocols", are
basic blocks for building distributed systems. By combining them you
can create a vast array of distributed applications. The following
scalability protocols are currently available:
- PAIR - simple one-to-one communication
- BUS - simple many-to-many communication
- REQREP - allows to build clusters of stateless services to process user requests
- PUBSUB - distributes messages to large sets of interested subscribers
- PIPELINE - aggregates messages from multiple sources and load balances them among many destinations
- SURVEY - allows to query state of multiple applications in a single go
我完全从我的机器人大脑开始。一切都是在 Python 中开发的。
我想尽可能保持一切模块化，并允许使用多个 CPU 核心 (Raspberry PI 2)。
我想到了使用多进程。一个用于串行通信，一个用于每个传感器，一个用于每个更高的功能。 全部通过转向 "brain" 功能连接。
我想通过消息总线连接进程。例如。如果每个传感器飞镖它自己的总线。然后更高的功能和大脑可以登录总线。在最佳情况下，我也想发送整个对象。
- 有没有好的框架提供总线？
- 整个主题是否有更好的方法？
谢谢
罗伯特
尝试nanomsg（ZeroMQ 的后续项目）：
nanomsg is a socket library that provides several common communication patterns. It aims to make the networking layer fast, scalable, and easy to use. Implemented in C, it works on a wide range of operating systems with no further dependencies.
The communication patterns, also called "scalability protocols", are basic blocks for building distributed systems. By combining them you can create a vast array of distributed applications. The following scalability protocols are currently available:
- PAIR - simple one-to-one communication
- BUS - simple many-to-many communication
- REQREP - allows to build clusters of stateless services to process user requests
- PUBSUB - distributes messages to large sets of interested subscribers
- PIPELINE - aggregates messages from multiple sources and load balances them among many destinations
- SURVEY - allows to query state of multiple applications in a single go