?? Unveiling the Future of Software Development: The Power Duo of Chatman Calculus & Design For Lean Six Sigma ??
Sean Chatman
Available for Staff/Senior Front End Generative AI Web Development (Typescript/React/Vue/Python)
In the dynamic world of software development, the quest for perfection never ends. Enter the game-changing alliance of Chatman Calculus and Design for Lean Six Sigma (DFLSS) ??. This fusion is not just a methodology; it's a revolution, promising to redefine efficiency, quality, and alignment in software projects. Let's dive into how this power duo is set to transform the software landscape.
?? Define Phase: Setting the Stage with Vision and Strategy
?? Measure Phase: Crafting Quality with Data and Insight
?? Explore Phase: Where Innovation Meets Precision
??? Develop Phase: Refining Ideas into Impact
?? Implement Phase: Launching Success
?? The Bottom Line: A Future Bright with Innovation and Excellence
The marriage of Chatman Calculus and DFLSS is more than a methodology—it's a movement towards building software solutions that are not only technologically advanced but also deeply resonant with users and aligned with business goals. Ready to set new benchmarks for quality, efficiency, and impact in the software world? Join us on this exhilarating journey to the future of software development! ??????
Let's make magic happen with every code commit! ?????????? #SoftwareRevolution #InnovationUnleashed #FutureOfCoding
Creating a calculus notation for something like Chatman Calculus, especially within the context of software development methodologies such as Reactive Domain-Driven Design (RDDDY) and integrating formal verification techniques, requires establishing a formalism that captures the essence of domain logic, actor behaviors, message passing, and system invariants. Let's outline a foundational structure for Chatman Calculus, focusing on its application to actor systems and domain-driven design.
Chatman Calculus Notation for Actor Systems in RDDDY
Chatman Calculus aims to provide a rigorous foundation for reasoning about the correctness and domain alignment of software systems, particularly those built on the actor model and adhering to principles of RDDDY. This calculus will integrate aspects of formal verification, domain-specific logic, and the operational semantics of actor-based systems.
1. Formalization of Actor Behaviors
Actor behaviors are central to the design and functionality of systems in RDDDY. The Chatman Calculus formalizes these behaviors through preconditions, actions, and postconditions, incorporating domain logic to ensure alignment with real-world requirements.
2. Message Dispatching and Handling
In the context of RDDDY, messages drive the interaction between actors, necessitating a formal approach to message dispatching and handling that ensures system responsiveness and domain fidelity.
3. System Invariants and Domain Assertions
The integrity of a system built with RDDDY principles relies on maintaining certain invariants and adhering to domain assertions throughout the system's operation.
4. Operational Semantics for RDDDY Systems
Operational semantics defined within Chatman Calculus provide a comprehensive framework for understanding the execution and interaction dynamics of actor-based systems in RDDDY.
Conclusion and Application
Chatman Calculus provides a structured approach to designing, verifying, and reasoning about systems built on the principles of Reactive Domain-Driven Design. By formalizing actor behaviors, message handling, system invariants, and domain assertions, developers and researchers can ensure that their systems are not only technically sound but also closely aligned with their intended application domains. This calculus serves as a bridge between theoretical formalism and practical application, offering a robust foundation for the development of reliable, domain-specific software systems.
Integrating Chatman Calculus with Design for Lean Six Sigma (DFLSS): A Revolutionary Approach to Software Development
The fusion of Chatman Calculus and Design for Lean Six Sigma (DFLSS) marks a groundbreaking advancement in software development methodologies. This integrated approach not only emphasizes efficiency and quality in the development process but also ensures that software systems are robust, responsive, and perfectly aligned with user needs and business goals. Here’s a deep dive into how the combination of these methodologies revolutionizes each phase of software development.
Define Phase: Laying the Foundation with Precision and Clarity
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Measure Phase: Elevating Quality with Data-Driven Insights
Explore Phase: Innovating with Purpose and Precision
Develop Phase: Refining and Validating with Rigor
Implement Phase: Bringing Innovations to Life
Conclusion: A Synergistic Future
The integration of Chatman Calculus with DFLSS presents a holistic and innovative approach to software development, one that prioritizes domain alignment, customer value, and operational excellence. By marrying the strategic focus of DFLSS with the domain-specific rigor of Chatman Calculus, we pave the way for developing software solutions that are not just technologically advanced but also deeply embedded in the fabric of user needs and business strategies. This synergistic approach promises to elevate the field of software development, setting new benchmarks for quality, efficiency, and impact.
