def test_nested_logical_conditions(sample_df):
step = FilterStep(
name='filter',
condition={
'and': [
{
'or': [
{
'column': 'colA',
'operator': 'eq',
'value': 'toto',
},
{
'column': 'colC',
'operator': 'lt',
'value': 33,
},
]
},
{'column': 'colB', 'operator': 'gt', 'value': 2},
]
},
)
df_result = execute_filter(step, sample_df)
assert_dataframes_equals(df_result, DataFrame({'colA': ['tata'], 'colB': [3], 'colC': [25]}))
def test_simple_notnull_filter(sample_df):
step = FilterStep(
name='filter',
condition={
'column': 'colA',
'operator': 'notnull',
},
)
df_result = execute_filter(step, sample_df)
assert_dataframes_equals(df_result, sample_df)
def test_simple_null_filter(sample_df):
step = FilterStep(
name='filter',
condition={
'column': 'colA',
'operator': 'isnull',
},
)
df_result = execute_filter(step, sample_df)
assert df_result.empty
def test_simple_lt_filter(sample_df):
step = FilterStep(
name='filter',
condition={
'column': 'colB',
'operator': 'lt',
'value': 2,
},
)
df_result = execute_filter(step, sample_df)
assert_dataframes_equals(df_result, DataFrame({'colA': ['toto'], 'colB': [1], 'colC': [100]}))
def test_simple_eq_filter(sample_df):
step = FilterStep(
name='filter',
condition={
'column': 'colA',
'operator': 'eq',
'value': 'tutu',
},
)
df_result = execute_filter(step, sample_df)
assert_dataframes_equals(df_result, DataFrame({'colA': ['tutu'], 'colB': [2], 'colC': [50]}))
def test_simple_matches_filter(sample_df):
step = FilterStep(
name='filter',
condition={
'column': 'colA',
'operator': 'matches',
'value': 'a.a',
},
)
df_result = execute_filter(step, sample_df)
assert_dataframes_equals(df_result, DataFrame({'colA': ['tata'], 'colB': [3], 'colC': [25]}))
def test_simple_ne_filter(sample_df):
step = FilterStep(
name='filter',
condition={
'column': 'colA',
'operator': 'ne',
'value': 'tutu',
},
)
df_result = execute_filter(step, sample_df)
assert_dataframes_equals(
df_result, DataFrame({'colA': ['toto', 'tata'], 'colB': [1, 3], 'colC': [100, 25]})
)
def test_and_logical_conditions(sample_df):
step = FilterStep(
name='filter',
condition={
'and': [
{
'column': 'colB',
'operator': 'le',
'value': 2,
},
{
'column': 'colC',
'operator': 'gt',
'value': 75,
},
]
},
)
df_result = execute_filter(step, sample_df)
assert_dataframes_equals(df_result, DataFrame({'colA': ['toto'], 'colB': [1], 'colC': [100]}))
