def test_drop_missing_input_implies_no_code_success():
arguments = {
'parameters': {
'attributes': ['class']
},
'named_inputs': {},
'named_outputs': {
'output data': 'out'
}
}
instance = DropOperation(**arguments)
assert instance.generate_code() is None
def test_drop_minimal_params_success():
params = {'attributes': 'TEST'}
n_in = {'input data': 'input_1'}
n_out = {'output data': 'output_1'}
instance = DropOperation(params, named_inputs=n_in, named_outputs=n_out)
code = instance.generate_code()
expected_code = "{out} = {input}.drop(columns={columns})" \
.format(out=n_out['output data'], input=n_in['input data'],
columns=params['attributes'])
result, msg = compare_ast(ast.parse(code), ast.parse(expected_code))
assert result, msg
def test_drop_success():
df = util.iris(size=10)
arguments = {
'parameters': {
'attributes': ['class']
},
'named_inputs': {
'input data': 'df',
},
'named_outputs': {
'output data': 'out'
}
}
instance = DropOperation(**arguments)
result = util.execute(instance.generate_code(), {'df': df})
assert result['out'].equals(util.iris(size=10).drop(['class'], axis=1))
def test_drop_invalid_attribute_param_fail():
df = util.iris(size=10)
arguments = {
'parameters': {
'attributes': ['invalid']
},
'named_inputs': {
'input data': 'df',
},
'named_outputs': {
'output data': 'out'
}
}
instance = DropOperation(**arguments)
with pytest.raises(KeyError) as key_err:
util.execute(instance.generate_code(), {'df': df})
assert "['invalid'] not found in axis" in str(key_err.value)
def test_drop_success():
slice_size = 10
df = ['df', util.iris(size=slice_size)]
arguments = {
'parameters': {
DropOperation.ATTRIBUTES_PARAM: ['class']
},
'named_inputs': {
'input data': df[0],
},
'named_outputs': {
'output data': 'out'
}
}
instance = DropOperation(**arguments)
result = util.execute(instance.generate_code(),
{'df': df[1]})
assert result['out'].equals(
util.iris(size=slice_size).drop(['class'], axis=1))
def test_drop_fail_invalid_attribute():
slice_size = 10
df = ['df', util.iris(size=slice_size)]
arguments = {
'parameters': {
DropOperation.ATTRIBUTES_PARAM: ['invalid']
},
'named_inputs': {
'input data': df[0],
},
'named_outputs': {
'output data': 'out'
}
}
instance = DropOperation(**arguments)
with pytest.raises(KeyError) as exc_info:
result = util.execute(instance.generate_code(),
{'df': df[1]})
assert "['invalid'] not found in axis" in str(exc_info.value)
def test_drop_success_missing_input_implies_no_code():
slice_size = 10
df = ['df', util.iris(size=slice_size)]
arguments = {
'parameters': {
DropOperation.ATTRIBUTES_PARAM: ['class']
},
'named_inputs': {},
'named_outputs': {
'output data': 'out'
}
}
instance = DropOperation(**arguments)
assert not instance.has_code
def test_drop_missing_parameters_fail():
slice_size = 10
df = ['df', util.iris(size=slice_size)]
arguments = {
'parameters': {},
'named_inputs': {
'input data': df[0],
},
'named_outputs': {
'output data': 'out'
}
}
with pytest.raises(ValueError) as val_err:
DropOperation(**arguments)
assert "'attributes' must be informed for task" in str(val_err.value)
def test_drop_success_no_output_implies_no_code():
"""
Change DropOperation: it shouldn't generate
code if there is not output!
"""
slice_size = 10
df = ['df', util.iris(size=slice_size)]
arguments = {
'parameters': {
DropOperation.ATTRIBUTES_PARAM: ['class']
},
'named_inputs': {
'input data': df[0],
},
'named_outputs': {
}
}
instance = DropOperation(**arguments)
assert not instance.has_code