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Merge pull request #104 from OFFIS-DAI/feature-api-transfer
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Draft: API overhaul, mango 2.0.0
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rcschrg authored Oct 16, 2024
2 parents 4b6f48a + 70f7411 commit 59c7bf8
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8 changes: 7 additions & 1 deletion .github/workflows/test-mango.yml
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Expand Up @@ -18,7 +18,7 @@ jobs:
strategy:
fail-fast: false
matrix:
python-version: ["3.8", "3.9", "3.10", "3.11", "3.12"]
python-version: ["3.10", "3.11", "3.12"]
steps:
- uses: actions/checkout@v4
- name: Set up Python
Expand All @@ -32,6 +32,8 @@ jobs:
pip install virtualenv
virtualenv venv
source venv/bin/activate
pip3 install -U sphinx
pip3 install -r docs/requirements.txt
pip3 install -r requirements.txt
pip3 install -e .
sudo apt update
Expand All @@ -44,6 +46,10 @@ jobs:
source venv/bin/activate
ruff check .
ruff format --check .
- name: Doctests
run: |
source venv/bin/activate
make -C docs doctest
- name: Test+Coverage
run: |
source venv/bin/activate
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1 change: 1 addition & 0 deletions docs/source/_static/Logo_mango_ohne_sub_white.svg
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163 changes: 128 additions & 35 deletions docs/source/agents-container.rst
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Expand Up @@ -12,58 +12,153 @@ serialization and deserialization of messages.
Container also help to to speed up message exchange between agents that run on the same physical hardware,
as data that is exchanged between such agents will not have to be sent through the network.

In mango, a container is created using the classmethod ``mango.create_container``:
In mango, a container is created using factory methods:

* :meth:`mango.create_tcp_container`
* :meth:`mango.create_mqtt_container`
* :meth:`mango.create_ec_container`

Most of the time, the tcp container should be the default choice if you wanna create simulations, which run in real time using
a simple but fast network protocol.

.. code-block:: python3
@classmethod
async def create_container(cls, *, connection_type: str = 'tcp', codec: Codec = None, clock: Clock = None,
addr: Optional[Union[str, Tuple[str, int]]] = None,
proto_msgs_module=None,
**kwargs):
def create_tcp_container(
addr: str | tuple[str, int],
codec: Codec = None,
clock: Clock = None,
copy_internal_messages: bool = False,
**kwargs: dict[str, Any],
) -> Container:
The factory methods are asyncio-free, meaning most of the time you can create containers without a running asyncio loop.

The factory method is a coroutine, so it has to be scheduled within a running asyncio loop.
A simple container, that uses plain tcp for message exchange can be created as follows:

.. code-block:: python3
.. testcode::

import asyncio
from mango import create_container
from mango import create_tcp_container

async def get_simple_container():
container = await create_container(addr=('localhost', 5555))
def get_simple_container():
container = create_tcp_container(addr=('localhost', 5555))
return container

simple_container = asyncio.run(get_simple_container()))
print(get_simple_container().addr)

.. testoutput::

('localhost', 5555)

The container type depends totally on the factory method you invoke. Every supported type has its own class backing
the functionality.

A container can be parametrized regarding its connection type ('tcp' or 'MQTT') and
regarding the codec that is used for message serialization.
The default codec is JSON (see section :doc:`codecs` for more information). It is also possible to
define the clock that an agents scheduler should use (see section scheduling).
define the clock that an agents scheduler should use (see page :doc:`scheduling`).

Note, that container creation is different from container starting. Before you can work with a container
you will want to register Agents, and then start (or activate) the container. This shall be done using an
asynchronous context manager, which we provide by invoking :meth:`mango.activate`.

.. testcode::

import asyncio
from mango import create_tcp_container, activate

async def start_container():
container = create_tcp_container(addr=('localhost', 5555))

async with activate(container) as c:
print("The container is activated now!")
await asyncio.sleep(0.1) # activate the container for 0.1 seconds, most of the time you want to include e.g. a condition to await
print("The container is automatically shut down, even on exceptions!")

asyncio.run(start_container())

.. testoutput::

After a container is created, it is waiting for incoming messages on the given address.
As soon as the container has some agents, it will distribute incoming messages
to the corresponding agents and allow agents to send messages to other agents.
The container is activated now!
The container is automatically shut down, even on exceptions!

At the end of its lifetime, a ``container`` should be shutdown by using the method ``shutdown()``.
It will then shutdown all agents that are still running
in this container and cancel running tasks.
At the end of its lifetime, a ``container`` the container will shutdown. This will be done by the context manager, so no need for the
user to worry about it. This will also shutdown all agents that are still running in this container and cancel running tasks.

***************
mango agents
***************
mango agents can be implemented by inheriting from the abstract class ``mango.Agent``.
This class provides basic functionality such as to register the agent at the container or
to constantly check the inbox for incoming messages.
Every agent lives in exactly one container and therefore an instance of a container has to be
provided when :py:meth:`__init__()` of an agent is called.
Custom agents that inherit from the ``Agent`` class have to call ``super().__init__(container, suggested_aid: str = None)__``
on initialization.
This will register the agent at the provided container instance and will assign a unique agent id
(``self.aid``) to the agent. However, it is possible to suggest an aid by setting the variable ``suggested_aid`` to your aid wish.
This class provides basic functionality such as to scheduling convenience methods or to constantly check the inbox for incoming messages.
Every agent can live in exactly one container, to register an agent the method :meth:`mango.Container.register` can be used. This method will assign
the agent a generated agent id (aid) and enables the agent scheduling feature.

