Add async request handling with tracking IDs #3
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Implements boilerplate-minimal async task processing for long-running operations.
Clients can now choose between synchronous (blocking) and asynchronous (task-based) execution.
## Key Features
### Core Async Functionality
- Task-based async execution with unique task IDs
- Client-controlled sync/async mode via query param or header
- Standard HTTP patterns for task management
- Built-in task status tracking and result retrieval
- Support for both sync and async Python functions
### Task Management
- Automatic task management endpoints:
- GET /tasks/ - List all tasks
- GET /tasks/{id} - Get complete task info
- GET /tasks/{id}/status - Get task status
- GET /tasks/{id}/result - Get result (with optional wait)
- DELETE /tasks/{id} - Cancel/delete task
### Flexible Configuration
- Simple case: just specify `async_funcs=['function_name']`
- Advanced: per-function TaskConfig with custom executors
- Multiple execution backends:
- ThreadPoolTaskExecutor (I/O-bound tasks)
- ProcessPoolTaskExecutor (CPU-bound tasks)
- Custom executors via TaskExecutor interface
- Pluggable storage backends via TaskStore interface
- TTL-based result expiration
### Developer Experience
- Convention-based with escape hatches
- Zero external dependencies (uses stdlib)
- Fully backward compatible
- Comprehensive test coverage (16 tests)
- Ready for au package integration
## Implementation Details
### New Modules
- `qh/async_tasks.py` - Core task management, stores, and executors
- `qh/async_endpoints.py` - HTTP endpoints for task management
- `qh/async_example.py` - Comprehensive usage examples
- `qh/tests/test_async_tasks.py` - Full test suite
### Modified Modules
- `qh/app.py` - Added async_funcs and async_config parameters to mk_app
- `qh/config.py` - Added async_config field to RouteConfig
- `qh/endpoint.py` - Added async execution logic to endpoint creation
- `qh/__init__.py` - Exported async task classes and functions
### API Examples
Simple case:
```python
app = mk_app([expensive_func], async_funcs=['expensive_func'])
# POST /expensive_func?async=true -> Returns task_id
```
Advanced configuration:
```python
app = mk_app(
[cpu_func, io_func],
async_funcs=['cpu_func', 'io_func'],
async_config={
'cpu_func': TaskConfig(
executor=ProcessPoolTaskExecutor(max_workers=4),
ttl=3600
),
'io_func': TaskConfig(async_mode='always')
}
)
```
## Design Philosophy
Following qh's "convention over configuration" approach:
- Default conventions use thread pools and query params
- Explicit configuration available for all aspects
- Built on standard patterns (HTTP 202 Accepted, polling)
- No external dependencies required (au integration optional)
## Testing
All 16 async tests passing:
- Basic sync/async execution
- Task status and result retrieval
- Failed task handling
- Multiple configuration modes (query, header, always)
- TTL and cleanup
- Native async functions
- Task management endpoints
- Multiple function support
## Documentation
Comprehensive README update with:
- Quickstart examples
- Advanced configuration
- Real-world use cases
- Migration guide
- Comparison with other frameworks
- au package integration guide
## Future Enhancements
The implementation is designed to support:
- Integration with au package for distributed execution
- Custom storage backends (Redis, database, etc.)
- WebSocket-based result streaming
- Task prioritization and scheduling
- Task dependencies and workflows
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