lint: flake8

tests/integration_tests/test_rule_based.py

@@ -47,7 +47,6 @@ def test_1_stack_overflow_survey(self):
         df = pd.read_csv("tests/data/stack_overflow_survey_sample.csv")
         config = {'engine': 'rule_based', 'pct_invalid': 0, 'seed': 420, 'mp_cutoff': 1e4}
 
-
         expected_types = {
             'Respondent': 'integer',
             'Professional': 'binary',

tests/unit_tests/rule_based/test_infer_dtypes.py

@@ -7,6 +7,7 @@
 
 get_column_data_type = RuleBasedEngine.get_column_data_type
 
+
 class TestInferDtypes(unittest.TestCase):
     def test_negative_integers(self):
         data = pd.DataFrame([-random.randint(-10, 10) for _ in range(100)], columns=['test_col'])

type_infer/base.py

@@ -27,7 +27,7 @@ def __init__(self):
 
 
 class BaseEngine:
-    def __init__(self, stable = True):
+    def __init__(self, stable=True):
         self.stable = stable  # whether the engine is stable or not (i.e. experimental)
 
     def infer(self, df) -> TypeInformation:
@@ -36,4 +36,4 @@ def infer(self, df) -> TypeInformation:
 
 
 class ENGINES:
-    RULE_BASED = 'rule_based'
+    RULE_BASED = 'rule_based'

type_infer/rule_based/core.py

@@ -15,7 +15,7 @@
 
 
 class RuleBasedEngine(BaseEngine):
-    def __init__(self, config = None):
+    def __init__(self, config=None):
         """
         :param config: a dictionary containing the configuration for the engine
                 pct_invalid : float
@@ -96,9 +96,9 @@ def infer(self, data: pd.DataFrame) -> TypeInformation:
         # @TODO Column removal logic was here, if the column was an identifier, move it elsewhere
         return type_information
 
-
     # @TODO: hardcode for distance, time, subunits of currency (e.g. cents) and other common units
     # @TODO: Add tests with plenty of examples
+
     def get_quantity_col_info(self, col_data: pd.Series) -> str:
         assert isinstance(col_data, pd.Series)
         char_const = None
@@ -134,7 +134,6 @@ def get_quantity_col_info(self, col_data: pd.Series) -> str:
         else:
             return False, None
 
-
     def get_binary_type(self, element: object) -> str:
         try:
             is_img = imghdr.what(element)
@@ -153,7 +152,6 @@ def get_binary_type(self, element: object) -> str:
             # Not a file or file doesn't exist
             return None
 
-
     def get_numeric_type(self, element: object) -> str:
         """ Returns the subtype inferred from a number string, or False if its not a number"""
         string_as_nr = cast_string_to_python_type(str(element))
@@ -177,7 +175,6 @@ def get_numeric_type(self, element: object) -> str:
             except Exception:
                 return None
 
-
     def type_check_sequence(self, element: object) -> str:
         dtype_guess = None
 
@@ -259,7 +256,6 @@ def type_check_date(element: object) -> str:
 
         return None
 
-
     def count_data_types_in_column(self, data):
         dtype_counts = Counter()
 
@@ -282,8 +278,12 @@ def count_data_types_in_column(self, data):
 
         return dtype_counts
 
-
-    def get_column_data_type(self, data: Union[pd.Series, np.ndarray, list], full_data: pd.DataFrame, col_name: str, pct_invalid: float):
+    def get_column_data_type(self,
+                             data: Union[pd.Series, np.ndarray, list],
+                             full_data: pd.DataFrame,
+                             col_name: str,
+                             pct_invalid: float
+                             ):
         """
         Provided the column data, define its data type and data subtype.