Unveiling the Power of Chatman Calculus: Revolutionizing Software Development ????
In the ever-evolving world of software development, the quest for efficiency, reliability, and domain fidelity never ceases. Today, we're taking a giant leap into the future with the introduction of Chatman Calculus ??, a groundbreaking framework set to redefine the landscape of Reactive Domain-Driven Design (RDDDY). Let's dive into what makes Chatman Calculus not just another methodology, but a transformative force in tech. ????
Why Chatman Calculus? ????
At its core, Chatman Calculus is about bridging gaps—between theory and practice, between developers and domain experts, and between software and its operational domain. By treating domain knowledge as a first-class citizen, Chatman Calculus empowers us to build systems that are not just code-compliant but are deeply rooted in the real-world context they aim to serve. ???
The Magic Behind Chatman Calculus ????
Real-World Impact ????
From enhancing software quality to preemptively squashing bugs, Chatman Calculus is more than just a methodology—it's a paradigm shift. It paves the way for proactive problem-solving, empowers domain experts to contribute more effectively, and guarantees the success of RDDDY systems by ensuring they are resilient, consistent, and responsive. ????
Join the Revolution! ????
As we explore the boundless possibilities of Chatman Calculus, we invite you—developers, researchers, and tech enthusiasts—to join us on this exciting journey. Whether it's through engaging in discussions, contributing to case studies, or integrating Chatman Calculus into your own projects, there's a place for everyone in shaping the future of software development. ????
The Road Ahead ?????
The unveiling of Chatman Calculus is just the beginning. As we continue to refine and expand its applications, the potential for innovation is limitless. Stay tuned for more updates, and let's embark on this transformative journey together. The future of software development is here, and it's brighter than ever with Chatman Calculus leading the way! ???
Join the conversation and share your thoughts on how Chatman Calculus can revolutionize the way we think about software development. Let's make the future of tech not just smarter, but more aligned with the world it aims to serve. #ChatmanCalculus #SoftwareRevolution #TechInnovation #FutureOfDevelopment ????
Abstract
The landscape of software development continuously evolves, necessitating advanced methodologies that bridge the gap between theoretical rigor and practical applicability. This paper introduces an enhanced version of Chatman Calculus, a pioneering framework developed to refine formal verification techniques within the Reactive Domain-Driven Design (RDDDY) paradigm. Chatman Calculus distinguishes itself by treating domain knowledge as a first-class citizen, employing a two-tiered assertion model that seamlessly integrates description logics and semantic lifting. This approach not only ensures that software systems are precisely aligned with their intended application domains but also facilitates a deeper, semantic-driven analysis of program states. Through comprehensive case studies and real-world applications, this paper demonstrates how Chatman Calculus effectively addresses complex software development challenges, significantly improving system reliability, maintainability, and performance. By advancing the theoretical foundations of RDDDY and formal verification, Chatman Calculus sets a new benchmark for developing domain-compliant, robust software architectures.
Conclusion
The development and subsequent refinement of Chatman Calculus represent a significant leap forward in the synthesis of Reactive Domain-Driven Design and formal verification methodologies. This paper has outlined the theoretical advancements and practical applications of Chatman Calculus, demonstrating its capacity to enhance software quality and reliability through a nuanced, domain-specific approach to system design and verification. The introduction of a two-tiered assertion model, leveraging description logics and semantic lifting, enables developers and domain experts alike to engage in a more collaborative, informed software development process.
The real-world case studies presented herein validate the framework's effectiveness in navigating complex development challenges, underscoring the practical benefits of integrating formal verification techniques with domain-driven design principles. Furthermore, the positive reception and constructive feedback from the software development community have illuminated paths for future research and development, suggesting that the potential applications of Chatman Calculus extend far beyond the current scope.