However, it is possible to suggest an aid by setting the parameter ``suggested_aid`` of :meth:`mango.Container.register` to your aid wish.
The aid is granted if there is no other agent with this id, and if the aid doesn't interfere with the default aid pattern, otherwise
the generated aid will be used. To check if the aid is available beforehand, you can use ``container.is_aid_available``.
It will also create the task to check for incoming messages.

Note that, custom agents that inherit from the ``Agent`` class have to call ``super().__init__()__`` on initialization.

.. testcode::

from mango import Agent, create_tcp_container

class MyAgent(Agent):
pass

async def create_and_register_agent():
container = create_tcp_container(addr=('localhost', 5555))

agent = container.register(MyAgent(), suggested_aid="CustomAgent")
return agent

print(asyncio.run(create_and_register_agent()).aid)

.. testoutput::

CustomAgent

Further there are some important lifecycle methods you often want to implement:

* :meth:`mango.Agent.on_ready`
* Called when all containers have been activated during the activate call, which started the container the agent is registered in.
* At this point all relevant containers have been started and the agent is already registered. This is the correct method for starting to send messages, even to other containers.
* :meth:`mango.Agent.on_register`
* Called when the Agent just has been registered.
* At this point the scheduler is initialized and the agent address is known, but no communication can happen yet.
* :meth:`mango.Agent.on_start`
* Called when the container of the agent has been started during activation.
* At this point internal communication is possible and depending on your setup external communication could be done too.

Besides the lifecycle, one of the main functions implemented in Agents are message exchange function. For this part read :doc:`/message exchange`.

*********************************
Express setup of mango simulation
*********************************

It is not necessary to create the container all by yourself, as you often want to just distribute some agents evenly to a number of containers. This can be done
with an asynchronous context manager created by :meth:`mango.run_with_tcp` (:meth:`mango.run_with_mqtt` for MQTT protocol). This method just expects the number of containers
you want to start and the agents, which shall run in these containers.

With this method sending a message to an agent in another container looks like this:

.. testcode::

import asyncio
from mango import PrintingAgent, run_with_tcp

async def run_with_tcp_example():
agent_tuple = (PrintingAgent(), dict(aid="MyAgent"))
single_agent = PrintingAgent()

async with run_with_tcp(2, agent_tuple, single_agent) as cl:
# cl is the list of containers, which are created internally
await agent_tuple[0].send_message("Hello, print me!", single_agent.addr)
await asyncio.sleep(0.1)

asyncio.run(run_with_tcp_example())

.. testoutput::

Received: Hello, print me! with {'sender_id': 'MyAgent', 'sender_addr': ['127.0.0.1', 5555], 'receiver_id': 'agent0', 'network_protocol': 'tcp', 'priority': 0}

***************
agent process
Expand All @@ -74,12 +169,10 @@ register the agent in a slightly different way.
.. code-block:: python3
process_handle = await main_container.as_agent_process(
agent_creator=lambda sub_container: TestAgent(
container, aid_main_agent, suggested_aid=f"process_agent1"
)
agent_creator=lambda sub_container: sub_container.register(MyAgent(), suggested_aid=f"process_agent1")
)
The process_handle is awaitable and will finish exactly when the process is fully set up. Further, it contains the pid `process_handle.pid`.
The ``process_handle`` is awaitable and will finish exactly when the process is fully set up. Further, it contains the pid ``process_handle.pid``.

Note that after the creation, the agent lives in a mirror container in another process. Therefore, it is not possible to interact
with the agent directly from the main process. If you want to interact with the agent after the creation, it is possible to
Expand All @@ -89,6 +182,6 @@ dispatch a task in the agent process using `dispatch_to_agent_process`.
main_container.dispatch_to_agent_process(
pid,
your_function, # will be called with the mirror container + x as arguments
your_function, # will be called with the mirror container + varargs as arguments
... # varargs, additional arguments you want to pass to your_function
)
21 changes: 17 additions & 4 deletions docs/source/api_ref/index.rst
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Expand Up @@ -2,17 +2,30 @@
API reference
=============

The API reference provides detailed descriptions of mango's classes and
The API reference provides detailed descriptions of the mango's classes and
functions.

Subpackages
-----------
.. automodule:: mango
:members:
:undoc-members:
:imported-members:
:inherited-members:


.. note::
Note that, most classes and functions described in the API reference
should be imported using `from mango import ...`, as the stable and public API
generally will be available by using `mango` and the internal module structure
might change, even in minor releases.

By subpackages
---------------

.. toctree::
:maxdepth: 2

mango.express
mango.agent
mango.container
mango.messages
mango.modules
mango.util
6 changes: 3 additions & 3 deletions docs/source/api_ref/mango.agent.rst
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@@ -1,15 +1,15 @@
mango.agent package
Agents API
===================

mango.agent.core module
Agent core
-----------------------

.. automodule:: mango.agent.core
:members:
:undoc-members:
:show-inheritance:

mango.agent.role module
Roles
-----------------------

.. automodule:: mango.agent.role
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