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[python] added f-strings to python-package/lightgbm/dask.py #4144

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merged 17 commits into from
May 15, 2021
Merged

[python] added f-strings to python-package/lightgbm/dask.py #4144

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1bd0e2c
added f-string to dask.py
NovusEdge Mar 30, 2021
0af6e62
Update python-package/lightgbm/dask.py
NovusEdge Apr 10, 2021
c056e23
Update python-package/lightgbm/dask.py
NovusEdge Apr 10, 2021
27e988b
Updated branch
NovusEdge Apr 10, 2021
74e64df
Merge branch 'master' of git://github.com/microsoft/LightGBM into mic…
NovusEdge Apr 10, 2021
ee77237
Updated file as per specifications
NovusEdge Apr 11, 2021
210f305
Updated file as per specifications
NovusEdge Apr 11, 2021
32d2215
Merge https://github.com/microsoft/LightGBM into dask
NovusEdge Apr 11, 2021
f058167
Removed warning as per specification
NovusEdge Apr 13, 2021
23521a5
Merge branch 'master' into dask
jameslamb May 10, 2021
8f01b98
update other places
jameslamb May 11, 2021
8c21be0
Apply suggestions from code review
jameslamb May 12, 2021
64abdcb
Merge branch 'master' into dask
jameslamb May 13, 2021
22c20eb
revert unnecessary change
jameslamb May 13, 2021
a20cb1d
Merge branch 'dask' of github.com:NovusEdge/LightGBM into dask
jameslamb May 13, 2021
c032e56
Apply suggestions from code review
jameslamb May 13, 2021
ef90c7f
Merge branch 'master' into dask
jameslamb May 14, 2021
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69 changes: 32 additions & 37 deletions python-package/lightgbm/dask.py
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Original file line number Diff line number Diff line change
Expand Up @@ -306,7 +306,7 @@ def _train(
'voting_parallel'
}
if params["tree_learner"] not in allowed_tree_learners:
_log_warning('Parameter tree_learner set to %s, which is not allowed. Using "data" as default' % params['tree_learner'])
_log_warning(f'Parameter tree_learner set to {params["tree_learner"]}, which is not allowed. Using "data" as default')
params['tree_learner'] = 'data'

# Some passed-in parameters can be removed:
Expand Down Expand Up @@ -704,12 +704,11 @@ def __init__(

_base_doc = LGBMClassifier.__init__.__doc__
_before_kwargs, _kwargs, _after_kwargs = _base_doc.partition('**kwargs')
_base_doc = (
_before_kwargs
+ 'client : dask.distributed.Client or None, optional (default=None)\n'
+ ' ' * 12 + 'Dask client. If ``None``, ``distributed.default_client()`` will be used at runtime. The Dask client used by this class will not be saved if the model object is pickled.\n'
+ ' ' * 8 + _kwargs + _after_kwargs
)
_base_doc = f"""
{_before_kwargs}client : dask.distributed.Client or None, optional (default=None)
{' ':4}Dask client. If ``None``, ``distributed.default_client()`` will be used at runtime. The Dask client used by this class will not be saved if the model object is pickled.
{_kwargs}{_after_kwargs}
"""

# the note on custom objective functions in LGBMModel.__init__ is not
# currently relevant for the Dask estimators
Expand Down Expand Up @@ -749,11 +748,10 @@ def fit(
+ _base_doc[_base_doc.find('verbose :'):])

# DaskLGBMClassifier support for callbacks and init_model is not tested
fit.__doc__ = (
_base_doc[:_base_doc.find('callbacks :')]
+ '**kwargs\n'
+ ' ' * 12 + 'Other parameters passed through to ``LGBMClassifier.fit()``.\n'
)
fit.__doc__ = f"""
{_base_doc[:_base_doc.find('callbacks :')]}**kwargs
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Other parameters passed through to ``LGBMClassifier.fit()``
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"""

def predict(self, X: _DaskMatrixLike, **kwargs: Any) -> dask_Array:
"""Docstring is inherited from the lightgbm.LGBMClassifier.predict."""
Expand Down Expand Up @@ -858,13 +856,11 @@ def __init__(

