Metadata-Version: 2.4
Name: daebus
Version: 0.0.9
Summary: A simple way to build python services running on a raspberry pi.
Project-URL: Homepage, https://github.com/twestos/daebus
Project-URL: Issues, https://github.com/twestos/daebus/issues
Author-email: Tom West <tom@bambo.co>
License-Expression: MIT
License-File: LICENSE
Classifier: Intended Audience :: Developers
Classifier: Operating System :: OS Independent
Classifier: Programming Language :: Python :: 3
Requires-Python: >=3.9
Requires-Dist: apscheduler>=3.11.0
Requires-Dist: redis>=6.0.0
Provides-Extra: dev
Requires-Dist: bump2version>=1.0.1; extra == 'dev'
Requires-Dist: codecov>=2.1.13; extra == 'dev'
Requires-Dist: flake8>=7.2.0; extra == 'dev'
Requires-Dist: pytest-cov>=6.1.1; extra == 'dev'
Requires-Dist: pytest-mock>=3.14.0; extra == 'dev'
Requires-Dist: pytest>=8.3.5; extra == 'dev'
Description-Content-Type: text/markdown

# Daebus

A simple framework for building systemd daemons and background services with a Flask-like interface, designed for inter-service communication in Linux environments. Daebus makes it easy to build, connect, and manage services for embedded devices like Raspberry Pi kiosks.

## Overview

Daebus was created to solve the challenge of managing multiple systemd services on Linux devices such as Raspberry Pi kiosks. It provides a Flask-inspired API that makes it simple to:

- Create systemd daemons that communicate with each other
- Expose HTTP endpoints for frontend applications (e.g., kiosk browsers)
- Enable quick bootstrapping of new services with minimal boilerplate

Services communicate via Redis pub/sub channels, providing a lightweight and reliable messaging system ideal for local service orchestration.

> **Note**: Daebus requires a Redis instance running on the system.

## Features

- **Flask-inspired API**: Simple, decorator-based API for defining service functionality
- **Redis Pub/Sub**: Direct channel-based communication between services
- **Action Routing**: Route messages to specific handlers based on action field
- **Background tasks**: Easy scheduling of periodic background tasks
- **Client library**: `DaebusCaller` allows for easy communication with Daebus services
- **HTTP endpoints**: Expose lightweight HTTP APIs from your daemon without additional dependencies
- **Specialized APIs**: Distinct and purpose-built APIs for HTTP and pub/sub contexts

## Installation
```bash
pip install daebus
```

## Quick Start

### Creating a Service

```python
from Daebus import Daebus, request, response, broadcast, cache, logger

app = Daebus(__name__)

# Define an action handler (like a Flask route)
@app.action("get_status")
def handle_status_request():
    try:
        payload = request.payload
        logger.info(f"Received status request: {payload}")

        # Process the request
        result = {"status": "healthy", "uptime": 3600}

        # Send response back to the requester
        return response.success(result)
    except Exception as e:
        return response.error(e)

# Define another action handler
@app.action("restart")
def handle_restart():
    try:
        logger.info("Handling restart request")
        # Restart logic here
        return response.success({"restarted": True})
    except Exception as e:
        return response.error(e)

# Define a channel listener for broadcasts
@app.listen("notifications")
def handle_notification(payload):
    logger.info(f"Received notification: {payload}")
    # Process the notification

# Define a background task that runs every 30 seconds
@app.background("health_check", 30)
def health_check():
    logger.info("Running health check")
    # Perform health check

    # Broadcast status to any interested services
    broadcast.send("system_status", {"status": "healthy"})

# Run the service
if __name__ == "__main__":
    app.run(service="my_service", debug=True)
```

### Communicating with Services using DaebusCaller

```python
from Daebus import DaebusCaller

# Create a caller for the target service
caller = DaebusCaller("my_service")

try:
    # Send a request to a specific action and wait for a response
    response = caller.send_request("get_status", {
        "detail_level": "full"
    })
    print(f"Service status: {response}")

    # Send a restart request
    restart_response = caller.send_request("restart", {
        "mode": "graceful"
    })
    print(f"Restart result: {restart_response}")

    # Send a message to a broadcast channel
    caller.send_message("notifications", {
        "type": "alert",
        "message": "System temperature high"
    })

    # Send a message directly to the service with a specific action
    caller.send_to_service({
        "timestamp": 1625176230,
        "info": "Direct message with action"
    }, action="log_info")
finally:
    # Clean up resources when done
    caller.close()
```

