[pre-commit.ci] auto fixes from pre-commit.com hooks

doc/source/dev/ci.rst

@@ -12,11 +12,11 @@ icclim continuous integration (CI) aims to assist development by:
 These goals are reached using multiple tools:
    -  pre-commit CI enforces the code style rules. It is run on new pull requests
       and may commit automatically to fix the source code.
-      If it fails to fix the code base, it woill block the PR from being merged. 
+      If it fails to fix the code base, it woill block the PR from being merged.
       The relevant configuration file is ``.pre-commit-config.yaml``.
 
    -  readthedocs, it serves our documentation on https://icclim.readthedocs.io/en/stable/.
-      It is configured with ``.readthedocs.yml`` and runs the generation of the 
+      It is configured with ``.readthedocs.yml`` and runs the generation of the
       documentation on each new pull request.
 
    -  github actions are used to run unit tests and report the results

doc/source/references/ecad_functions_api.rst

@@ -17,4 +17,3 @@ For example to use this new API with the index `su` you can do:
    import icclim
 
    summer_days = icclim.su(in_files=glob.glob("netcdf_files/tasmax*.nc"))
-

doc/source/references/generic_functions_api.rst

@@ -27,4 +27,3 @@ For more details on threshold and how to personalize them, see
 :ref:`threshold` documentation. We also prepared a few examples on
 :ref:`generic_indices_recipes` so that you get an idea of the
 capabilities of these generic indices.
-

doc/source/references/icclim_index_api.rst

@@ -20,7 +20,7 @@ on how to use `icclim.index`.
 
 .. autofunction:: icclim.index(**kwargs)
    :noindex:
-   
+
 .. note::
 
    For the variable names see the :ref:`correspondence table "index -

doc/source/tutorials/notebooks/.jukit/.jukit_info.json

@@ -1 +1 @@
-{"import_complete": 0, "terminal": "nvimterm"}
+{"import_complete": 0, "terminal": "nvimterm"}

doc/source/tutorials/notebooks/averaged_tas_anomaly.py

@@ -1,5 +1,5 @@
 r"""°°°
-# Calculate the Averaged Temperature Anomaly 
+# Calculate the Averaged Temperature Anomaly
 
 ## Averaged Temperature Anomaly 2081-2100 vs 1971-2000 SSP585
 

src/icclim/main.py

@@ -37,7 +37,6 @@
     ClimateVariable,
     build_climate_vars,
 )
-from icclim.pre_processing.input_parsing import build_input_dict
 from icclim.models.constants import (
     RESAMPLE_METHOD,
     UNITS_KEY,
@@ -52,6 +51,7 @@
     QuantileInterpolationRegistry,
 )
 from icclim.models.standard_index import StandardIndex
+from icclim.pre_processing.input_parsing import build_input_dict
 from icclim.user_indices import parse
 from icclim.utils import read_date
 

src/icclim/models/climate_variable.py

@@ -3,6 +3,7 @@
 A climate variable is a structure that contains all the pre-processed input varaible to compute a climate index.
 A climate index may require one or more climate variables to be computed.
 """
+
 from __future__ import annotations
 
 from collections.abc import Sequence
@@ -22,7 +23,6 @@
     build_reference_da,
     build_studied_data,
     guess_input_type,
-    guess_var_names,
     read_dataset,
 )
 
@@ -34,7 +34,7 @@
 
     from icclim.generic_indices.standard_variable import StandardVariable
     from icclim.generic_indices.thresholds.models import Threshold
-    from icclim.icclim_types import InFileBaseType, InFileLike
+    from icclim.icclim_types import InFileBaseType
     from icclim.models.global_metadata import GlobalMetadata
     from icclim.models.standard_index import StandardIndex
     from icclim.pre_processing.in_file_dictionary import InFileDictionary
@@ -45,7 +45,7 @@ class ClimateVariable:
     """
     ClimateVariable is a dataclass that represents a variable used to compute a climate index.
 
