`bubus`: 📢 Production-ready event bus library for Python

Bubus is a fully-featured, Pydantic-powered event bus library for async Python.

It's designed for quickly building event-driven applications with Python in a way that "just works" with async support, proper support for nested events, and real concurrency control.

It provides a pydantic-based API for implementing publish-subscribe patterns with type safety, async/sync handler support, and advanced features like event forwarding between buses. It's inspired by the simplicity of JS's async system and DOM events APIs, and it aims to bring a fully type-checked EventTarget-style API to Python.

🔢 Quickstart

Install bubus and get started with a simple event-driven application:

pip install bubus

import asyncio
from bubus import EventBus, BaseEvent
from your_auth_events import AuthRequestEvent, AuthResponseEvent

bus = EventBus()

class UserLoginEvent(BaseEvent):
    username: str
    timestamp: float

async def handle_login(login_event: UserLoginEvent):
    auth_request = await bus.dispatch(AuthRequestEvent(...))  # dispatch a nested event
    auth_response = await bus.expect(AuthResponseEvent)       # wait for an event to be seen

    print(f"User {event.username} logged in at {event.timestamp} with API key: {await auth_response.event_result()}")
    return {"status": "success", "user": event.username}


bus.on(UserLoginEvent, handle_login)

event = bus.dispatch(UserLoginEvent(username="alice", timestamp=1234567890))
result = await event
print(f"Login handled: {result.event_results}")

✨ Features

🔠 Type-Safe Events with Pydantic

Define events as Pydantic models with full type checking and validation:

from typing import Any
from bubus import BaseEvent

class OrderCreatedEvent(BaseEvent):
    order_id: str
    customer_id: str
    total_amount: float
    items: list[dict[str, Any]]

# Events are automatically validated
event = OrderCreatedEvent(
    order_id="ORD-123",
    customer_id="CUST-456", 
    total_amount=99.99,
    items=[{"sku": "ITEM-1", "quantity": 2}]
)

🔀 Async and Sync Handler Support

Register both synchronous and asynchronous handlers for maximum flexibility:

# Async handler
async def async_handler(event: BaseEvent):
    await asyncio.sleep(0.1)  # Simulate async work
    return "async result"

# Sync handler
def sync_handler(event: BaseEvent):
    return "sync result"

bus.on('MyEvent', async_handler)
bus.on('MyEvent', sync_handler)

Handlers can also be defined under classes for easier organization:

class SomeService:
    some_value = 'this works'

    async def handlers_can_be_methods(self, event: BaseEvent):
        return self.some_value
    
    @classmethod
    async def handler_can_be_classmethods(cls, event: BaseEvent):
        return cls.some_value

    @staticmethod
    async def handlers_can_be_staticmethods(event: BaseEvent):
        return 'this works too'

# All usage patterns behave the same:
bus.on('MyEvent', SomeClass().handlers_can_be_methods)
bus.on('MyEvent', SomeClass.handler_can_be_classmethods)
bus.on('MyEvent', SomeClass.handlers_can_be_staticmethods)

🔎 Event Pattern Matching

Subscribe to events using multiple patterns:

# By event type string
bus.on('UserActionEvent', handler)

# By event model class
bus.on(UserActionEvent, handler)

# Wildcard - handle all events
bus.on('*', universal_handler)

⏩ Forward `Events` Between `EventBus`s

You can define separate EventBus instances in different "microservices" to separate different areas of concern. EventBuss can be set up to forward events between each other (with automatic loop prevention):

# Create a hierarchy of buses
main_bus = EventBus(name='MainBus')
auth_bus = EventBus(name='AuthBus')
data_bus = EventBus(name='DataBus')

# Forward events between buses (infinite loops are automatically prevented)
main_bus.on('AuthEvent', auth_bus.dispatch)
auth_bus.on('*', data_bus.dispatch)

# Events flow through the hierarchy with tracking
event = main_bus.dispatch(MyEvent())
await event
print(event.event_path)  # ['MainBus', 'AuthBus', 'DataBus']  # list of buses that have already procssed the event