_base_doc = LGBMRegressor.__init__.__doc__
_before_kwargs, _kwargs, _after_kwargs = _base_doc.partition('**kwargs')
_base_doc = (
_before_kwargs
+ 'client : dask.distributed.Client or None, optional (default=None)\n'
+ ' ' * 12 + 'Dask client. If ``None``, ``distributed.default_client()`` will be used at runtime. The Dask client used by this class will not be saved if the model object is pickled.\n'
+ ' ' * 8 + _kwargs + _after_kwargs
)

_base_doc = f"""
{_before_kwargs}client : dask.distributed.Client or None, optional (default=None)
{' ':4}Dask client. If ``None``, ``distributed.default_client()`` will be used at runtime. The Dask client used by this class will not be saved if the model object is pickled.
{_kwargs}{_after_kwargs}
"""
# the note on custom objective functions in LGBMModel.__init__ is not
# currently relevant for the Dask estimators
__init__.__doc__ = _base_doc[:_base_doc.find('Note\n')]
Expand Down Expand Up @@ -899,15 +895,16 @@ def fit(
)

# DaskLGBMRegressor does not support evaluation data, or early stopping
_base_doc = (_base_doc[:_base_doc.find('group :')]
+ _base_doc[_base_doc.find('verbose :'):])
fit.__doc__ = f"""
{_base_doc[:_base_doc.find('callbacks :')]}**kwargs
Other parameters passed through to ``LGBMRegressor.fit()``
"""
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# DaskLGBMRegressor support for callbacks and init_model is not tested
fit.__doc__ = (
_base_doc[:_base_doc.find('callbacks :')]
+ '**kwargs\n'
+ ' ' * 12 + 'Other parameters passed through to ``LGBMRegressor.fit()``.\n'
)
fit.__doc__ = f"""
{_base_doc[:_base_doc.find('callbacks :')]}**kwargs
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Other parameters passed through to ``LGBMRegressor.fit()``
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"""

def predict(self, X: _DaskMatrixLike, **kwargs) -> dask_Array:
"""Docstring is inherited from the lightgbm.LGBMRegressor.predict."""
Expand Down Expand Up @@ -993,12 +990,11 @@ def __init__(

_base_doc = LGBMRanker.__init__.__doc__
_before_kwargs, _kwargs, _after_kwargs = _base_doc.partition('**kwargs')
_base_doc = (
_before_kwargs
+ 'client : dask.distributed.Client or None, optional (default=None)\n'
+ ' ' * 12 + 'Dask client. If ``None``, ``distributed.default_client()`` will be used at runtime. The Dask client used by this class will not be saved if the model object is pickled.\n'
+ ' ' * 8 + _kwargs + _after_kwargs
)
_base_doc = f"""
{_before_kwargs}client : dask.distributed.Client or None, optional (default=None)
{' ':4}Dask client. If ``None``, ``distributed.default_client()`` will be used at runtime. The Dask client used by this class will not be saved if the model object is pickled.
{_kwargs}{_after_kwargs}
"""

# the note on custom objective functions in LGBMModel.__init__ is not
# currently relevant for the Dask estimators
Expand Down Expand Up @@ -1040,11 +1036,10 @@ def fit(
+ _base_doc[_base_doc.find('verbose :'):])

# DaskLGBMRanker support for callbacks and init_model is not tested
fit.__doc__ = (
_base_doc[:_base_doc.find('callbacks :')]
+ '**kwargs\n'
+ ' ' * 12 + 'Other parameters passed through to ``LGBMRanker.fit()``.\n'
)
fit.__doc__ = f"""
{_base_doc[:_base_doc.find('callbacks :')]}**kwargs
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Other parameters passed through to ``LGBMRegressor.fit()``
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"""

def predict(self, X: _DaskMatrixLike, **kwargs: Any) -> dask_Array:
"""Docstring is inherited from the lightgbm.LGBMRanker.predict."""
Expand Down