-    It groups together the input variable (studied_data), its associated metadata (standard_var) 
+    It groups together the input variable (studied_data), its associated metadata (standard_var)
     if any, the threshold it must be compared to.
 
     Attributes
@@ -77,7 +77,7 @@ def build_indicator_metadata(
     ) -> dict[str, str | dict]:
         """
         Build the metadata for the indicator that will be computed with this variable.
-        
+
         Parameters
         ----------
         src_freq: Frequency
@@ -145,7 +145,7 @@ def build_climate_vars(
 
     Returns
     -------
-    list of ClimateVariable that will be used to compute the climate index.    
+    list of ClimateVariable that will be used to compute the climate index.
     """
     if standard_index is not None and len(standard_index.input_variables) > len(
         climate_vars_dict
@@ -249,6 +249,7 @@ def _build_reference_variable(
         is_reference=True,
     )
 
+
 def build_climate_var(
     climate_var_name: str,
     climate_var_data: InFileDictionary | InFileBaseType,

src/icclim/models/global_metadata.py

@@ -10,6 +10,7 @@
 
 class GlobalMetadata(TypedDict):
     """Global metadata model."""
+
     history: str | None
     source: str | None
     time_encoding: dict | None  # to be read from ds.time.encoding

src/icclim/pre_processing/in_file_dictionary.py

@@ -21,7 +21,7 @@ class InFileDictionary(TypedDict):
         in_files = {
             "tasmax": {
                 "study": "tasmax-store.zarr",
-            "threshold": build_threshold(operator=">", value=["per-1.nc", "per-2.nc"]),
+                "threshold": build_threshold(operator=">", value=["per-1.nc", "per-2.nc"]),
             },
             "pr": "pr.nc",
             "tasmin": {"study": "tasmin.nc"},

src/icclim/pre_processing/input_parsing.py

@@ -24,11 +24,10 @@
 
     from pint import Quantity
 
-    from icclim.icclim_types import InFileBaseType
+    from icclim.generic_indices.thresholds.models import Threshold
+    from icclim.icclim_types import InFileBaseType, InFileLike
     from icclim.models.standard_index import StandardIndex
     from icclim.pre_processing.in_file_dictionary import InFileDictionary
-    from icclim.generic_indices.thresholds.models import Threshold
-    from icclim.icclim_types import InFileLike
 
 
 DEFAULT_INPUT_FREQUENCY = "days"
@@ -121,7 +120,7 @@ def guess_var_names(
     Returns
     -------
     list[Hashable]
-        The list of guessed variable names. 
+        The list of guessed variable names.
     """
     if var_names is None:
         return _guess_dataset_var_names(ds=ds, standard_index=standard_index)
@@ -293,6 +292,7 @@ def _build_in_file_dict(
         }
     return {var_name: {"study": input_dataset[var_name]} for var_name in var_names}
 
+
 def _read_dataarray(
     data: DataArray,
     standard_var: StandardVariable | None = None,

tests/test_ecad_indices.py

@@ -1,15 +1,17 @@
 import pytest
-from icclim.ecad.ecad_indices import EcadIndexRegistry, DcscIndexRegistry
+from icclim.ecad.ecad_indices import DcscIndexRegistry, EcadIndexRegistry
 from icclim.icclim_exceptions import InvalidIcclimArgumentError
 from icclim.models.standard_index import StandardIndex
 
+
 def test_listing():
     res = EcadIndexRegistry.to_list()
     indices = [
         k for k, v in EcadIndexRegistry.__dict__.items() if isinstance(v, StandardIndex)
     ]
     assert len(res) == len(indices)
 
+
 class TestIndexFromString:
     def test_simple(self):
         res = EcadIndexRegistry.lookup("SU")
@@ -23,6 +25,7 @@ def test_error(self):
         with pytest.raises(InvalidIcclimArgumentError):
             EcadIndexRegistry.lookup("cacahuête")
 
+
 def test_dcsc_index_registry():
     # Test the length of the index registry
     assert len(DcscIndexRegistry.to_list()) == 24