🔱 Event Results Aggregation

Collect and aggregate results from multiple handlers:

async def load_user_config(event):
    return {"debug": True, "port": 8080}

async def load_system_config(event):
    return {"debug": False, "timeout": 30}

bus.on('GetConfig', load_user_config)
bus.on('GetConfig', load_system_config)

# Get a merger of all dict results
event = await bus.dispatch(GetConfig())
config = await event.event_results_flat_dict()
# {'debug': False, 'port': 8080, 'timeout': 30}

# Or get individual results
results = await event.event_results_by_handler_id()

🚦 FIFO Event Processing

Events are processed in strict FIFO order, maintaining consistency:

# Events are processed in the order they were dispatched
for i in range(10):
    bus.dispatch(ProcessTaskEvent(task_id=i))

# Even with async handlers, order is preserved
await bus.wait_until_idle()

If a handler dispatches and awaits any child events during execution, those events will jump the FIFO queue and be processed immediately:

def child_handler(event: SomeOtherEvent):
    return 'xzy123'

def main_handler(event: MainEvent):
    # enqueue event for processing after main_handler exits
    child_event = bus.dispatch(SomeOtherEvent())
    
    # can also await child events to process immediately instead of adding to FIFO queue
    completed_child_event = await child_event
    return f'result from awaiting child event: {await completed_child_event.event_result()}'  # 'xyz123'

bus.on(SomeOtherEvent, child_handler)
bus.on(MainEvent, main_handler)

await bus.dispatch(MainEvent()).event_result()
# result from awaiting child event: xyz123

🧹 Memory Management

EventBus includes automatic memory management to prevent unbounded growth in long-running applications:

# Create a bus with memory limits (default: 50 events)
bus = EventBus(max_history_size=100)  # Keep max 100 events in history

# Or disable memory limits for unlimited history
bus = EventBus(max_history_size=None)

Automatic Cleanup:

When max_history_size is set, EventBus automatically removes old events when the limit is exceeded
Completed events are removed first (oldest first), then started events, then pending events
This ensures active events are preserved while cleaning up old completed events

Manual Memory Management:

# For request-scoped buses (e.g. web servers), clear all memory after each request
try:
    event_service = EventService()  # Creates internal EventBus
    await event_service.process_request()
finally:
    # Clear all event history and remove from global tracking
    await event_service.eventbus.stop(clear=True)

Memory Monitoring:

EventBus automatically monitors total memory usage across all instances
Warnings are logged when total memory exceeds 50MB
Use bus.stop(clear=True) to completely free memory for unused buses
To avoid memory leaks from big events, the default limits are intentionally kept low. events are normally processed as they come in, and there is rarely a need to keep every event in memory longer after its complete. long-term storage should be accomplished using other mechanisms, like the WAL

⛓️ Parallel Handler Execution

Enable parallel processing of handlers for better performance.
The tradeoff is slightly less deterministic ordering as handler execution order will not be guaranteed when run in parallel.

# Create bus with parallel handler execution
bus = EventBus(parallel_handlers=True)

# Multiple handlers run concurrently for each event
bus.on('DataEvent', slow_handler_1)  # Takes 1 second
bus.on('DataEvent', slow_handler_2)  # Takes 1 second

start = time.time()
await bus.dispatch(DataEvent())
# Total time: ~1 second (not 2)

🪆 Dispatch Nested Child Events From Handlers

Automatically track event relationships and causality tree:

async def parent_handler(event: BaseEvent):
    # handlers can emit more events to be processed asynchronously after this handler completes
    child_event_async = event.event_bus.dispatch(ChildEvent())   # equivalent to bus.dispatch(...)
    assert child_event_async.status != 'completed'
    # ChildEvent handlers will run after parent_handler exits

    # or you can dispatch an event and block until it finishes processing by awaiting the event
    # this recursively waits for all handlers, including if event is forwarded to other buses
    # (note: awaiting an event from inside a handler jumps the FIFO queue and will process it immediately, before any other pending events)
    child_event_sync = await bus.dispatch(ChildEvent())
    # ChildEvent handlers run immediately
    assert child_event_sync.event_status == 'completed'

