more pylint adjustments

.pylintrc.toml

@@ -15,7 +15,7 @@
 # A comma-separated list of package or module names from where C extensions may
 # be loaded. Extensions are loading into the active Python interpreter and may
 # run arbitrary code.
-# extension-pkg-allow-list =
+extension-pkg-allow-list = ["cftime"]
 
 # A comma-separated list of package or module names from where C extensions may
 # be loaded. Extensions are loading into the active Python interpreter and may
@@ -36,7 +36,7 @@ fail-under = 10
 # from-stdin =
 
 # Files or directories to be skipped. They should be base names, not paths.
-ignore = ["CVS"]
+ignore = ["CVS", "conftest.py"]
 
 # Add files or directories matching the regular expressions patterns to the
 # ignore-list. The regex matches against paths and can be in Posix or Windows

xclim/analog.py

@@ -458,7 +458,7 @@ def pivot(x, y):
 
         return np.max(np.abs(cx - cy))
 
-    return max(pivot(x, y), pivot(y, x))
+    return max(pivot(x, y), pivot(y, x))  # pylint: disable=arguments-out-of-order
 
 
 @metric

xclim/core/calendar.py

@@ -1398,7 +1398,8 @@ def stack_periods(
         If ``stride`` is a divisor of ``window``, the correct timeseries can be reconstructed with :py:func:`unstack_periods`.
         The coordinate of `period` is the first timestep of each window.
     """
-    from xclim.core.units import (  # Import in function to avoid cyclical imports
+    # Import in function to avoid cyclical imports
+    from xclim.core.units import (  # pylint: disable=import-outside-toplevel
         ensure_cf_units,
         infer_sampling_units,
     )
@@ -1575,7 +1576,7 @@ def unstack_periods(da: xr.DataArray | xr.Dataset, dim: str = "period"):
          0   o   o   o   x   x
         === === === === === === === ===
     """
-    from xclim.core.units import infer_sampling_units
+    from xclim.core.units import infer_sampling_units  # pylint: disable=import-outside-toplevel
 
     try:
         starts = da[dim]

xclim/core/indicator.py

@@ -1631,7 +1631,7 @@ def build_indicator_module(
     ModuleType
         A indicator module built from a mapping of Indicators.
     """
-    from xclim import indicators
+    from xclim import indicators  # pylint: disable=import-outside-toplevel
 
     out: ModuleType
     if hasattr(indicators, name):

xclim/core/locales.py

@@ -80,17 +80,15 @@ def _valid_locales(locales):
     if isinstance(locales, str):
         return True
     return all(
-        [
-            # A locale is valid if it is a string from the list
-            (isinstance(locale, str) and locale in _LOCALES)
-            or (
-                # Or if it is a tuple of a string and either a file or a dict.
-                not isinstance(locale, str)
-                and isinstance(locale[0], str)
-                and (isinstance(locale[1], dict) or Path(locale[1]).is_file())
-            )
-            for locale in locales
-        ]
+        # A locale is valid if it is a string from the list
+        (isinstance(locale, str) and locale in _LOCALES)
+        or (
+            # Or if it is a tuple of a string and either a file or a dict.
+            not isinstance(locale, str)
+            and isinstance(locale[0], str)
+            and (isinstance(locale[1], dict) or Path(locale[1]).is_file())
+        )
+        for locale in locales
     )
 
 

xclim/core/units.py

@@ -336,10 +336,8 @@ def convert_units_to(  # noqa: C901
                 for direction, sign in [("to", 1), ("from", -1)]:
                     # If the dimensionality diff is compatible with this conversion
                     compatible = all(
-                        [
-                            dimdiff == (sign * dim_order_diff.get(f"[{dim}]"))
-                            for dim, dimdiff in convconf["dimensionality"].items()
-                        ]
+                        dimdiff == sign * dim_order_diff.get(f"[{dim}]")
+                        for dim, dimdiff in convconf["dimensionality"].items()
                     )
                     # Does the input cf standard name have an equivalent after conversion
                     valid = cf_conversion(standard_name, convname, direction)
@@ -372,9 +370,7 @@ def convert_units_to(  # noqa: C901
     raise NotImplementedError(f"Source of type `{type(source)}` is not supported.")
 
 
-def cf_conversion(
-    standard_name: str, conversion: str, direction: Literal["to", "from"]
-) -> str | None:
+def cf_conversion(standard_name: str, conversion: str, direction: str) -> str | None:
     """Get the standard name of the specific conversion for the given standard name.
 
