feat: add range_len for easing progress information

python/clim_recal/utils/core.py

@@ -137,6 +137,37 @@ def from_year_range_to_str(
 DEFAULT_CPM_START_MONTH_DAY: Final[MonthDay] = MonthDay(month=12, day=1)
 
 
+def range_len(
+    maximum: int, start: int = 0, stop: int | None = None, step: int = 1
+) -> int:
+    """Cacluate the total length of range with indexing.
+
+    Parameters
+    ----------
+    maximum
+        Maximum range length.
+    start
+        Index to start from.
+    stop
+        Index to stop at.
+    step
+        Steps between `start` and `stop` indexes
+
+    Examples
+    --------
+    >>> range_len(100)
+    100
+    >>> range_len(100, 90)
+    10
+    >>> range_len(100, 20, 30)
+    10
+    >>> range_len(100, 20, 30, 2)
+    5
+    """
+    stop = stop or maximum
+    return (stop - start - 1) // step + 1
+
+
 def run_callable_attr(
     instance: object, method_name: str = "execute", *args, **kwargs
 ) -> Any:

python/clim_recal/utils/xarray.py

@@ -42,6 +42,7 @@
     ISO_DATE_FORMAT_STR,
     climate_data_mount_path,
     console,
+    range_len,
     results_path,
 )
 from .data import (
@@ -1513,8 +1514,8 @@ class XarrayTimeSeriesCalcManager(Sequence):
     >>> tmp_save: Path = getfixture('tmp_path') / 'xarray-time-series-summary-manager'
     >>> xr_var_managers = XarrayTimeSeriesCalcManager(save_folder=tmp_save)
     >>> save_paths: tuple[Path, ...] = xr_var_managers.save_joined_xr_time_series(stop=2, ts_stop=2)
-    Aggregating '05' 'tasmax' ...
-    Aggregating '06' 'tasmax' ...
+    Aggregating '05' 'tasmax' (1/2)...
+    Aggregating '06' 'tasmax' (2/2)...
     >>> pprint(save_paths)
     (...Path('.../median-tasmax-05.nc'),
      ...Path('.../median-tasmax-06.nc'))
@@ -1583,14 +1584,14 @@ def join_xr_time_series_vars_iter(
     ) -> Iterable[tuple[T_Dataset, Path]]:
         if not self.source_folders:
             self._set_source_folders()
+        aggregate_count: int = range_len(
+            maximum=len(self), start=start, stop=stop, step=step
+        )
         for i, var_path in enumerate(islice(self, start, stop, step)):
             var_path = Path(var_path)
             run, variable = self._get_var_run(var_path)
             log_str: str = f"Aggregating '{variable}' '{run}'"
-            if not start and not stop and step == 1:
-                console.print(f"{log_str} ({i + 1}/{len(self)})...")
-            else:
-                console.print(f"{log_str} ...")
+            console.print(f"{log_str} ({i + 1}/{aggregate_count})...")
             yield join_xr_time_series_var(
                 var_path, start=ts_start, stop=ts_stop, step=ts_step
             ), var_path