MNT: Fix or ignore issues raised by pyright. [skip ci]

pydaymet/cli.py

@@ -8,7 +8,7 @@
 import click
 import geopandas as gpd
 import pandas as pd
-import shapely.geometry as sgeom
+import shapely
 
 from pydaymet import pydaymet as daymet
 from pydaymet.exceptions import (
@@ -43,7 +43,7 @@ def get_target_df(tdf: DFType, req_cols: list[str]) -> DFType:
     missing = [c for c in req_cols if c not in tdf]
     if missing:
         raise MissingItemError(missing)
-    return tdf[req_cols]  # pyright: ignore[reportGeneralTypeIssues]
+    return tdf[req_cols]  # pyright: ignore[reportReturnType]
 
 
 def get_required_cols(geom_type: str, columns: pd.Index) -> list[str]:
@@ -55,9 +55,9 @@ def get_required_cols(geom_type: str, columns: pd.Index) -> list[str]:
 def _get_region(gid: str, geom: Polygon | MultiPolygon | Point) -> str:
     """Get the Daymer region of an input geometry (point or polygon)."""
     region_bbox = {
-        "na": sgeom.box(-136.8989, 6.0761, -6.1376, 69.077),
-        "hi": sgeom.box(-160.3055, 17.9539, -154.7715, 23.5186),
-        "pr": sgeom.box(-67.9927, 16.8443, -64.1195, 19.9381),
+        "na": shapely.box(-136.8989, 6.0761, -6.1376, 69.077),
+        "hi": shapely.box(-160.3055, 17.9539, -154.7715, 23.5186),
+        "pr": shapely.box(-67.9927, 16.8443, -64.1195, 19.9381),
     }
     for region, bbox in region_bbox.items():
         if bbox.contains(geom):

pydaymet/core.py

@@ -11,7 +11,7 @@
 import numpy as np
 import numpy.typing as npt
 import pandas as pd
-import shapely.geometry as sgeom
+import shapely
 import xarray as xr
 
 from pydaymet.exceptions import InputRangeError, InputTypeError, InputValueError
@@ -21,8 +21,8 @@
     from numba import config as numba_config
     from numba import jit, prange
 
-    ngjit = functools.partial(jit, nopython=True, nogil=True)
-    numba_config.THREADING_LAYER = "workqueue"
+    ngjit = functools.partial(jit, nopython=True, nogil=True)  # pyright: ignore[reportAssignmentType]
+    numba_config.THREADING_LAYER = "workqueue"  # pyright: ignore[reportAttributeAccessIssue]
     has_numba = True
 except ImportError:
     has_numba = False
@@ -206,9 +206,9 @@ def __init__(
         self.snow = validated.snow
 
         self.region_bbox = {
-            "na": sgeom.box(-136.8989, 6.0761, -6.1376, 69.077),
-            "hi": sgeom.box(-160.3055, 17.9539, -154.7715, 23.5186),
-            "pr": sgeom.box(-67.9927, 16.8443, -64.1195, 19.9381),
+            "na": shapely.box(-136.8989, 6.0761, -6.1376, 69.077),
+            "hi": shapely.box(-160.3055, 17.9539, -154.7715, 23.5186),
+            "pr": shapely.box(-67.9927, 16.8443, -64.1195, 19.9381),
         }
         if self.region == "pr":
             self.valid_start = pd.to_datetime("1950-01-01")
@@ -366,7 +366,7 @@ def dates_tolist(self, dates: tuple[str, str]) -> list[tuple[pd.Timestamp, pd.Ti
         lp = period[(period.is_leap_year) & (~period.strftime(DATE_FMT).str.endswith("12-31"))]
         _period = period[(period.isin(nl)) | (period.isin(lp))]
         years = [_period[_period.year == y] for y in _period.year.unique()]
-        return [(y[0], y[-1]) for y in years]
+        return [(y[0], y[-1]) for y in years]  # pyright: ignore[reportReturnType]
 
     def years_tolist(self, years: list[int] | int) -> list[tuple[pd.Timestamp, pd.Timestamp]]:
         """Correct dates for Daymet accounting for leap years.

pydaymet/pet.py

@@ -1,5 +1,5 @@
 """Core class for the Daymet functions."""
-# pyright: reportGeneralTypeIssues=false
+# pyright: reportReturnType=false,reportArgumentType=false
 from __future__ import annotations
 
 from dataclasses import dataclass, fields
@@ -28,6 +28,7 @@
     CRSTYPE = Union[int, str, CRS]
     DF = TypeVar("DF", pd.DataFrame, xr.Dataset)
     DS = TypeVar("DS", pd.Series, xr.DataArray)
+    PET_METHODS = Literal["penman_monteith", "priestley_taylor", "hargreaves_samani"]
 
