netmem

Basic memory synchronization across the network in Python.

This package has a network-synchronized dictionary that runs on asyncio event loops. It supports binding to the dictionary similar to tk.Variable() and is also compatible with tkinter and its event loops.

Installation

The easiest way is to just open your favorite terminal and type

pip install netmem

Alternatively you can clone this repo and install it with

python setup.py install

Requirements

• The amazing aiohttp library
• Python v3.5+

The basis for netmem is asynchronous IO and event loops, so I apologize to Python v2.x users and for that matter, Python v3.4. Although Python v3.4 supports asyncio, I really like the async for and async with constructs introduced in v3.5, and I use them in a number of places. Since Python is already on v3.6 at the time of this writing, I do not feel too terribly bad leaving v3.4 behind.

Usage

Here is the smallest meaningful example I can come up with. Run it on two different computers on the same network.

import tkinter as tk
import netmem

def main():
    print("Run this on two different computers.")
    mem = netmem.NetworkMemory()
    mem.connect_on_new_thread(netmem.UdpConnector(local_addr=("225.0.0.1", 9991)))

    tk1 = tk.Tk()
    lbl = tk.Label(tk1, text="Favorite operating system:")
    lbl.pack()
    txt = tk.Entry(tk1, textvariable=mem.tk_var("fav_os"))
    txt.pack()

    tk1.mainloop()


if __name__ == "__main__":
    main()

You can bind a listener to the NetworkMemory object to be notified when a value changes, such as when an update arrives over the network. The listener works like the following code snippet.

def memory_changed(netmem_dict, key, old_val, new_val)
    print("Update  {}:{}".format(key, new_val))

def main():
    mem = netmem.NetworkMemory()
    mem.add_listener(memory_changed)
    mem["foo"] = "bar"

The output from this would be the following

Update foo:bar

Incidentally the underlying BindableDict class is pretty handy on its own, without even the network synchronizing capabilities.

Data Structure

NetworkMemory subclasses a Python dictionary, so you can access the data within it as you do any dictionary object. Additionally you can bind listeners to NetworkMemory (because in fact it subclasses a bindable dictionary, which is something I borrowed from other code I wrote).