black: Remove unnecessary blank lines in multiple files

Various files across the project had unnecessary blank lines which have been removed in this commit. These changes make the code more concise and easy to read. It's a part of making the code adhere to best coding practices for readability.

bblocks/import_tools/common.py

@@ -42,7 +42,6 @@ def get_data(self, indicators: str | list = "all", **kwargs) -> pd.DataFrame:
             indicators_ = self._data.values()
 
         if isinstance(indicators, list):
-
             for _ in indicators:
                 if _ not in self._data:
                     logger.warning(f"{_} not loaded or is an invalid indicator.")

bblocks/import_tools/ilo.py

@@ -195,12 +195,10 @@ def load_data(self, indicator: str | list) -> ImportData:
             indicator = [indicator]
 
         for ind in indicator:  # loop through indicators
-
             path = BBPaths.raw_data / f"{ind}.csv"
 
             # download data if not saved to disk
             if not path.exists():
-
                 # download glossaries if not loaded to object
                 if self._glossaries is None:
                     self._load_glossaries()
@@ -245,7 +243,6 @@ def update_data(self, reload_data: bool = True) -> ImportData:
             self._load_area_dict()
 
         for ind in self._data:  # loop through loaded indicators
-
             # download data
             download_data(
                 ind, BBPaths.raw_data / f"{ind}.csv", self._glossaries, self._area_dict

bblocks/other_tools/dictionaries.py

@@ -63,7 +63,6 @@ def update_dictionaries() -> None:
 
 
 def g20_countries() -> dict:
-
     return Dict(
         {
             x: convert(x, src="ISO3", to="name_short", not_found=None)

tests/test_dataframe_tools/test_df_common.py

@@ -5,7 +5,6 @@
 
 
 def test__get_wb_ind():
-
     data = __get_wb_ind(
         ind_code="SP.POP.TOTL", ind_name="test_population", update=False, mrnev=False
     )
@@ -23,7 +22,6 @@ def test__get_wb_ind():
 
 
 def test_get_population_df():
-
     data = get_population_df(most_recent_only=True, update=False)
 
     assert list(data.columns) == ["year", "iso_code", "population"]