Merge pull request #87 from maurerle/fix_lint

Improve codebase by running linter checks

.github/workflows/publish-mango.yml

@@ -37,4 +37,4 @@ jobs:
       - name: Publish package
         uses: pypa/gh-action-pypi-publish@v1
         with:
-          password: ${{ secrets.PYPI_API_TOKEN }}
+          password: ${{ secrets.PYPI_API_TOKEN }}

.github/workflows/test-mango.yml

@@ -5,7 +5,7 @@ on: [push]
 permissions:
   contents: read
 
-jobs: 
+jobs:
   build:
     runs-on: ubuntu-latest
     strategy:
@@ -36,4 +36,4 @@ jobs:
       run: |
         source venv/bin/activate
         coverage run -m pytest
-        coverage report
+        coverage report

.gitignore

@@ -105,4 +105,4 @@ docs/build/
 docs/source/_build
 
 # Git
-*.orig
+*.orig

.readthedocs.yaml

@@ -17,4 +17,4 @@ formats:
 python:
    version: "3.7"
    install:
-   - requirements: docs/requirements.txt
+   - requirements: docs/requirements.txt

docs/requirements.txt

@@ -6,4 +6,4 @@ imagesize==0.7.1
 Jinja2==2.9
 MarkupSafe==0.23
 Sphinx==4.0.2
-sphinx-rtd-theme==0.5.2
+sphinx-rtd-theme==0.5.2

docs/source/ACL messages.rst

@@ -1 +0,0 @@
-

docs/source/agents-container.rst

@@ -60,15 +60,15 @@ 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. 
-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 
+(``self.aid``) to the agent. However, it is possible to suggest an aid by setting the variable ``suggested_aid`` 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.
 
 ***************
 agent process
 ***************
-To improve multicore utilization, mango provides a way to distribute agents to processes. For this, it is necessary to create and 
+To improve multicore utilization, mango provides a way to distribute agents to processes. For this, it is necessary to create and
 register the agent in a slightly different way.
 
 .. code-block:: python3
@@ -82,7 +82,7 @@ The process_handle is awaitable and will finish exactly when the process is full
 
 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
-dispatch a task in the agent process using `dispatch_to_agent_process`. 
+dispatch a task in the agent process using `dispatch_to_agent_process`.
 
 .. code-block:: python3
     main_container.dispatch_to_agent_process(

docs/source/codecs.rst

@@ -5,12 +5,12 @@ Codecs
 Most of the codec related code is taken and adapted from aiomas:
 https://gitlab.com/sscherfke/aiomas/
 
-Codecs enable the container to encode and decode known data types to send them as messages. 
+Codecs enable the container to encode and decode known data types to send them as messages.
 Mango already contains two codecs: A json serializer that can (recursively) handle any json serializable object and a protobuf codec
-that will wrap an object into a generic protobuf message. Other codecs can be implemented by inheriting 
-from the ``Codec`` base class and implementing its ``encode`` and ``decode`` methods. 
-Codecs will only handle types explicitely known to them. 
-New known types can be added to a codec with the ``add_serializer`` method. 
+that will wrap an object into a generic protobuf message. Other codecs can be implemented by inheriting
+from the ``Codec`` base class and implementing its ``encode`` and ``decode`` methods.
+Codecs will only handle types explicitely known to them.
+New known types can be added to a codec with the ``add_serializer`` method.
 This method expects a type together with a serialization method and a deserialization method that translate the object into a format
 the codec can handle (for example a json-serializable string for the json codec).
 
@@ -137,7 +137,7 @@ All that is left to do now is to pass our codec to the container. This is done d
 **@json_serializable decorator**
 
 In the above example we explicitely defined methods to (de)serialize our class. For simple classes, especially data classes,
-we can achieve the same result (for json codecs) via the ``@json_serializable`` decorator. This creates the ``__asdict__``, 
+we can achieve the same result (for json codecs) via the ``@json_serializable`` decorator. This creates the ``__asdict__``,
 ``__fromdict__`` and ``__serializer__`` functions in the class:
 
 .. code-block:: python3
@@ -178,10 +178,10 @@ provides the `codecs.FastJson` codec. This codec usese `msgspec` and does not pr
 proto codec and ACLMessage
 ##########################
 
-Serialization methods for the proto codec are expected to encode the object into a protobuf message object with the ``SerializeToString`` 
+Serialization methods for the proto codec are expected to encode the object into a protobuf message object with the ``SerializeToString``
 method.
-The codec then wraps the message into a generic message wrapper, containing the serialized 
-protobuf message object and a type id. 
+The codec then wraps the message into a generic message wrapper, containing the serialized
+protobuf message object and a type id.
 This is necessary because in general the original type of a protobuf message can not be infered
 from its serialized form.
 