 __all__ = ["potential_et"]
 
@@ -333,7 +334,7 @@ def __init__(
         self,
         clm: pd.DataFrame,
         coords: tuple[float, float],
-        method: str,
+        method: PET_METHODS,
         crs: CRSTYPE = 4326,
         params: dict[str, float] | None = None,
     ) -> None:
@@ -415,11 +416,11 @@ def penman_monteith(self) -> pd.DataFrame:
         )
 
         # recommended when no data is not available to estimate wind speed
-        u_2m = self.clm[self.u2m] if self.u2m in self.clm else 2.0
+        u_2m = self.clm.get(self.u2m, 2.0)
         self.clm["pet (mm/day)"] = (
             0.408 * vp_slope * (rad_n - self.params.soil_heat_flux)
             + gamma * 900.0 / (self.tmean + 273.0) * u_2m * (e_s - e_a)
-        ) / (vp_slope + gamma * (1 + 0.34 * u_2m))
+        ) / (vp_slope + gamma * (1 + 0.34 * u_2m))  # pyright: ignore[reportOperatorIssue]
 
         return self.clm
 
@@ -525,7 +526,7 @@ class PETGridded:
     def __init__(
         self,
         clm: xr.Dataset,
-        method: str,
+        method: PET_METHODS,
         params: dict[str, float] | None = None,
     ) -> None:
         self.clm = clm.copy()
@@ -640,7 +641,7 @@ def penman_monteith(self) -> xr.Dataset:
         )
 
         # recommended when no data is not available to estimate wind speed
-        u_2m = self.clm["u2m"] if "u2m" in self.clm_vars else 2.0
+        u_2m = self.clm.get("u2m", 2.0)
         self.clm["pet"] = (
             0.408 * self.clm["vp_slope"] * (self.clm["rad_n"] - self.params.soil_heat_flux)
             + self.clm["gamma"]

pydaymet/pydaymet.py

@@ -1,5 +1,5 @@
 """Access the Daymet database for both single single pixel and gridded queries."""
-# pyright: reportGeneralTypeIssues=false
+# pyright: reportArgumentType=false,reportCallIssue=false,reportReturnType=false
 from __future__ import annotations
 
 import functools
@@ -28,6 +28,7 @@
     from shapely import MultiPolygon, Polygon
 
     CRSTYPE = Union[int, str, pyproj.CRS]
+    PET_METHODS = Literal["penman_monteith", "priestley_taylor", "hargreaves_samani"]
 
 DATE_FMT = "%Y-%m-%dT%H:%M:%SZ"
 MAX_CONN = 10
@@ -131,7 +132,7 @@ def _by_coord(
     daymet: Daymet,
     time_scale: str,
     dates: list[tuple[pd.Timestamp, pd.Timestamp]],
-    pet: str | None,
+    pet: PET_METHODS | None,
     pet_params: dict[str, float] | None,
     snow: bool,
     snow_params: dict[str, float] | None,
@@ -181,7 +182,7 @@ def get_bycoords(
     | None = None,
     region: Literal["na", "hi", "pr"] = "na",
     time_scale: Literal["daily", "monthly", "annual"] = "daily",
-    pet: Literal["penman_monteith", "priestley_taylor", "hargreaves_samani"] | None = None,
+    pet: PET_METHODS | None = None,
     pet_params: dict[str, float] | None = None,
     snow: bool = False,
     snow_params: dict[str, float] | None = None,
@@ -407,7 +408,7 @@ def get_bygeom(
     | None = None,
     region: Literal["na", "hi", "pr"] = "na",
     time_scale: Literal["daily", "monthly", "annual"] = "daily",
-    pet: Literal["penman_monteith", "priestley_taylor", "hargreaves_samani"] | None = None,
+    pet: PET_METHODS | None = None,
     pet_params: dict[str, float] | None = None,
     snow: bool = False,
     snow_params: dict[str, float] | None = None,
@@ -589,7 +590,7 @@ def get_bystac(
     region: Literal["na", "hi", "pr"] = "na",
     time_scale: Literal["daily", "monthly", "annual"] = "daily",
     res_km: int = 1,
-    pet: Literal["penman_monteith", "priestley_taylor", "hargreaves_samani"] | None = None,
+    pet: PET_METHODS | None = None,
     pet_params: dict[str, float] | None = None,
     snow: bool = False,
     snow_params: dict[str, float] | None = None,