1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
38
39
40
41
42
43
44
45
46
47
48
49
50
51
52
53
54
55
56
57
58
59
60
61
62
63
64
65
66
67
68
69
70
71
72
73
74
75
76
77
78
79
80
81
82
83
84
85
86
87
88
89
90
91
92
93
94
95
96
97
98
99
100
101
102
|
# Registry Pattern
## Overview
The Registry pattern allows components to register themselves via decorators, enabling automatic discovery and centralized management of available types.
## Structure
```python
# In module __init__.py (e.g., data_module/dataset/__init__.py)
from typing import Dict, Callable, TypeVar
T = TypeVar('T')
DATASET_FACTORY: Dict[str, type] = {}
def register_dataset(name: str) -> Callable[[T], T]:
"""Decorator to register dataset classes."""
def decorator(cls: T) -> T:
DATASET_FACTORY[name] = cls
return cls
return decorator
```
## Usage
```python
# In implementation file (e.g., simple_dataset.py)
from data_module.dataset import register_dataset
@register_dataset("simple")
class SimpleDataset(Dataset):
def __init__(self, cfg):
# Implementation
pass
```
## Benefits
- **Automatic registration**: Components register themselves on import
- **Declarative**: Single decorator line replaces manual registration code
- **Import-time discovery**: Auto-import pattern finds all implementations
- **Type-safe**: Preserves original class type
## Implementation Details
1. Decorator returns the class unchanged (for immediate use)
2. Side effect: adds class to factory dict
3. Name parameter must be unique per module
4. Registration happens at module import time
## Advanced Patterns
### Registration with Config
```python
def register_model(name: str):
def decorator(cls):
MODEL_FACTORY[name] = cls
# Add config validation
cls._config_schema = getattr(cls, '_config_schema', {})
return cls
return decorator
```
### Conditional Registration
```python
def register_dataset(name: str, experimental: bool = False):
def decorator(cls):
if not experimental or cfg.enable_experimental:
DATASET_FACTORY[name] = cls
return cls
return decorator
```
### Multi-Registry
```python
# Multiple registries in one module
DATASET_FACTORY = {}
AUGMENTATION_FACTORY = {}
def register_dataset(name: str):
def decorator(cls):
DATASET_FACTORY[name] = cls
return cls
return decorator
def register_augmentation(name: str):
def decorator(fn):
AUGMENTATION_FACTORY[name] = fn
return fn
return decorator
```
## Best Practices
- **Unique names**: Use descriptive, unique registration names
- **Documentation**: Document required parameters in class docstring
- **Validation**: Validate config in `__init__`, not in decorator
- **Consistency**: Use same naming convention across modules
|
