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black formating (black is upgraded in github)

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Young
2021-04-27 04:04:43 +00:00
parent 9a74fe34f6
commit 5a7eecabee
6 changed files with 9 additions and 9 deletions
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2
examples/benchmarks/TFT/data_formatters/base.py
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@@ -132,7 +132,7 @@ class GenericDataFormatter(abc.ABC):
return -1, -1 return -1, -1
def get_column_definition(self): def get_column_definition(self):
""""Returns formatted column definition in order expected by the TFT.""" """Returns formatted column definition in order expected by the TFT."""
column_definition = self._column_definition column_definition = self._column_definition

2
qlib/contrib/backtest/position.py
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@@ -128,7 +128,7 @@ class Position:
return self.position["cash"] return self.position["cash"]
def get_stock_amount_dict(self): def get_stock_amount_dict(self):
"""generate stock amount dict {stock_id : amount of stock} """ """generate stock amount dict {stock_id : amount of stock}"""
d = {} d = {}
stock_list = self.get_stock_list() stock_list = self.get_stock_list()
for stock_code in stock_list: for stock_code in stock_list:

2
qlib/contrib/report/graph.py
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@@ -18,7 +18,7 @@ from ...utils import get_module_by_module_path
class BaseGraph: class BaseGraph:
"""""" """ """
_name = None _name = None

4
qlib/data/dataset/processor.py
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@@ -129,7 +129,7 @@ class FilterCol(Processor):
class TanhProcess(Processor): class TanhProcess(Processor):
""" Use tanh to process noise data""" """Use tanh to process noise data"""
def __call__(self, df): def __call__(self, df):
def tanh_denoise(data): def tanh_denoise(data):
@@ -144,7 +144,7 @@ class TanhProcess(Processor):
class ProcessInf(Processor): class ProcessInf(Processor):
"""Process infinity """ """Process infinity"""
def __call__(self, df): def __call__(self, df):
def replace_inf(data): def replace_inf(data):

4
qlib/model/base.py
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@@ -11,11 +11,11 @@ class BaseModel(Serializable, metaclass=abc.ABCMeta):
@abc.abstractmethod @abc.abstractmethod
def predict(self, *args, **kwargs) -> object: def predict(self, *args, **kwargs) -> object:
""" Make predictions after modeling things """ """Make predictions after modeling things"""
pass pass
def __call__(self, *args, **kwargs) -> object: def __call__(self, *args, **kwargs) -> object:
""" leverage Python syntactic sugar to make the models' behaviors like functions """ """leverage Python syntactic sugar to make the models' behaviors like functions"""
return self.predict(*args, **kwargs) return self.predict(*args, **kwargs)

4
qlib/portfolio/optimizer/base.py
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@@ -5,9 +5,9 @@ import abc
class BaseOptimizer(abc.ABC): class BaseOptimizer(abc.ABC):
""" Construct portfolio with a optimization related method """ """Construct portfolio with a optimization related method"""
@abc.abstractmethod @abc.abstractmethod
def __call__(self, *args, **kwargs) -> object: def __call__(self, *args, **kwargs) -> object:
""" Generate a optimized portfolio allocation """ """Generate a optimized portfolio allocation"""
pass pass