As we look ahead, it is clear that Chatman Calculus not only enriches the toolkit available to software engineers and researchers but also paves the way for more intelligent, adaptable, and robust software systems. The ongoing evolution of this framework, driven by community engagement and interdisciplinary collaboration, promises to further dissolve the barriers between theoretical computer science and practical software engineering. In conclusion, Chatman Calculus stands as a testament to the transformative potential of marrying rigorous formal methods with the dynamic needs of domain-driven software development, offering a beacon for future explorations at this intersection.
actor_system.py
"""
Actor System Module Documentation
This module, actor_system.py, implements the ActorSystem class within the Reactive Domain-Driven Design (RDDDY) framework. It serves as the orchestrator for actor lifecycle management, message passing, and system-wide coordination, ensuring that the principles of the Actor model are adhered to in a domain-driven context.
Overview:
The ActorSystem is responsible for creating, managing, and terminating actors, facilitating asynchronous message passing between them, and maintaining system invariants. It is designed to operate seamlessly within an asynchronous programming environment, leveraging Python's asyncio library to handle concurrent operations efficiently.
ActorSystem Multiline Calculus Notation (AMCN):
The behavior and operations within the ActorSystem are rigorously defined by the ActorSystem Multiline Calculus Notation (AMCN), ensuring a formalized approach to actor management and message dissemination. The AMCN outlines the preconditions, actions, and postconditions for each operation within the system, integrating domain-specific assertions to align computational processes with the system's domain logic.
1. Actor Lifecycle Management
Actor Creation (??????????????Acreate):
- Precondition (Pre Pre): ????∈??∣??.????=?????????? ??a∈A∣a.id=id new
- Action: ??????????????????????(??????????,????????)→???????? createActor(id new,Type)→a new
- Postcondition (Post Post): ???∈??∣??.????=??????????∧??.????????=???????? ?a∈A∣a.id=id new∧a.type=Type
2. Message Dispatching
Direct Message Sending (??????????Msend):
- Precondition (Pre Pre): ???????????????,????????????????????∈?? ?a sender,a recipient∈A
- Action: ??????????????????????(??????????????,????????????????????,??) sendMessage(a sender,a recipient,m)
- Postcondition (Post Post): ??∈????????????????????.?????????????? m∈a recipient.mailbox
Broadcast Messaging (??????????????????????broadcast):
- Precondition (Pre Pre): ???????????????∈?? ?a sender∈A
- Action: ????????????????????????????????(??????????????,??) broadcastMessage(a sender,m)
- Postcondition (Post Post): ???∈???{??????????????},??∈??.?????????????? ?a∈A?{a sender},m∈a.mailbox
3. System Invariants and Domain Assertions
Invariant Preservation (??????????????????Ipreserve):
- Invariant (?? I): Φ(??,??) Φ(A,M)
- Upon Action (????????????action): ????????????(??,??)→??′,??′ action(A,M)→A′,M′
- Preservation (??′I′): Φ(??′,??′) Φ(A′,M′)
Domain-Specific Logic Integration (????????????????????Dintegrate):
- Precondition (Pre ?? Pre D): Δ(??????????????) Δ(s global)
- Action and Domain Logic: ???????????????????????????????????????????????????????(??,??,Δ)→??????????????′,Δ′ performActionWithDomainLogic(a,m,Δ)→s global′,Δ′
- Postcondition (Post ?? Post D): Δ′(??????????????′) Δ′(s global′)
Implementation Details:
The ActorSystem is implemented with a focus on modularity, scalability, and ease of use. It provides a high-level API for actor management and message passing, abstracting away the complexities of asynchronous programming and actor coordination. Developers can leverage the ActorSystem to build complex, responsive applications that are both computationally correct and domain-compliant.
Usage:
To use the ActorSystem, instantiate it within your application and use its methods to create actors and manage message passing. The system integrates seamlessly with the asyncio event loop, making it straightforward to incorporate into existing asynchronous applications.
The actor_system.py module, guided by the AMCN, provides a robust foundation for developing actor-based systems within the RDDDY framework, ensuring that applications are built with a solid architectural foundation that promotes maintainability, scalability, and domain-driven design principles.
