5. Workflow

There are two recommended workflows :

• the first one:

  1. design your whole actions tree model and build it
  2. create and assign encoders and handlers

• The second is more complient with the YAGNI [*] idiom philosophy :

  You only populate your model and create encoders/handlers when a need arise in the source code redaction.

Of course, these are just recommandations, not commandements.

5.1. The recommended setup

The recommended setup is to create a module which only purpose is to build the action tree, importing it in both client and server scripts and assigning there encoders and handlers

here is an example for a pseudo chat program :

[tree.py] :

from netbytes import p_build

model = '''
client_message (msg:str)
server_message (sender:str, msg:str)'''

tree = p_build(model)

[client.py] :

from netbytes import data_decode
from tree import tree

# let's assume that 'conn' is a connection made with the server

@tree.client_message.ENCODER
def msg_encoder(msg):
    return msg

@tree.server_message.HANDLER
def msg_server_handler(data):
    sender, msg = data_decode(data)
    widget_text.append('{} >>> {}\n'.format(sender, msg))

def on_return_pressed(event):
    msg = widget_entry.get()
    conn.send(tree.client_message(msg))

# assume we are inside a thread
while 1:
    data = conn.recieve()
    tree._handle(data)

[server.py] :

from netbytes import data_encode
from tree import tree

# let's assume that 'conn' is a connection made with the client, and that 'conn.name' returns the name of the client
# let's also assume that 'conns' is a list of all client connections

@tree.server_message.ENCODER
def msg_encoder(sender, msg):
    return data_encode([server,msg])

@tree.client_message.HANDLER
def msg_client_handler(data):
    msg = data
    for conn in conns:
        conn.send(tree.server_message(conn.name, msg))

# assume we are inside a thread
while 1:
    data = conn.recieve()
    tree._handle(data)

[*]	: You Ain’t Gonna Need It