### Adding HTTP Endpoints to Your Service

You can easily add HTTP endpoints to your daemon using the built-in HTTP server:

```python
from Daebus import Daebus, DaebusHttp

app = Daebus(__name__)

# Create and attach an HTTP endpoint
http = DaebusHttp(port=8080)
app.attach(http)

# Define HTTP routes (similar to Flask)
@app.route("/status")
def get_status(req):
    # Use the request object to access request data
    # req.payload contains JSON, form data, or query params

    # For HTTP responses, use response.send with data and status code
    return response.send({
        "service": "my_service",
        "status": "running",
        "timestamp": time.time()
    }, 200)  # 200 OK status code

# Routes with parameters
@app.route("/devices/<device_id>")
def get_device(req, device_id):
    # The device_id parameter is extracted from the URL
    if device_id == "123":
        return response.send({
            "device_id": device_id,
            "status": "online"
        }, 200)
    else:
        # Error responses with appropriate status codes
        return response.send({
            "error": "Device not found"
        }, 404)  # 404 Not Found

# POST requests
@app.route("/control", methods=["POST"])
def control_action(req):
    # Access JSON data from the request payload
    data = req.payload

    # Process the request
    return response.send({
        "success": True,
        "message": "Command received"
    }, 201)  # 201 Created

# Run the service with HTTP enabled
app.run(service="my_service")
```

### Configuring CORS for HTTP Endpoints

If your HTTP API needs to be accessed from web browsers, you can configure Cross-Origin Resource Sharing (CORS):

```python
from Daebus import Daebus, DaebusHttp

app = Daebus(__name__)

# Configure CORS when creating the HTTP endpoint
cors_config = {
    'allowed_origins': ['http://localhost:3000', 'https://example.com'],  # Specific origins
    'allowed_methods': ['GET', 'POST', 'OPTIONS'],                        # Allowed HTTP methods
    'allowed_headers': ['Content-Type', 'Authorization'],                 # Allowed headers
    'expose_headers': ['X-Custom-Header'],                                # Headers exposed to client
    'allow_credentials': True,                                            # Allow cookies
    'max_age': 3600                                                       # Cache preflight for 1 hour
}

# Create HTTP endpoint with CORS support
http = DaebusHttp(port=8080, cors_config=cors_config)
app.attach(http)

# Alternatively, configure CORS after initialization
# http = DaebusHttp(port=8080)
# http.configure_cors({
#     'allowed_origins': '*',  # Allow all origins
#     'allowed_methods': ['GET', 'POST'],
#     'allowed_headers': '*',  # Allow all headers
# })

@app.route("/api/data")
def get_data(req):
    # This endpoint will now include CORS headers in the response
    return response.send({"data": "example"}, 200)
```

You can use these CORS configuration options:

- `allowed_origins`: List of allowed origins or `'*'` for any origin
- `allowed_methods`: List of allowed HTTP methods or `'*'` for any method
- `allowed_headers`: List of allowed headers or `'*'` for any header
- `expose_headers`: List of headers to expose to the client
- `allow_credentials`: Boolean for allowing credentials (cookies)
- `max_age`: Cache time (seconds) for preflight requests

### Protocol-Specific Response Methods

Daebus provides distinct response methods optimized for each protocol:

```python
from Daebus import Daebus, DaebusHttp, request, response

app = Daebus(__name__)
http = DaebusHttp(port=8080)
app.attach(http)

# Shared function for business logic
def get_status_data():
    return {
        "service": "my_service",
        "status": "healthy",
        "uptime": 3600
    }

# HTTP route with HTTP-specific response using response.send
@app.route("/status")
def http_status_handler(req):
    try:
        data = get_status_data()

        # Use response.send() for HTTP responses, with status code
        return response.send(data, 200)
    except Exception as e:
        # HTTP errors with appropriate status codes
        return response.send({"error": str(e)}, 500)

# Redis action handler with pub/sub specific response methods
@app.action("get_status")
def redis_status_handler():
    try:
        data = get_status_data()

        # Use response.success() for Redis responses
        return response.success(data)
    except Exception as e:
        # Redis-specific error handling
        return response.error(e)
```

### Advanced: Direct Access to Protocol-Specific Classes

For advanced usage, you can access the protocol-specific classes directly:

```python
from Daebus import (
    Daebus, DaebusHttp,
    HttpRequest, HttpResponse,  # HTTP-specific classes
    PubSubRequest, PubSubResponse  # Pub/Sub-specific classes
)

app = Daebus(__name__)
http = DaebusHttp(port=8080)
app.attach(http)

# Use HTTP-specific classes directly for advanced customization
@app.route("/advanced")
def advanced_handler(req):
    # Check if we have the right request type
    if not isinstance(req, HttpRequest):
        raise TypeError("Expected an HttpRequest object")

    # Create a custom HTTP response
    custom_response = HttpResponse(None)
    return custom_response.send({
        "message": "Custom HTTP response",
        "path": req.path
    }, 200)
```

Benefits of protocol-specific methods:

- `response.send(data, status_code)` - HTTP focused, with explicit status codes
- `response.success(data)` - Pub/sub focused, adds necessary pub/sub metadata
- `response.error(exception)` - Pub/sub focused, formats exceptions for pub/sub
- Clear distinction between HTTP and pub/sub handling
- Direct access to protocol-specific classes for advanced customization

## How It Works

### Action Routing

Daebus uses a simple action routing system:

1. Each service automatically listens on its main channel (named after the service)
2. Messages sent to this channel can include an `action` field to route to specific handlers
3. Handlers are registered using `@app.action("action_name")`

For example:

- When a message with `action: "get_status"` is received, it's routed to the function decorated with `@app.action("get_status")`
- When a message with `action: "restart"` is received, it's routed to the function decorated with `@app.action("restart")`