@@ -280,6 +280,3 @@ process by making the proto type known to the codec using the ``register_proto_t
 
     b'\x08\x01\x12\x0c\x12\nsome_bytes'
     content: "some_bytes"
-
-
-    

docs/source/conf.py

@@ -12,21 +12,20 @@
 #
 import os
 import sys
-import sphinx_rtd_theme
 
 # If extensions (or modules to document with autodoc) are in another directory,
 # add these directories to sys.path here. If the directory is relative to the
 # documentation root, use os.path.abspath to make it absolute, like shown here.
-sys.path.insert(0, os.path.abspath('../../mango'))
+sys.path.insert(0, os.path.abspath("../../mango"))
 
 # -- Project information -----------------------------------------------------
 
-project = 'mango'
-copyright = '2023, mango team'
-author = 'mango team'
+project = "mango"
+copyright = "2023, mango team"
+author = "mango team"
 
 # The full version, including alpha/beta/rc tags
-release = '0.1'
+release = "0.1"
 
 
 # -- General configuration ---------------------------------------------------
@@ -35,17 +34,17 @@
 # extensions coming with Sphinx (named 'sphinx.ext.*') or your custom
 # ones.
 extensions = [
-    'sphinx.ext.autodoc',
-    'sphinx.ext.doctest',
-    'sphinx.ext.intersphinx',
-    'sphinx.ext.graphviz',
-    'sphinx.ext.imgmath',
-    'sphinx_rtd_theme',
+    "sphinx.ext.autodoc",
+    "sphinx.ext.doctest",
+    "sphinx.ext.intersphinx",
+    "sphinx.ext.graphviz",
+    "sphinx.ext.imgmath",
+    "sphinx_rtd_theme",
 ]
 
 
 # Add any paths that contain templates here, relative to this directory.
-templates_path = ['_templates']
+templates_path = ["_templates"]
 
 # List of patterns, relative to source directory, that match files and
 # directories to ignore when looking for source files.
@@ -58,9 +57,9 @@
 # The theme to use for HTML and HTML Help pages.  See the documentation for
 # a list of builtin themes.
 #
-html_theme = 'sphinx_rtd_theme'
+html_theme = "sphinx_rtd_theme"
 
 # Add any paths that contain custom static files (such as style sheets) here,
 # relative to this directory. They are copied after the builtin static files,
 # so a file named "default.css" will overwrite the builtin "default.css".
-html_static_path = ['_static']
+html_static_path = ["_static"]

docs/source/customizing-container.rst

@@ -6,4 +6,4 @@ A mango container can be customized regarding its way it connects to other conta
 
 ***************
 connection type
-***************
+***************

docs/source/development.rst

@@ -2,12 +2,12 @@
 Development Guidelines
 ======================
 
-As we mainly work in a critical domain, we set great value on code quality not only to ensure correctness, but also to improve readability and maintainability. To reach this goal we have to set some standards regarding the development process and the test quality. 
+As we mainly work in a critical domain, we set great value on code quality not only to ensure correctness, but also to improve readability and maintainability. To reach this goal we have to set some standards regarding the development process and the test quality.
 
 Quickstart
 ##########
 
-In mango it is not possible to directly push on the branches *development* or *master*. Both branches are protected and changes can only be merged using a github pull-request. So when you work on a feature, the typical process would be to create a feature-branch. When you are finished you just have to create a merge-request, pass the CI/CD pipeline, make a maintainer review the changes, and you are ready to merge! 
+In mango it is not possible to directly push on the branches *development* or *master*. Both branches are protected and changes can only be merged using a github pull-request. So when you work on a feature, the typical process would be to create a feature-branch. When you are finished you just have to create a merge-request, pass the CI/CD pipeline, make a maintainer review the changes, and you are ready to merge!
 
 CI/CD
 #####
@@ -32,7 +32,7 @@ A unit test is a test for the smallest possible testable part of the code. This
 Integration Tests
 *****************
 
-An integration test is everything what aims to test more than one unit. 
+An integration test is everything what aims to test more than one unit.
 
