python自定义dataclass实现
dataclass是python3.7中自带的decorator，可以为customer class生成init function，同时支持以attribute形式获取class item。
For example：
@dataclass
class Point:
x: float
_: KW_ONLY
y: float
z: float
p = Point(0, y=1.5, z=2.0)定义dataclass的约束有以下几点：1.所有field必须有annotation，本约束的原因将在后续内容说明 2. ‘non-default parameter follows default parameter’ rule，即有default的param必须在无default的之后。
同时，dataclass并不会依据annotation对field value类型做强约束，这一点与python function相同，即使声明字段为str，传入其他类型也不会报错。
首先通过分析dataclass实现原理，判断如何嵌入自定义内容。
原理很简单，dataclass为class生成了许多function，其中最主要的是 __init__，同时还包括__repr__, __eq__等，每个方法最后都通过_create_fn方法生成。在生成方法时需要得到field name，default，及locals等内容。
关于参数annotation和default的获取分为两步，首先通过`__annotations__`方法得到所有field的annotationdict，注意，此处获得的是有序的。而后，通过get class attribute方法得到所有field的default。使用这种方式要求每个field必须有annotation，原因为，假如class中存在一个field有default没有annotation，则__dict__能够拿到该值，__annotation__中没有该key，无法恢复class field原始的顺序，因而会对生成function造成影响。
关于class field获取的说明如下（截图出自python dataclasses.py）
在搞清原理后，便可以动手实现自定义的dataclass，大致框架如下。
def my_dataclass(_cls):
def _create_fn(name, args, body, *, globals=None, locals=None,
return_type):
"""To generate function in class."""
# Reference: Source code of dataclasses.dataclass
# Doc link: https://docs.python.org/3/library/dataclasses.html
# Reference code link:
# https://github.com/python/cpython/blob/17b16e13bb444001534ed6fccb459084596c8bcf/Lib/dataclasses.py#L412
# Note that we mutate locals when exec() is called
if locals is None:
locals = {}
if 'BUILTINS' not in locals:
import builtins
locals['BUILTINS'] = builtins
locals['_return_type'] = return_type
return_annotation = '->_return_type'
args = ','.join(args)
body = '\n'.join(f' {b}' for b in body)
# Compute the text of the entire function.
txt = f' def {name}({args}){return_annotation}:\n{body}'
local_vars = ', '.join(locals.keys())
txt = f"def __create_fn__({local_vars}):\n{txt}\n return {name}"
ns = {}
exec(txt, globals, ns)
return ns['__create_fn__'](**locals)
def _create_init_fn(cls, fields):
"""Generate the __init__ function for user-defined class."""
# Reference code link:
# https://github.com/python/cpython/blob/17b16e13bb444001534ed6fccb459084596c8bcf/Lib/dataclasses.py#L523
def _get_data_type_from_annotation(anno):
# Get Input(min, max) object class Input
if isinstance(anno, EnumMeta):
return anno
k_type = anno if type(anno) is type else type(anno)
# Get data type if annotation is dsl.types, special logic for Enum
if k_type is Enum:
return anno._enum_class if anno._enum_class else str
return k_type.DATA_TYPE if issubclass(k_type, _Param) else k_type
init_func_annotation = {}
for k, v in getattr(cls, '__annotations__', {}).items():
init_func_annotation[k] = _get_data_type_from_annotation(v)
locals = {f'_type_{key}': init_func_annotation[key] for key, val in fields.items()}
# Collect field defaults if val is parameter and is optional
default_keys = set({key for key, val in fields.items() if val._has_default})
defaults = {f'_dlft_{key}': fields[key].default for key in default_keys}
locals.update(defaults)
_init_param = ['self']
for key in fields:
param = f'{key}:_type_{key}=_dlft_{key}' if key in default_keys else f'{key}:_type_{key}'
_init_param.append(param)
body_lines = [f'self.{key}={key}' for key in fields]
# If no body lines, use 'pass'.
if not body_lines:
body_lines = ['pass']
return _create_fn('__init__', _init_param, body_lines, locals=locals, return_type=None)
def _process_class(cls, all_fields):
"""Generate some functions into class."""
setattr(cls, '__init__', _create_init_fn(cls, all_fields))
# set some other function for your class
# setattr(cls, '__repr__', _create_repr_fn(all_fields))
return cls
def _wrap(cls):
all_fields = your_own_get_fields_function()
return _process_class(cls, all_fields)
return _wrap(_cls)