    # in all cases, parent-child relationships are automagically tracked
    assert child_event_async.event_parent_id == event.event_id
    assert child_event_sync.event_parent_id == event.event_id

parent_event = bus.dispatch(ParentEvent())
print(parent_event.event_children)           # show all the child events emitted during handling of an event
print(bus.log_tree())                        # print a nice pretty tree view of the entire event hierarchy

⏳ Expect an Event to be Dispatched

Wait for specific events to be seen on a bus with optional filtering:

# Block until a specific event is seen (with optional timeout)
request_event = await bus.dispatch(RequestEvent(...))
response_event = await bus.expect('ResponseEvent', timeout=30)

# Block until a specific event is seen (with optional predicate filtering)
response_event = await bus.expect(
    ResponseEvent,  # can pass event type as a string or class
    predicate=lambda e: e.request_id == my_request_id,
    timeout=30
)

Important

expect() resolves when the event is first dispatched to the EventBus, not when it completes. await response_event to get the completed event.

📝 Write-Ahead Logging

Persist events automatically for durability and debugging:

# Enable WAL persistence
bus = EventBus(name='MyBus', wal_path='./events.jsonl')

# All completed events are automatically persisted
bus.dispatch(ImportantEvent(data="critical"))

# Events are saved as JSONL for easy processing
# {"event_type": "ImportantEvent", "data": "critical", ...}

📚 API Documentation

`EventBus`

The main event bus class that manages event processing and handler execution.

EventBus(
    name: str | None = None,
    wal_path: Path | str | None = None,
    parallel_handlers: bool = False,
    max_history_size: int | None = 50
)

Parameters:

name: Optional unique name for the bus (auto-generated if not provided)
wal_path: Path for write-ahead logging of events to a jsonl file (optional)
parallel_handlers: If True, handlers run concurrently for each event, otherwise serially if False (the default)
max_history_size: Maximum number of events to keep in history (default: 50, None = unlimited)

`EventBus` Properties

name: The bus identifier
id: Unique UUID7 for this bus instance
event_history: Dict of all events the bus has seen by event_id (limited by max_history_size)
events_pending: List of events waiting to be processed
events_started: List of events currently being processed
events_completed: List of completed events
all_instances: Class-level WeakSet tracking all active EventBus instances (for memory monitoring)

`EventBus` Methods

`on(event_type: str | Type[BaseEvent], handler: Callable)`

Subscribe a handler to events matching a specific event type or '*' for all events.

bus.on('UserEvent', handler_func)  # By event type string
bus.on(UserEvent, handler_func)    # By event class
bus.on('*', handler_func)          # Wildcard - all events

`dispatch(event: BaseEvent) -> BaseEvent`

Enqueue an event for processing and return the pending Event immediately (synchronous).

event = bus.dispatch(MyEvent(data="test"))
result = await event  # await the pending Event to get the completed Event

Note: When max_history_size is set, EventBus enforces a hard limit of 100 pending events (queue + processing) to prevent runaway memory usage. Dispatch will raise RuntimeError if this limit is exceeded.

`expect(event_type: str | Type[BaseEvent], timeout: float | None=None, predicate: Callable[[BaseEvent], bool]=None) -> BaseEvent`

Wait for a specific event to occur.

# Wait for any UserEvent
event = await bus.expect('UserEvent', timeout=30)

# Wait with custom filter
event = await bus.expect(
    'UserEvent',
    predicate=lambda e: e.user_id == 'specific_user'
)

`wait_until_idle(timeout: float | None=None)`

Wait until all events are processed and the bus is idle.

await bus.wait_until_idle()             # wait indefinitely until EventBus has finished processing all events

await bus.wait_until_idle(timeout=5.0)  # wait up to 5 seconds

`stop(timeout: float | None=None, clear: bool=False)`

Stop the event bus, optionally waiting for pending events and clearing memory.

await bus.stop(timeout=1.0)  # Graceful stop, wait up to 1sec for pending and active events to finish processing
await bus.stop()             # Immediate shutdown, aborts all pending and actively processing events
await bus.stop(clear=True)   # Stop and clear all event history and handlers to free memory

`BaseEvent`

Base class for all events. Subclass BaseEvent to define your own events.

