Breaking changes
**Auto generation of `**init**`method from type hints is decoupled from`TreeClass`**
**Alternatives**
Use:
1. _Preferably_ decorate with `pytreeclass.autoinit` with `pytreeclass.field` as field specifier. as `pytreeclass.field` has more features (e.g. `callbacks`, multiple argument kind selection) and the init generation is cached compared to `dataclasses`.
2. decorate with `dataclasses.dataclass` with `dataclasses.field` as field specifier. however :
1. _Must_ set `fronzen=False` because the `__setattr__`, `__delattr__` is handled by `TreeClass`
2. _Optionally_ `repr=False` to be handled by `TreeClass`
3. _Optionally_ `eq=hash=False` as it is handled by `TreeClass`
<div align="center">
<table>
<tr>
<td>
Before
python
import jax.tree_util as jtu
import pytreeclass as tc
import dataclasses as dc
class Tree(tc.TreeClass):
a: int = 1
jtu.tree_leaves(Tree())
[1]
</td>
<td>
After
Equivalent behavior when decorating with either:
1. `pytreeclass.autoinit`
2. `dataclasses.dataclass`
python
import jax.tree_util as jtu
import pytreeclass as tc
tc.autoinit
class Tree(tc.TreeClass):
a: int = 1
jtu.tree_leaves(Tree())
[1]
</td>
<tr>
</table>
</div>
This change aims to fix the ambiguity of using the `dataclass` mental model in the following siutations:
1. subclassing. previously, using `TreeClass` as a base class is equivalent to decorating the class with `dataclasses.dataclass`, however this is a bit challenging to understand as demonstrated in the next example:
python
import pytreeclass as tc
import dataclasses as dc
class A(tc.TreeClass):
def ___init__(self, a:int):
self.a = a
class B(A):
...
When instantiating `B(a=...)`, an error will be raised, because using `TreeClass` is equivalent of decorating all classes with `dataclass`, which synthesize the `__init__` method based on the fields.
Since no fields (e.g. type hinted values) then the synthesized `__init__` method .
The previous code is equivalent to this code.
python
dc.dataclass
class A:
def __init__(self, a:int):
self.a = a
dc.dataclass
class B:
...
2. `dataclass_transform` does not play nicely with user created `__init__` see [1](https://github.com/microsoft/pyright/issues/4738), [2](https://github.com/python/typing/discussions/1187)
`leafwise_transform` is decoupled from `TreeClass`.
instead decorate the class with `pytreeclass.leafwise`.