예제 #1
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    def test_pythagoras(self):
        from math import sqrt

        X = Symbol('X')
        Y = Symbol('Y')

        expr = sym_call(sqrt, X ** 2 + Y ** 2)
        func = to_callable(expr)

        self.assertEqual(func(X=3, Y=4), 5)
예제 #2
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파일: base.py 프로젝트: sharpe5/dfply
 def argument_symbolic_reference(self, arg):
     if hasattr(arg, '_eval'):
         arg = symbolic.to_callable(arg)(self.df)
     if isinstance(arg, pd.Series):
         return arg.name
     elif isinstance(arg, pd.DataFrame):
         return symbolic.sym_call(lambda *x: x, arg.columns.tolist())
     elif isinstance(arg, (list, tuple)):
         arglist = [self.argument_symbolic_reference(subarg) for subarg in arg]
         return symbolic.sym_call(lambda *x: x, *arglist)
     return arg
예제 #3
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 def _label_or_arg(self, df, arg):
     """Recursively extracts pandas series arguments or retains original
     argument."""
     arg = symbolic.to_callable(arg)(df)
     if isinstance(arg, pd.Series):
         return arg.name
     elif isinstance(arg, pd.DataFrame):
         return arg.columns.tolist()
     elif isinstance(arg, (list, tuple)):
         return [self._label_or_arg(df, subarg) for subarg in arg]
     else:
         return arg
예제 #4
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    def test_to_callable_from_nonsymbolic_callable(self):
        func = mock.Mock(return_value='return value')
        del func._eval  # So it doesn't pretend to be symbolic

        test_callable = to_callable(func)

        # Ensure running to_callable does not call the function
        self.assertFalse(func.called)

        result = test_callable('arg1', 'arg2', kwarg_name='kwarg value')

        func.assert_called_once_with('arg1', 'arg2', kwarg_name='kwarg value')
        self.assertEqual(result, 'return value')
예제 #5
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    def test_to_callable_from_symbolic(self):
        mock_expr = mock.Mock()
        mock_expr._eval.return_value = 'eval return value'

        test_callable = to_callable(mock_expr)

        # Ensure running to_callable does not evaluate the expression
        self.assertFalse(mock_expr._eval.called)

        result = test_callable('arg1', 'arg2', kwarg_name='kwarg value')

        mock_expr._eval.assert_called_once_with(
            {0: 'arg1', 1: 'arg2', 'kwarg_name': 'kwarg value'})
        self.assertEqual(result, 'eval return value')
예제 #6
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 def _kwargs_eval(self, df, kwargs):
     return {k:symbolic.to_callable(v)(df) for k,v in kwargs.items()}
예제 #7
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 def _args_eval(self, df, args):
     return [df]+[symbolic.to_callable(arg)(df) for arg in args]
예제 #8
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파일: base.py 프로젝트: sharpe5/dfply
 def call_action(self, args, kwargs):
     self.df = args[0]
     symbolic_function = symbolic.Call(self.function,
                                       args=[self.df]+self.recurse_args(args[1:]),
                                       kwargs=self.recurse_kwargs(kwargs))
     return symbolic.to_callable(symbolic_function)(self.df)
예제 #9
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파일: base.py 프로젝트: sharpe5/dfply
 def call_action(self, args, kwargs):
     symbolic_function = symbolic.Call(self.function,
                                       args=self.recurse_args(args),
                                       kwargs=self.recurse_kwargs(kwargs))
     return symbolic.to_callable(symbolic_function)(args[0])
예제 #10
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 def test_to_callable_from_nonsymbolic_noncallable(self):
     test_callable = to_callable('nonsymbolic')
     self.assertEqual(
         test_callable('arg1', 'arg2', kwarg_name='kwarg value'),
         'nonsymbolic')