### Channel Types

Daebus uses two types of Redis pub/sub channels:

1. **Service Channels**: Named after the service (e.g., `my_service`) and used for direct communication with action routing
2. **Custom Channels**: Any additional channels that services can publish to or subscribe to (e.g., `notifications`, `system_status`)

### Message Flow

1. **Request/Response**:

    - Client calls `send_request("action_name", payload)`
    - DaebusCaller sends message to service's main channel with the action field
    - Service routes to appropriate handler based on action
    - Handler processes request and sends response back to caller's response channel

2. **Broadcasts**:
    - Any service can broadcast to any channel with `broadcast.send(channel, payload)`
    - Interested services subscribe to those channels with `@app.listen(channel)`

### HTTP Endpoints

Daebus provides a lightweight HTTP server that:

1. Uses Python's built-in `http.server` module (no external dependencies)
2. Automatically converts Python dictionaries to JSON responses
3. Parses JSON and form data from requests
4. Supports URL parameters with the same syntax as Flask (`/path/<param>`)
5. Runs in a background thread, allowing your service to handle both Redis and HTTP requests

### Protocol-Specific Classes

Daebus provides specialized classes for each protocol:

1. **For Pub/Sub (Redis)**:

    - `PubSubRequest`: Handles pub/sub message payloads, reply channels, and request IDs
    - `PubSubResponse`: Provides `success()`, `error()`, and `progress()` methods for pub/sub responses

2. **For HTTP**:
    - `HttpRequest`: Adapts HTTP requests to a similar interface as pub/sub requests
    - `HttpResponse`: Provides `send()` method for HTTP responses with status codes

These specialized classes are normally accessed through the `request` and `response` proxies, which automatically select the appropriate implementation based on the current context.

## Key Concepts

### Action Handlers vs Channel Listeners

- **Action Handlers** (`@app.action`):

    - Receive messages from the service's main channel
    - Automatically routed based on the `action` field
    - Support request/response pattern with `response.success()` and `response.error()`

- **Channel Listeners** (`@app.listen`):
    - Receive broadcast messages from any channel
    - Used for one-way communications (no responses)
    - Useful for event notifications and broadcasts

### Lifecycle Hooks

Daebus provides lifecycle hooks to run code at specific points during the service's lifecycle:

- **On Start** (`@app.on_start()`):
    - Runs once after the service has fully started
    - All Redis connections, threads, and components are initialized
    - Ideal for initialization tasks, broadcasting startup events, or setting initial cache values

Example:

```python
@app.on_start()
def initialize_service():
    logger.info("Service is starting up...")

    # Set initial cache values
    cache.set("service.start_time", str(time.time()))
    cache.set("service.status", "running")

    # Broadcast a startup message
    broadcast.send("system.events", {
        "event": "startup",
        "service": app.name,
        "timestamp": time.time()
    })
```

### Context Objects

Within handlers, you have access to:

- `request`: Contains the incoming request data (adapts to HTTP or Redis context)
- `response`: Used to send responses back to the requester
    - For Redis: `response.success()`, `response.error()`
    - For HTTP: `response.send(data, status_code)`
- `broadcast`: Used to publish messages to channels
- `cache`: Direct access to Redis for storage
- `logger`: Configured logger for the service

## Advanced Usage

### Custom Service Extensions

You can extend `DaebusCaller` to create custom service-specific clients:

```python
class CameraServiceCaller(DaebusCaller):
    def __init__(self, redis_host='localhost', redis_port=6379):
        super().__init__("camera_service", redis_host, redis_port)

    def take_picture(self, resolution="high"):
        return self.send_request("take_picture", {
            "resolution": resolution
        })

    def start_recording(self, duration=60):
        return self.send_request("start_recording", {
            "duration": duration
        })
```

### Error Handling

Daebus provides built-in error handling for actions:

```python
@app.action("risky_operation")
def risky_operation():
    try:
        # Perform risky operation
        result = perform_operation()
        return response.success({"result": result})
    except Exception as e:
        logger.error(f"Operation failed: {e}")
        return response.error(e)
```

## Background

Daebus was born from the need to manage multiple systemd services on Raspberry Pi kiosks. The project required several background daemons that could:

1. Communicate with each other efficiently
2. Expose HTTP endpoints for frontend applications running in Chromium
3. Be easily bootstrapped with minimal boilerplate

Traditional approaches like Unix sockets proved limiting, so Redis pub/sub was chosen as the communication backbone due to its reliability and simplicity. The Flask-like interface was inspired by the ease of setting up web services with Flask, bringing that same developer experience to systemd daemon development.

For proper operation, Daebus requires a Redis instance running on the system to handle the pub/sub messaging between services.

# Version Management

To increment the version number, use bump2version:

```bash
# For patch version (0.0.1 -> 0.0.2)
bump2version patch

# For minor version (0.1.0 -> 0.2.0)
bump2version minor

# For major version (1.0.0 -> 2.0.0)
bump2version major

# Don't forget to push both the commit and the tags
git push && git push --tags
```

You can also use the GitHub Actions workflow "Bump Version" to automatically bump versions and push tags.
