fix(doc): improve python/resampling/resampling_hads.py documentation

python/resampling/resampling_hads.py

@@ -10,28 +10,31 @@
 import os
 from os import cpu_count
 
-import netCDF4
 import pandas as pd
-import scipy
 import xarray as xr  # requires rioxarray extension
 from tqdm import tqdm
 
 
 def enforce_date_dropping(
     raw_data: xr.Dataset, converted_data: xr.Dataset
 ) -> xr.Dataset:
-    """
-    Workaround to avoid convert_calendar misbehavior with monthly data files.
-
-    For leap years, the conversion assigns dropped data to the previous date instead of deleting it.
-    Here we manually delete those dates to avoid duplicates later in the pipeline.
-
-    Args:
-        raw_data (xr.Dataset): The original data.
-        converted_data (xr.Dataset): The data after conversion.
-
-    Returns:
-        xr.Dataset: The converted data with specific dates dropped.
+    """Workaround convert_calendar misbehavior with monthly data files.
+
+    For leap years, the conversion assigns dropped data to the previous
+    date instead of deleting it. Here we manually delete those dates to
+    avoid duplicates later in the pipeline.
+
+    Parameters
+    ----------
+    raw_data
+        The original data.
+    converted_data
+        The data after conversion.
+
+    Returns
+    -------
+    xr.Dataset
+        The converted data with specific dates dropped.
     """
     month_day_drop = {(1, 31), (4, 1), (6, 1), (8, 1), (10, 1), (12, 1)}
     time_values = pd.DatetimeIndex(raw_data.coords["time"].values)
@@ -56,16 +59,28 @@ def enforce_date_dropping(
     return converted_data
 
 
-def resample_hadukgrid(x):
-    """
-    Resamples the UKHADs data to match UKCP18 data both spatially and temporally
-    and saves the resampled data to the output directory.
-    inputs:
-        x: list of inputs
-            x[0]: file to be resampled
-            x[1]: x_grid
-            x[2]: y_grid
-            x[3]: output_dir
+def resample_hadukgrid(x: list) -> int:
+    """Resample UKHADs data to match UKCP18 spatially and temporally.
+
+    Results are saved to the output directory.
+
+    Parameters
+    ----------
+    x
+        x[0]: file to be resampled
+        x[1]: x_grid
+        x[2]: y_grid
+        x[3]: output_dir
+
+    Returns
+    -------
+    bool
+        Whether function was a success (True) or not (False).
+
+    Raises
+    ------
+    Exception
+        Generic execption for any errors raised.
     """
     try:
         # due to the multiprocessing implementations inputs come as list