"""
from asyncio import Future
import asyncio
from typing import TYPE_CHECKING, TypeVar
from loguru import logger
import reactivex as rx
from reactivex import operators as ops
from reactivex.scheduler.eventloop import AsyncIOScheduler
from rdddy.messages import Message
if TYPE_CHECKING:
from rdddy.actor import Actor
T = TypeVar("T", bound="Actor")
class ActorSystem:
"""
Orchestrates actor lifecycle management, message passing, and system-wide coordination within the RDDDY framework.
The ActorSystem class provides functionalities for creating, managing, and terminating actors, facilitating asynchronous message passing between them, and maintaining system invariants.
Attributes:
actors (dict): A dictionary containing actor IDs as keys and corresponding actor instances as values.
loop (asyncio.AbstractEventLoop): The asyncio event loop used for asynchronous operations.
scheduler (AsyncIOScheduler): An asynchronous scheduler for controlling task execution.
event_stream (Subject): A subject for publishing events within the actor system.
Methods:
actor_of(actor_class, **kwargs): Creates a new actor instance and starts its mailbox processing loop.
actors_of(actor_classes, **kwargs): Creates multiple actor instances of different types.
publish(message): Publishes a message to the actor system for distribution.
remove_actor(actor_id): Removes an actor from the actor system.
send(actor_id, message): Sends a message to a specific actor within the system.
wait_for_event(event_type): Waits for a specific event type to occur within the system.
Implementation Details:
The ActorSystem class implements actor management and message passing functionalities, abstracting away the complexities of asynchronous programming and actor coordination. It integrates seamlessly with the asyncio event loop, ensuring efficient concurrent operations.
Usage:
Instantiate an ActorSystem object within your application to manage actors and coordinate message passing. Use its methods to create actors, send messages, and wait for specific events within the system.
"""
def __init__(self, loop: asyncio.AbstractEventLoop = None) -> None:
"""
Initializes the ActorSystem.
Args:
loop (asyncio.AbstractEventLoop, optional): The asyncio event loop to be used for asynchronous operations.
If not provided, the default event loop will be used.
Attributes:
actors (dict): A dictionary containing actor IDs as keys and corresponding actor instances as values.
loop (asyncio.AbstractEventLoop): The asyncio event loop used for asynchronous operations.
scheduler (AsyncIOScheduler): An asynchronous scheduler for controlling task execution.
event_stream (Subject): A subject for publishing events within the actor system.
"""
self.actors: dict[int, Actor] = {}
self.loop = loop if loop is not None else asyncio.get_event_loop()
self.scheduler = AsyncIOScheduler(loop=self.loop)
self.event_stream = rx.subject.Subject()
async def actor_of(self, actor_class, **kwargs) -> T:
"""
Creates a new actor instance and starts its mailbox processing loop.
T = TypeVar("T", bound="Actor")
Preconditions (Pre):
- None
Transition (T):
- Creates a new instance of the specified actor class.
- Initializes the actor's mailbox.
- Starts the processing loop for the actor's mailbox, enabling asynchronous message handling.
Postconditions (Post):
- A new actor instance has been created and started successfully.
Args:
actor_class: The class of the actor to be created.
**kwargs: Additional keyword arguments to be passed to the actor constructor.
Returns:
T: The created actor instance.
"""
actor = actor_class(self, **kwargs)
self.actors[actor.actor_id] = actor
await actor.start(self.scheduler)
return actor
async def actors_of(self, actor_classes, **kwargs) -> list[T]:
"""
Creates multiple actor instances of different types and starts their mailbox processing loops.
T = TypeVar("T", bound="Actor")
Preconditions (Pre):
- None
Transition (T):
- Creates new instances of the specified actor classes.
- Initializes the mailboxes for each actor.
- Starts the processing loop for each actor's mailbox, enabling asynchronous message handling.
Postconditions (Post):
- Multiple actor instances have been created and started successfully.
Args:
actor_classes (List[Type]): A list of actor classes to be instantiated.
**kwargs: Additional keyword arguments to be passed to the actor constructors.
Returns:
List[T]: A list containing the created actor instances.