 Coverage
 *****************
@@ -42,12 +42,12 @@ We aim to reach a code coverage of > 90%. Currently, we measure the **statement*
 Reviews
 *****************
 
-Tests are great but do not lead to better readability and maintainability. One part that will is the review process. In mango we came to the understanding that we want to review **every** change, which should be merged into the development branch. There are no exceptions to this. The idea is not only to check the code for errors, bad smells and security flaws, its part of generating a common understanding of good coding. 
+Tests are great but do not lead to better readability and maintainability. One part that will is the review process. In mango we came to the understanding that we want to review **every** change, which should be merged into the development branch. There are no exceptions to this. The idea is not only to check the code for errors, bad smells and security flaws, its part of generating a common understanding of good coding.
 
 Linting
 *****************
 
-Another approach to improve the code quality is static code analysis, or better known as linting. Linting is an easy to set up possibility to make sure that a certain code standard is fulfilled. There are many useful rules, which can be checked automatically, so we have another line of defense and spare some time when reviewing. 
+Another approach to improve the code quality is static code analysis, or better known as linting. Linting is an easy to set up possibility to make sure that a certain code standard is fulfilled. There are many useful rules, which can be checked automatically, so we have another line of defense and spare some time when reviewing.
 
 Formatting
 *****************
@@ -57,4 +57,4 @@ The project is formatted using black + isort with default settings.
 ```bash
 isort mango examples tests
 black mango examples tests
-```
+```

docs/source/installation.rst

@@ -48,5 +48,3 @@ __ https://mosquitto.org/
     The protobuf codec is an optional feature that you need to explicity install if you need it.
 
     **TODO: make protobuf optional**
-
-

docs/source/migration.rst

@@ -14,4 +14,4 @@ mango 0.4.0 to 1.0.0
 * The parameters create_acl and acl_metadata from 'send_message' has been removed: use send_acl_message instead
 * The parameter mqtt_kwargs from 'send_message' has been removed: use kwargs instead
 * The DateTimeScheduledTask has been removed: use TimestampScheduledTask instead
-* The context and scheduler of an agent are no longer public: use the convenience methods for sending/scheduling or _context, _scheduler from within the agent
+* The context and scheduler of an agent are no longer public: use the convenience methods for sending/scheduling or _context, _scheduler from within the agent

docs/source/scheduling.rst

@@ -61,7 +61,7 @@ When using the scheduling another feature becomes available: suspendable tasks.
 Dispatch Tasks to other Process
 *******************************
 
-As asyncio does not provide real parallelism to utilize multiple cores and agents may have tasks, which need a lot computational power, the need to dispatch certain tasks to other processes appear. Handling inter process communication manually is quite exhausting and having multiple process pools across different roles or agents leads to inefficient resource allocations. As a result mango offers a way to dispatch tasks, based on coroutine-functions, to other processes, managed by the framework. 
+As asyncio does not provide real parallelism to utilize multiple cores and agents may have tasks, which need a lot computational power, the need to dispatch certain tasks to other processes appear. Handling inter process communication manually is quite exhausting and having multiple process pools across different roles or agents leads to inefficient resource allocations. As a result mango offers a way to dispatch tasks, based on coroutine-functions, to other processes, managed by the framework.
 
 Analogues to the normal API there are two different ways, first you create a ScheduledProcessTask and call ``schedule_process_task``, second you invoke the convnience methods with "process" in the name. These methods exists on any Agent, the RoleContext and the Scheduler.
 In mango the following process tasks are available:
@@ -190,4 +190,3 @@ If you comment in the ExternalClock and change your main() as follows, the progr
             clock.set_time(clock.time + 5)
         await receiver.wait_for_reply
         await c.shutdown()
-

docs/source/tutorial.rst

@@ -8,10 +8,10 @@ Introduction
 
 This tutorial gives an overview of the basic functions of mango agents and containers. It consists of four
 parts building a scenario of two PV plants, operated by their respective agents being directed by a remote
-controller. 
+controller.
 
-Each part comes with a standalone executable file. Subsequent parts either extend the functionality or simplify 
-some concept in the previous part. 
+Each part comes with a standalone executable file. Subsequent parts either extend the functionality or simplify
+some concept in the previous part.
 
 As a whole, this tutorial covers:
     - container and agent creation
@@ -92,10 +92,10 @@ Now we can create our agents. Agents always live inside a container and this con
