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Support property attributes in repr of BaseMixin #469

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merged 5 commits into from
Sep 5, 2024
Merged

Support property attributes in repr of BaseMixin #469

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25540b0
replace self.__dict__[arg] with getattr(self, arg)
Sep 3, 2024
4194b0e
update changelog
Sep 3, 2024
20c39a1
add tests
Sep 4, 2024
3c50db3
fix
Sep 4, 2024
993f6f5
fix
Sep 4, 2024
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2 changes: 1 addition & 1 deletion CHANGELOG.md
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Expand Up @@ -29,7 +29,7 @@ and this project adheres to [Semantic Versioning](https://semver.org/spec/v2.0.0
-

### Changed
-
- Add support of property attributes in `__repr__` of `BaseMixin` ([#469](https://github.com/etna-team/etna/pull/469))
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Not only __repr__, but also to_dict.

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6 changes: 3 additions & 3 deletions etna/core/mixins.py
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Expand Up @@ -32,11 +32,11 @@ def __repr__(self):
if param.kind == param.VAR_POSITIONAL:
continue
elif param.kind == param.VAR_KEYWORD:
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Let's create some basic tests on working with BaseMixin. The methods to functionality to check is:

  • repr
    • Add test on dummy class with private attribute and public property
  • to_dict
    • We already have file test_to_dict, let's add new tests here
    • Add test on dummy class with private attribute and public property
  • set_params
    • We already have file test_set_params, let's add new tests here
    • Add test on dummy class with private attribute and public property

for arg_, value in self.__dict__[arg].items():
for arg_, value in getattr(self, arg).items():
args_str_representation += f"{arg_} = {repr(value)}, "
else:
try:
value = self.__dict__[arg]
value = getattr(self, arg)
except KeyError as e:
value = None
warnings.warn(f"You haven't set all parameters inside class __init__ method: {e}")
Expand Down Expand Up @@ -90,7 +90,7 @@ def to_dict(self):
init_parameters = self._get_init_parameters()
params = {}
for arg in init_parameters.keys():
value = self.__dict__[arg]
value = getattr(self, arg)
if value is None:
continue
params[arg] = BaseMixin._parse_value(value=value)
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1 change: 0 additions & 1 deletion pyproject.toml
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Expand Up @@ -209,7 +209,6 @@ filterwarnings = [
"ignore: Given top_k=.* is less than n_segments=.*. Algo will filter data without Gale-Shapley run.",
"ignore: This model doesn't work with exogenous features",
"ignore: Some of external objects in input parameters could be not",
"ignore: You haven't set all parameters inside class __init__ method.* 'is_freezed'",
# external warnings
"ignore: Attribute 'logging_metrics' is an instance of `nn.Module` and is already",
"ignore: Attribute 'loss' is an instance of `nn.Module` and is already",
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