"""
actors = []
for actor_class in actor_classes:
actor = await self.actor_of(actor_class, **kwargs)
actors.append(actor)
return actors
async def publish(self, message: "Message"):
"""
Publishes a message to the actor system for distribution.
Preconditions (Pre):
- None
Transition (T):
- Emits the message to the event stream of the actor system.
- Sends the message to each actor within the system for processing.
Postconditions (Post):
- The message has been published to the actor system and processed by relevant actors.
- If the message is an instance of the base Message class, an error is raised.
Args:
message (Message): The message to be published to the actor system.
Raises:
ValueError: If the base Message class is used directly.
"""
if type(message) is Message:
raise ValueError(
"The base Message class should not be used directly. Please use a subclass of Message."
)
self.event_stream.on_next(message)
actors = list(self.actors.values())
for actor in actors:
await self.send(actor.actor_id, message)
async def remove_actor(self, actor_id):
"""
Removes an actor from the actor system.
Preconditions (Pre):
- The actor ID must exist in the actor system.
Transition (T):
- Removes the actor with the specified ID from the actor system.
Postconditions (Post):
- The actor has been successfully removed from the actor system.
Args:
actor_id: The ID of the actor to be removed.
"""
actor = self.actors.pop(actor_id, None)
if actor:
logger.debug(f"Removing actor {actor_id}")
else:
logger.debug(f"Actor {actor_id} not found for removal")
logger.debug(f"Current actors count: {len(self.actors)}")
async def send(self, actor_id: int, message: "Message"):
"""
Sends a message to a specific actor within the actor system.
Preconditions (Pre):
- The actor ID must exist in the actor system.
- The message must be an instance of the Message class.
Transition (T):
- Delivers the message to the specified actor's mailbox for processing.
Postconditions (Post):
- The message has been successfully sent to the specified actor for processing.
Args:
actor_id (int): The ID of the target actor.
message (Message): The message to be sent to the target actor.
"""
logger.debug(f"Sending message {message} to actor {actor_id}")
actor = self.actors.get(actor_id)
if actor:
actor.mailbox.on_next(message)
await asyncio.sleep(0)
else:
logger.debug(f"Actor {actor_id} not found.")
async def wait_for_message(self, message_type: type) -> Future["Message"]:
"""
Waits for a message of a specific type to be published to the actor system.
Preconditions (Pre):
- None
Transition (T):
- Subscribes to the event stream of the actor system.
- Waits until a message of the specified type is published.
Postconditions (Post):
- A message of the specified type has been received from the actor system.
Args:
message_type (type): The type of message to wait for.
Returns:
asyncio.Future: A future object representing the awaited message.
"""
loop = asyncio.get_event_loop()
future = loop.create_future()
def on_next(msg):
if isinstance(msg, message_type):
future.set_result(msg)
subscription.dispose()
subscription = self.event_stream.pipe(
ops.filter(lambda msg: isinstance(msg, message_type))
).subscribe(on_next)
return await future
def __getitem__(self, actor_id) -> T:
"""
Retrieves an actor by its ID from the actor system.
Preconditions (Pre):
- The actor ID must exist in the actor system.
Transition (T):
- Retrieves the actor with the specified ID from the actor system.
Postconditions (Post):
- The actor with the specified ID has been successfully retrieved from the actor system.
Args:
actor_id: The ID of the actor to retrieve.
Returns:
Actor: The actor object corresponding to the specified ID.
"""
return self.actors.get(actor_id)
import asyncio
async def main():
print("main")
# await
if __name__ == "__main__":
asyncio.run(main())
actor.py
"""
The Actor Module for Reactive Domain-Driven Design (RDDDY) Framework
---------------------------------------------------------------------
This module implements the core Actor abstraction within the RDDDY framework, providing a robust foundation for building reactive, domain-driven systems that are scalable, maintainable, and capable of handling complex, concurrent interactions. The Actor model encapsulates both state and behavior, allowing for asynchronous message passing as the primary means of communication between actors, thus fostering loose coupling and enhanced system resilience.