Make sure none of your own event data fields start with event_ or model_ to avoid clashing with BaseEvent or pydantic builtin attrs.

`BaseEvent` Fields

class BaseEvent(BaseModel):
    # Framework-managed fields
    event_type: str              # Defaults to class name
    event_id: str                # Unique UUID7 identifier, auto-generated if not provided
    event_timeout: float = 60.0  # Maximum execution in seconds for each handler
    event_schema: str            # Module.Class@version (auto-set based on class & LIBRARY_VERSION env var)
    event_parent_id: str         # Parent event ID (auto-set)
    event_path: list[str]        # List of bus names traversed (auto-set)
    event_created_at: datetime   # When event was created, auto-generated
    event_results: dict[str, EventResult]   # Handler results
    
    # Data fields
    # ... subclass BaseEvent to add your own event data fields here ...
    # some_key: str
    # some_other_key: dict[str, int]
    # ...

event.event_results contains a dict of pending EventResult objects that will be completed once handlers finish executing.

`BaseEvent` Properties

event_status: Literal['pending', 'started', 'complete'] Event status
event_started_at: datetime When first handler started processing
event_completed_at: datetime When all handlers completed processing
event_children: list[BaseEvent] Get any child events emitted during handling of this event
event_bus: EventBus Shortcut to get the bus currently processing this event

`BaseEvent` Methods

`await event`

Await the Event object directly to get the completed Event object once all handlers have finished executing.

event = bus.dispatch(MyEvent())
completed_event = await event

raw_result_values = [(await event_result) for event_result in completed_event.event_results.values()]
# equivalent to: completed_event.event_results_list()  (see below)

`event_result(timeout: float | None=None) -> Any`

Utility method helper to execute all the handlers and return the first handler's raw result value.

result = await event.event_result()

`event_results_by_handler_id(timeout: float | None=None) -> dict`

Utility method helper to get all raw result values organized by {handler_id: result_value}.

results = await event.event_results_by_handler_id()
# {'handler_id_1': result1, 'handler_id_2': result2}

`event_results_list(timeout: float | None=None) -> list[Any]`

Utility method helper to get all raw result values in a list.

results = await event.event_results_list()
# [result1, result2]

`event_results_flat_dict(timeout: float | None=None) -> dict`

Utility method helper to merge all raw result values that are dicts into a single flat dict.

results = await event.event_results_flat_dict()
# {'key1': 'value1', 'key2': 'value2'}

`event_results_flat_list(timeout: float | None=None) -> list`

Utility method helper to merge all raw result values that are lists into a single flat list.

results = await event.event_results_flat_list()
# ['item1', 'item2', 'item3']

`event_bus` (property)

Shortcut to get the EventBus that is currently processing this event. Can be used to avoid having to pass an EventBus instance to your handlers.

bus = EventBus()

async def some_handler(event: MyEvent):
    # You can always dispatch directly to any bus you have a reference to
    child_event = bus.dispatch(ChildEvent())
    
    # OR use the event.event_bus shortcut to get the current bus:
    child_event = await event.event_bus.dispatch(ChildEvent())

`EventResult`

The placeholder object that represents the pending result from a single handler executing an event.
Event.event_results contains a dict[PythonIdStr, EventResult] in the shape of {handler_id: EventResult()}.

You shouldn't need to ever directly use this class, it's an internal wrapper to track pending and completed results from each handler within BaseEvent.event_results.