     pv_agent_0 = PVAgent(pv_container)
     pv_agent_1 = PVAgent(pv_container)
 
-For now, our agents are purely passive entities. To make them do something, we need to send them a message. Messages are 
+For now, our agents are purely passive entities. To make them do something, we need to send them a message. Messages are
 passed by the container via the ``send_message`` function always at least expects some content and a target address.
 To send a message directly to an agent, we also need to provide its agent id which is set by the container when the agent
-is created. 
+is created.
 
 .. code-block:: python
 
@@ -120,7 +120,7 @@ This concludes the first part of our tutorial. If you run this code, you should
     | Hello I am a PV agent! My id is agent0.
     | Hello I am a PV agent! My id is agent1.
     | Received message with content: Hello, this is a simple message. and meta {'network_protocol': 'tcp', 'priority': 0}.
-   
+
 
 .. raw:: html
 
@@ -170,7 +170,7 @@ The replies to feed_in requests and later the acknowledgements that a new maximu
 We use the ``performative`` field of the ACL message to do this. We set the ``performative`` field to ``inform``
 for feed_in replies and to ``accept_proposal`` for feed_in change acknowledgements. All messages between containers
 are expected to be ACL Messages (or implement the split_content_and_meta function). Since we do not want to create
-the full ACL object ourselves every time, within this example we always use the convenience method 
+the full ACL object ourselves every time, within this example we always use the convenience method
 ``container.send_acl_message``, which also supports setting the acl metadata.
 
 .. code-block:: python
@@ -270,7 +270,7 @@ perform its active actions. We do this by implementing a ``run`` function with t
 - send a feed_in request to each known pv agent
 - wait for all pv agents to answer
 - find the minimum reported feed_in
-- send a maximum feed_in setpoint of this minimum to each pv agent 
+- send a maximum feed_in setpoint of this minimum to each pv agent
 - again, wait for all pv agents to reply
 - terminate
 
@@ -406,7 +406,7 @@ This example covers:
    <summary><a>step by step</a></summary>
 
 We want to use the types of custom message objects as the new mechanism for message typing. We define these
-as simple data classes. For simple classes like this, we can use the ``json_serializable`` decorator to 
+as simple data classes. For simple classes like this, we can use the ``json_serializable`` decorator to
 provide us with the serialization functionality.
 
 .. code-block:: python
@@ -454,7 +454,7 @@ Next, we need to create a codec, make our message objects known to it, and pass
     )
 
 Any time the content of a message matches one of these types now the corresponding serialize and deserialize
-functions are called. Of course, you can also create your own serialization and deserialization functions with 
+functions are called. Of course, you can also create your own serialization and deserialization functions with
 more sophisticated behaviours and pass them to the codec. For more details refer to the ``codecs`` section of
 the documentation.
 
@@ -507,7 +507,7 @@ you should receive the same output as in part 2:
 Corresponding file: `v4_scheduling_and_roles.py`
 
 In example 3, you restructured your code to use codecs for easier handling of typed message objects.
-Now it is time to expand the functionality of our controller. In addition to setting the maximum feed_in 
+Now it is time to expand the functionality of our controller. In addition to setting the maximum feed_in
 of the pv agents, the controller should now also periodically check if the pv agents are still reachable.
 
 To achieve this, the controller should send a regular "ping" message to each pv agent that is in turn answered
@@ -527,7 +527,7 @@ Thus, things like message handlers that require container knowledge are introduc
 
 This example covers:
     - role API basics
-    - scheduling and periodic tasks 
+    - scheduling and periodic tasks
 
 .. raw:: html
 

examples/distributed_clock/README.md

@@ -13,4 +13,4 @@ If the `clock_agent`s routine takes longer, the manager will wait for it to fini
 
 Caution: it is needed, that all agents are connected before starting the manager
 
-This example is tested with MQTT as well as by using TCP connection
+This example is tested with MQTT as well as by using TCP connection

examples/distributed_clock/clock_agent.py

@@ -3,7 +3,6 @@
 from typing import TypedDict
 
 import numpy as np
-
 from mango import Role, RoleAgent, create_container
 from mango.messages.message import Performatives
 from mango.util.clock import ExternalClock

examples/distributed_clock/clock_manager.py

@@ -132,7 +132,7 @@ async def main(start):
     if isinstance(clock, ExternalClock):
         for i in tqdm(range(30)):
             next_event = await clock_agent.distribute_time()
-            logger.info(f"current step: {clock.time}")
+            logger.info("current step: %s", clock.time)
             await tasks_complete_or_sleeping(c)
             # comment next line to see that the first message is not received in correct timings
             # also comment sleep(0) in termination_detection to see other timing problems