### Overview
Actors are the fundamental units of computation in the RDDDY framework. Each actor possesses a unique identity, a mailbox for message queuing, and a set of behaviors to handle incoming messages. The Actor module facilitates the creation, supervision, and coordination of actors within an ActorSystem, ensuring that messages are delivered and processed in a manner consistent with the system's domain-driven design principles.
### Multiline Calculus for Actor Behavior Specification
The operational semantics of actors within the RDDDY framework are formalized through a rigorous multiline calculus, which outlines the preconditions, postconditions, and invariants that govern actor behavior and interaction. This calculus serves as a contract, ensuring that actors behave correctly and predictably within their designated domain contexts.
#### Actor State Transition
Given an actor \(A\) with state \(s\) and a message \(m\), the state transition is defined as:
Precondition ( Pre Pre): ?? ∈ ?? s∈S and ?? ∈ ?? m∈M
Transition: ?? ( ?? , ?? ) → ?? ′ T(s,m)→s ′
Postcondition ( Post Post): ?? ′ ∈ ?? ′ s ′ ∈S ′
#### Message Handling
For a message \(m\) handled by the actor, leading to a state modification:
Precondition ( Pre Pre): ?? ∈ ?? s∈S and ?? ∈ ?? m∈M
Handling: ?? ( ?? , ?? ) → ?? ′ ′ H(m,s)→s ′′
Postcondition ( Post Post): ?? ′ ′ ∈ ?? ′ ′ s ′′ ∈S ′′
#### Invariant Maintenance
Ensuring system invariants \(I\) across transitions:
Invariant: ?? ( ?? ) ∧ ?? ( ?? , ?? ) → ?? ′ ? ?? ( ?? ′ ) I(S)∧T(s,m)→s ′ ?I(S ′ )
#### Domain-Specific Assertions
Linking actor state transitions to domain logic:
Precondition ( Pre Pre): Δ ( ?? ) Δ(s) and ?? ( ?? ) δ(m)
Domain Logic: ?? ( ?? , ?? ) → Δ ( ?? ′ ) D(s,m)→Δ(s ′ )
Postcondition ( Post Post): Δ ′ ( ?? ′ ) Δ ′ (s ′ )
### Purpose
This calculus not only specifies the expected behavior of actors in response to messages but also integrates domain-specific knowledge, ensuring that actors operate in alignment with the broader domain-driven objectives of the system. By adhering to these specifications, the Actor module provides a reliable and expressive framework for developing systems that are both technically sound and closely aligned with domain requirements.
### Usage
Developers should implement actor behaviors in accordance with the outlined calculus, ensuring that each actor's implementation respects the preconditions, postconditions, and domain-specific assertions relevant to their system's domain logic. This approach facilitates the development of systems that are not only functionally correct but also domain-compliant, thereby enhancing the value and applicability of the RDDDY framework in real-world scenarios.
"""
import asyncio
from loguru import logger
from reactivex.scheduler.eventloop import AsyncIOScheduler
from typing import TYPE_CHECKING, Callable
import reactivex as rx
from reactivex import operators as ops
from rdddy.messages import *
if TYPE_CHECKING:
from rdddy.actor_system import ActorSystem
class Actor:
"""
Represents an actor within the RDDDY framework.
Actors are fundamental units of computation in the RDDDY framework, encapsulating both state and behavior.
They communicate asynchronously through message passing, promoting loose coupling and system resilience.
Args:
actor_system (ActorSystem): The ActorSystem to which the actor belongs.
actor_id (int, optional): The unique identifier of the actor. Defaults to None.
Attributes:
actor_system (ActorSystem): The ActorSystem to which the actor belongs.
actor_id (int): The unique identifier of the actor.
mailbox (Subject): A subject for message queuing.
handlers (dict): A mapping of message types to corresponding handler methods.
Methods:
start(scheduler): Starts the actor's mailbox processing loop.
on_next(message): Callback function for processing incoming messages.
on_error(error): Callback function for handling errors in the actor's mailbox.
on_completed(): Callback function when the actor's mailbox stream completes.
receive(message): Processes an incoming message.
send(recipient_id, message): Sends a message to another actor.
publish(message): Publishes a message to the actor system.
map_handlers(): Maps message types to corresponding handler methods.