`EventResult` Fields

class EventResult(BaseModel):
    id: str                    # Unique identifier
    handler_id: str           # Handler function ID
    handler_name: str         # Handler function name
    eventbus_id: str          # Bus that executed this handler
    eventbus_name: str        # Bus name
    
    status: str               # 'pending', 'started', 'completed', 'error'
    result: Any               # Handler return value
    error: str | None         # Error message if failed
    
    started_at: datetime      # When handler started
    completed_at: datetime    # When handler completed
    timeout: float            # Handler timeout in seconds
    child_events: list[BaseEvent] # list of child events emitted during handler execution

`EventResult` Methods

`await result`

Await the EventResult object directly to get the raw result value.

handler_result = event.event_results['handler_id']
value = await handler_result  # Returns result or raises an exception if handler hits an error

🧵 Advanced Concurrency Control

`@retry` Decorator

The @retry decorator provides automatic retry functionality with built-in concurrency control for any function, including event handlers. This is particularly useful when handlers interact with external services that may temporarily fail.

from bubus import EventBus, BaseEvent
from bubus.helpers import retry

bus = EventBus()

class FetchDataEvent(BaseEvent):
    url: str

@retry(
    wait=2,                     # Wait 2 seconds between retries
    retries=3,                  # Retry up to 3 times after initial failure
    timeout=5,                  # Each attempt times out after 5 seconds
    semaphore_limit=5,          # Max 5 concurrent executions
    backoff_factor=1.5,         # Exponential backoff: 2s, 3s, 4.5s
    retry_on=(TimeoutError, ConnectionError)  # Only retry on specific exceptions
)
async def fetch_with_retry(event: FetchDataEvent):
    # This handler will automatically retry on network failures
    async with aiohttp.ClientSession() as session:
        async with session.get(event.url) as response:
            return await response.json()

bus.on(FetchDataEvent, fetch_with_retry)

Retry Parameters

timeout: Maximum amount of time function is allowed to take per attempt, in seconds (default: 5)
retries: Number of additional retry attempts if function raises an exception (default: 3)
retry_on: Tuple of exception types to retry on (default: None = retry on any Exception)
wait: Base seconds to wait between retries (default: 3)
backoff_factor: Multiplier for wait time after each retry (default: 1.0)
semaphore_limit: Maximum number of concurrent calls that can run at the same time
semaphore_scope: Scope for the semaphore: class, self, global, or multiprocess
semaphore_timeout: Maximum time to wait for a semaphore slot before proceeding or failing
semaphore_lax: Continue anyway if semaphore fails to be acquired in within the given time
semaphore_name: Unique semaphore name to allow sharing a semaphore between functions

Semaphore Options

Control concurrency with built-in semaphore support:

# Global semaphore - all calls share one limit
@retry(semaphore_limit=3, semaphore_scope='global')
async def global_limited_handler(event): ...

# Per-class semaphore - all instances of a class share one limit
class MyService:
    @retry(semaphore_limit=2, semaphore_scope='class')
    async def class_limited_handler(self, event): ...

# Per-instance semaphore - each instance gets its own limit
class MyService:
    @retry(semaphore_limit=1, semaphore_scope='self')
    async def instance_limited_handler(self, event): ...

# Cross-process semaphore - all processes share one limit
@retry(semaphore_limit=5, semaphore_scope='multiprocess')
async def process_limited_handler(event): ...

Advanced Example

import logging

# Configure logging to see retry attempts
logging.basicConfig(level=logging.INFO)

class DatabaseEvent(BaseEvent):
    query: str

class DatabaseService:
    @retry(
        wait=1,
        retries=5,
        timeout=10,
        semaphore_limit=10,          # Max 10 concurrent DB operations
        semaphore_scope='class',     # Shared across all instances
        semaphore_timeout=30,        # Wait up to 30s for semaphore
        semaphore_lax=False,         # Fail if can't acquire semaphore
        backoff_factor=2.0,          # Exponential backoff: 1s, 2s, 4s, 8s, 16s
        retry_on=(ConnectionError, TimeoutError)
    )
    async def execute_query(self, event: DatabaseEvent):
        # Automatically retries on connection failures
        # Limited to 10 concurrent operations across all instances
        result = await self.db.execute(event.query)
        return result