     Parameters

xclim/indicators/land/_streamflow.py

@@ -22,6 +22,7 @@ class Streamflow(ResamplingIndicator):
     src_freq = "D"
     keywords = "streamflow hydrology"
 
+    # TODO: TJS: The signature of this method seems wrong. Should it be `def cfcheck(cls, q):` or something else? Is it a static method?
     @staticmethod
     def cfcheck(q):
         check_valid(q, "standard_name", "water_volume_transport_in_river_channel")

xclim/indices/_agro.py

@@ -662,12 +662,12 @@ def dryness_index(
     adjustment_array_north = xarray.DataArray(
         [0, 0, 0, 0.1, 0.3, 0.5, 0.5, 0.5, 0.5, 0, 0, 0],
         dims="month",
-        coords=dict(month=np.arange(1, 13)),
+        coords={"month": np.arange(1, 13)},
     )
     adjustment_array_south = xarray.DataArray(
         [0.5, 0.5, 0.5, 0, 0, 0, 0, 0, 0, 0.1, 0.3, 0.5],
         dims="month",
-        coords=dict(month=np.arange(1, 13)),
+        coords={"month": np.arange(1, 13)},
     )
 
     has_north, has_south = False, False

xclim/indices/_conversion.py

@@ -5,7 +5,7 @@
 
 import numpy as np
 import xarray as xr
-from numba import float32, float64, vectorize  # noqa
+from numba import vectorize
 
 from xclim.core.units import (
     amount2rate,
@@ -1584,12 +1584,7 @@ def potential_evapotranspiration(
     return out
 
 
-@vectorize(
-    # [
-    #     float64(float64, float64, float64, float64),
-    #     float32(float32, float32, float32, float32),
-    # ],
-)
+@vectorize
 def _utci(tas, sfcWind, dt, wvp):
     """Return the empirical polynomial function for UTCI. See :py:func:`universal_thermal_climate_index`."""
     # Taken directly from the original Fortran code by Peter Bröde.

xclim/indices/fire/_cffwis.py

@@ -417,10 +417,9 @@ def _drought_code(  # pragma: no cover
     """
     fl = _day_length_factor(lat, mth)  # type: ignore
 
-    if t < -2.8:
-        t = -2.8  # type: ignore
+    t = max(t, -2.8)  # type: ignore
     pe = (0.36 * (t + 2.8) + fl) / 2  # *Eq.22*#
-    pe = max(pe, 0.0)
+    pe = max(pe, 0.0)  # type: ignore
 
     if p > 2.8:
         ra = p
@@ -1074,7 +1073,7 @@ def fire_weather_ufunc(  # noqa: C901
 
     # Verification of all arguments
     for i, (arg, name, usedby, has_time_dim) in enumerate(needed_args):
-        if any([ind in indexes + [season_method] for ind in usedby]):
+        if any(ind in indexes + [season_method] for ind in usedby):
             if arg is None:
                 raise TypeError(
                     f"Missing input argument {name} for index combination {indexes} "
@@ -1172,7 +1171,8 @@ def fire_weather_ufunc(  # noqa: C901
 
     if len(outputs) == 1:
         return {outputs[0]: das}
-    return {name: da for name, da in zip(outputs, das)}
+
+    return dict(zip(outputs, das))
 
 
 @declare_units(last_dc="[]", winter_pr="[length]")
@@ -1644,14 +1644,14 @@ def fire_season(
     ):
         raise ValueError("Thresholds must be scalar.")
 
-    kwargs = dict(
-        method=method,
-        temp_start_thresh=convert_units_to(temp_start_thresh, "degC"),
-        temp_end_thresh=convert_units_to(temp_end_thresh, "degC"),
-        temp_condition_days=temp_condition_days,
-        snow_condition_days=snow_condition_days,
-        snow_thresh=convert_units_to(snow_thresh, "m"),
-    )
+    kwargs = {
+        "method": method,
+        "temp_start_thresh": convert_units_to(temp_start_thresh, "degC"),
+        "temp_end_thresh": convert_units_to(temp_end_thresh, "degC"),
+        "temp_condition_days": temp_condition_days,
+        "snow_condition_days": snow_condition_days,
+        "snow_thresh": convert_units_to(snow_thresh, "m"),
+    }
 
     def _apply_fire_season(ds, **kwargs):
         season_mask = ds.tas.copy(

xclim/indices/fire/_ffdi.py

@@ -172,8 +172,7 @@ def _griffiths_drought_factor(p, smd, lim, df):  # pragma: no cover
                 dflim = 9.0
             else:
                 dflim = 10.0
-            if dfw > dflim:
-                dfw = dflim
+            dfw = min(dfw, dflim)
 
         dfw = min(dfw, 10.0)
 

xclim/indices/generic.py

@@ -90,9 +90,8 @@ def select_resample_op(
     """
     da = select_time(da, **indexer)
     r = da.resample(time=freq)
-    if op in _xclim_ops:
-        op = _xclim_ops[op]
     if isinstance(op, str):
+        op = _xclim_ops.get(op, op)
         out = getattr(r, op.replace("integral", "sum"))(dim="time", keep_attrs=True)
     else:
         with xr.set_options(keep_attrs=True):

xclim/indices/helpers.py

@@ -153,7 +153,9 @@ def time_correction_for_solar_angle(time: xr.DataArray) -> xr.DataArray:
     return _wrap_radians(convert_units_to(tc, "rad"))
 
 
-def eccentricity_correction_factor(time: xr.DataArray, method="spencer"):
+def eccentricity_correction_factor(
+    time: xr.DataArray, method: str = "spencer"
+) -> xr.DataArray:
     """Eccentricity correction factor of the Earth's orbit.
 