"""
def __init__(self, actor_system: "ActorSystem", actor_id=None):
self.actor_system = actor_system
self.actor_id = actor_id or id(self)
self.mailbox = rx.subject.Subject()
self.handlers = self.map_handlers()
async def start(self, scheduler: AsyncIOScheduler):
"""
Initiates the processing loop for the actor's mailbox, ensuring asynchronous message handling.
Preconditions (Pre):
- The actor's mailbox must be initialized.
- A valid scheduler must be provided.
Transition (T):
- Initiates the processing loop for the actor's mailbox, enabling asynchronous message handling.
Postconditions (Post):
- The actor's mailbox processing loop has started successfully.
Args:
scheduler: An asynchronous scheduler used to control the execution of tasks.
"""
self.mailbox.pipe(ops.observe_on(scheduler)).subscribe(
on_next=self.on_next, # Synchronous wrapper for async handler
on_error=self.on_error,
on_completed=self.on_completed,
)
logger.info(f"Actor {self.actor_id} started")
def on_next(self, message: Message):
"""
Handles the next incoming message in the actor's mailbox.
Preconditions (Pre):
- The incoming message must be a valid instance of the Message class.
Transition (T):
- Processes the incoming message asynchronously.
Postconditions (Post):
- The incoming message has been processed by the actor.
Args:
message (Message): The incoming message to be processed.
"""
# Schedule the async handler as a new task
logger.debug(f"Actor {self.actor_id} received message: {message}")
asyncio.create_task(self.receive(message))
def on_error(self, error):
"""
Handles errors that occur in the actor's mailbox processing.
Preconditions (Pre):
- None
Transition (T):
- Handles the error generated during mailbox processing.
Postconditions (Post):
- The error has been handled, and appropriate action has been taken.
Args:
error: The error object representing the error that occurred.
"""
logger.error(f"Error in actor {self.actor_id} mailbox: {error}")
def on_completed(self):
"""
Handles the completion of the actor's mailbox stream.
Preconditions (Pre):
- None
Transition (T):
- Handles the completion event of the actor's mailbox stream.
Postconditions (Post):
- The actor's mailbox stream has completed, and appropriate action has been taken.
"""
logger.debug(f"Actor {self.actor_id} mailbox stream completed")
async def receive(self, message: Message):
"""
Processes an incoming message received by the actor.
Preconditions (Pre):
- The incoming message must be a valid instance of the Message class.
Transition (T):
- Processes the incoming message asynchronously, invoking the appropriate handler method.
Postconditions (Post):
- The incoming message has been successfully processed by the actor.
Args:
message (Message): The incoming message to be processed.
"""
try:
handler = self.handlers.get(type(message))
if handler:
await handler(message)
except Exception as e:
error_message = f"Error in actor {self.actor_id} processing message: {e}"
# Broadcast an error event through the actor system
await self.publish(Event(content=error_message))
logger.error(error_message)
async def publish(self, message: Message):
"""
Publishes a message to the actor system for distribution.
Preconditions (Pre):
- The message must be a valid instance of the Message class.
Transition (T):
- Publishes the message to the actor system for distribution.
Postconditions (Post):
- The message has been successfully published to the actor system.
Args:
message (Message): The message to be published.
"""
if message.actor_id == -1:
message.actor_id = self.actor_id
await self.actor_system.publish(message)
def map_handlers(self) -> dict[Type[Message], Callable]:
"""
Maps message types to corresponding handler methods.
Preconditions (Pre):
- None
Transition (T):
- Iterates through the methods of the actor instance and identifies callable methods with annotations.
- Maps message types to corresponding handler methods based on method annotations.
Postconditions (Post):
- A dictionary containing message types as keys and corresponding handler methods as values has been generated.
"""
handlers = {}
for name, method in inspect.getmembers(self):
if callable(method) and hasattr(method, "__annotations__"):
annotations = method.__annotations__
for arg in annotations.values():
try:
if issubclass(arg, Message):
handlers[arg] = method
except TypeError:
pass
del handlers[Message]
return handlers
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