# Register the handler
db_service = DatabaseService()
bus.on(DatabaseEvent, db_service.execute_query)

👾 Development

Set up the development environment using uv:

git clone https://github.com/browser-use/bubus && cd bubus

# Create virtual environment with Python 3.12
uv venv --python 3.12

# Activate virtual environment (varies by OS)
source .venv/bin/activate  # On Unix/macOS
# or
.venv\Scripts\activate  # On Windows

# Install dependencies
uv sync --dev --all-extras

# Run linter & type checker
uv run ruff check --fix
uv run ruff format
uv run pyright

# Run all tests
uv run pytest -vxs --full-trace tests/

# Run specific test file
uv run pytest tests/test_eventbus.py

🔗 Inspiration

🏛️ License

This project is licensed under the MIT License. For more information, see the main browser-use repository: https://github.com/browser-use/browser-use

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bubus		bubus
tests		tests
.gitignore		.gitignore
.pre-commit-config.yaml		.pre-commit-config.yaml
.python-version		.python-version
LICENSE		LICENSE
README.md		README.md
pyproject.toml		pyproject.toml

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bubus: 📢 Production-ready event bus library for Python

🔢 Quickstart

✨ Features

🔠 Type-Safe Events with Pydantic

🔀 Async and Sync Handler Support

🔎 Event Pattern Matching

⏩ Forward Events Between EventBuss

🔱 Event Results Aggregation

🚦 FIFO Event Processing

🧹 Memory Management

⛓️ Parallel Handler Execution

🪆 Dispatch Nested Child Events From Handlers

⏳ Expect an Event to be Dispatched

📝 Write-Ahead Logging

📚 API Documentation

EventBus

EventBus Properties

EventBus Methods

on(event_type: str | Type[BaseEvent], handler: Callable)

dispatch(event: BaseEvent) -> BaseEvent

expect(event_type: str | Type[BaseEvent], timeout: float | None=None, predicate: Callable[[BaseEvent], bool]=None) -> BaseEvent

wait_until_idle(timeout: float | None=None)

stop(timeout: float | None=None, clear: bool=False)

BaseEvent

BaseEvent Fields

BaseEvent Properties

BaseEvent Methods

await event

event_result(timeout: float | None=None) -> Any

event_results_by_handler_id(timeout: float | None=None) -> dict

event_results_list(timeout: float | None=None) -> list[Any]

event_results_flat_dict(timeout: float | None=None) -> dict

event_results_flat_list(timeout: float | None=None) -> list

event_bus (property)

EventResult

EventResult Fields

EventResult Methods

await result

🧵 Advanced Concurrency Control

@retry Decorator

Retry Parameters

Semaphore Options

Advanced Example

👾 Development

🔗 Inspiration

🏛️ License

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`bubus`: 📢 Production-ready event bus library for Python

⏩ Forward `Events` Between `EventBus`s

`EventBus`

`EventBus` Properties

`EventBus` Methods

`on(event_type: str | Type[BaseEvent], handler: Callable)`

`dispatch(event: BaseEvent) -> BaseEvent`

`expect(event_type: str | Type[BaseEvent], timeout: float | None=None, predicate: Callable[[BaseEvent], bool]=None) -> BaseEvent`

`wait_until_idle(timeout: float | None=None)`

`stop(timeout: float | None=None, clear: bool=False)`

`BaseEvent`

`BaseEvent` Fields

`BaseEvent` Properties

`BaseEvent` Methods

`await event`

`event_result(timeout: float | None=None) -> Any`

`event_results_by_handler_id(timeout: float | None=None) -> dict`

`event_results_list(timeout: float | None=None) -> list[Any]`

`event_results_flat_dict(timeout: float | None=None) -> dict`

`event_results_flat_list(timeout: float | None=None) -> list`

`event_bus` (property)

`EventResult`

`EventResult` Fields

`EventResult` Methods

`await result`

`@retry` Decorator

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