     The squared ratio of the mean distance Earth-Sun to the distance at a specific moment.
@@ -163,9 +165,10 @@ def eccentricity_correction_factor(time: xr.DataArray, method="spencer"):
     ----------
     time: xr.DataArray
         Time coordinate
-    method : str
-        Which approximation to use. The default ("spencer") uses the first five terms of the fourier series of the
-        eccentricity, while "simple" approximates with only the first two.
+    method : {'spencer', 'simple'}
+        Which approximation to use.
+        The default ("spencer") uses the first five terms of the fourier series of the eccentricity.
+        The "simple" method approximates with only the first two.
 
     Returns
     -------
@@ -191,6 +194,7 @@ def eccentricity_correction_factor(time: xr.DataArray, method="spencer"):
             + 0.000719 * np.cos(2 * da)
             + 0.000077 * np.sin(2 * da)
         )
+    raise NotImplementedError("Method must be one of 'simple' or 'spencer'.")
 
 
 def cosine_of_solar_zenith_angle(

xclim/indices/stats.py

@@ -133,13 +133,13 @@ def fit(
         dask="parallelized",
         output_dtypes=[float],
         keep_attrs=True,
-        kwargs=dict(
+        kwargs={
             # Don't know how APP should be included, this works for now
-            dist=dist,
-            nparams=len(dist_params),
-            method=method,
+            "dist": dist,
+            "nparams": len(dist_params),
+            "method": method,
             **fitkwargs,
-        ),
+        },
         dask_gufunc_kwargs={"output_sizes": {"dparams": len(dist_params)}},
     )
 

xclim/sdba/base.py

@@ -226,7 +226,9 @@ def group(
         They are broadcast, merged to the grouping dataset and regrouped in the output.
         """
         if das:
-            from .utils import broadcast  # pylint: disable=cyclic-import
+            from .utils import (  # pylint: disable=cyclic-import,import-outside-toplevel
+                broadcast,
+            )
 
             if da is not None:
                 das[da.name] = da

xclim/sdba/properties.py

@@ -99,7 +99,9 @@ def _postprocess(self, outs, das, params):
 
     def get_measure(self):
         """Get the statistical measure indicator that is best used with this statistical property."""
-        from xclim.core.indicator import registry
+        from xclim.core.indicator import (  # pylint: disable=import-outside-toplevel
+            registry,
+        )
 
         return registry[self.measure].get_instance()
 
@@ -354,7 +356,7 @@ def _spell_stats(
         stat_resample,
     ):
         # PB: This prevents an import error in the distributed dask scheduler, but I don't know why.
-        import xarray.core.resample_cftime  # noqa: F401, pylint: disable=unused-import
+        import xarray.core.resample_cftime  # noqa: F401, pylint: disable=unused-import,import-outside-toplevel
 
         da = ds.data
         mask = ~(da.isel({dim: 0}).isnull()).drop_vars(
@@ -906,7 +908,7 @@ def _bivariate_spell_stats(
         stat_resample,
     ):
         # PB: This prevents an import error in the distributed dask scheduler, but I don't know why.
-        import xarray.core.resample_cftime  # noqa: F401, pylint: disable=unused-import
+        import xarray.core.resample_cftime  # noqa: F401, pylint: disable=unused-import,import-outside-toplevel
 
         conds = []
         masks = []

xclim/sdba/utils.py

@@ -1027,12 +1027,12 @@ def optimal_transport(gridX, gridY, muX, muY, numItermax, transform):
     :cite:cts:`sdba-robin_2021`
     """
     try:
-        from ot import emd  # noqa
-    except ImportError:
+        from ot import emd  # pylint: disable=import-outside-toplevel
+    except ImportError as e:
         raise ImportError(
-            "The optional dependency `ot` is required for optimal_transport. "
-            "You can install it with `pip install pot` or `pip install 'xclim[extras]'`."
-        )
+            "The optional dependency `POT` is required for optimal_transport. "
+            "You can install it with `pip install POT` or `pip install 'xclim[extras]'`."
+        ) from e
 
     if transform == "standardize":
         gridX = (gridX - gridX.mean()) / gridX.std()