black format file

Author: jedwards4b

.pre-commit-config.yaml

@@ -0,0 +1,17 @@
+exclude: ^utils/.*$
+
+repos:
+  - repo: https://github.com/pre-commit/pre-commit-hooks
+    rev: v6.0.0
+    hooks:
+      - id: end-of-file-fixer
+      - id: trailing-whitespace
+      - id: debug-statements
+  - repo: https://github.com/psf/black
+    rev: 25.9.0
+    hooks:
+      - id: black
+  - repo: https://github.com/PyCQA/pylint
+    rev: v3.3.8
+    hooks:
+      - id: pylint

.pylintrc

@@ -15,5 +15,5 @@ disable=
 max-line-length=100
 
 [TYPECHECK]
-ignored-modules=xarray,xesmf,cmor,numpy,geocat.comp
+ignored-modules=xarray,xesmf,cmor,numpy,geocat.comp,yaml
 ignored-classes=cmor

README.md

@@ -2,7 +2,7 @@
 # cmip7-prep (skeleton)
 
 Quickstart:
-1) Ensure you have a precomputed E3SM weights file: `map_ne30pg3_to_1x1d_aave.nc`.
+1) Ensure you have a precomputed ESMF weights file: `map_ne30pg3_to_1x1d_aave.nc`.
 2) Fill in `cmor_dataset.json` placeholders (experiment_id, etc.).
 3) Export the CMIP7 Data Request v1.2.2 (CSV) as `data_request_v1.2.2.csv`.
 4) `poetry install`

cmip7_prep/mapping_compat.py

@@ -1,4 +1,3 @@
-
 # cmip7_prep/mapping_compat.py
 r"""Mapping loader/evaluator compatible with CMIP6-style lists and CMIP7-style dicts.
 
@@ -48,6 +47,7 @@ def _normalize_table_name(value: Optional[str]) -> Optional[str]:
 @dataclass(frozen=True)
 class VarConfig:
     """Normalized mapping entry for a single CMIP variable."""
+
     name: str
     table: Optional[str] = None
     units: Optional[str] = None
@@ -110,6 +110,7 @@ class Mapping:
     The loader accepts both dict- and list-based YAML styles. All table names
     are normalized to a short form (e.g., 'Amon').
     """
+
     def __init__(self, path: str | Path) -> None:
         self.path = Path(path)
         self._vars: Dict[str, VarConfig] = self._load_yaml(self.path)
@@ -138,7 +139,9 @@ def _load_yaml(path: Path) -> Dict[str, VarConfig]:
                 name = str(item["name"])
                 result[name] = _to_varconfig(name, item)
         else:
-            raise TypeError("Unsupported YAML structure: expected dict or list at top level.")
+            raise TypeError(
+                "Unsupported YAML structure: expected dict or list at top level."
+            )
 
         return result
 
@@ -208,7 +211,9 @@ def _to_varconfig(name: str, cfg: TMapping[str, Any]) -> VarConfig:
     return vc
 
 
-def _require_vars(ds: xr.Dataset, names: List[str], context: str) -> Dict[str, xr.DataArray]:
+def _require_vars(
+    ds: xr.Dataset, names: List[str], context: str
+) -> Dict[str, xr.DataArray]:
     missing = [n for n in names if n not in ds]
     if missing:
         raise KeyError(f"{context}: missing variables {missing}")
@@ -224,7 +229,11 @@ def _realize_core(ds: xr.Dataset, vc: VarConfig) -> xr.DataArray:
         return ds[vc.source]
 
     # 2) identity mapping from a single raw variable
-    if vc.raw_variables and vc.formula in (None, "", "null") and len(vc.raw_variables) == 1:
+    if (
+        vc.raw_variables
+        and vc.formula in (None, "", "null")
+        and len(vc.raw_variables) == 1
+    ):
         var = vc.raw_variables[0]
         if var not in ds:
             raise KeyError(f"raw variable {var!r} not found in dataset")
@@ -263,7 +272,9 @@ def _apply_unit_conversion(da: xr.DataArray, rule: Any) -> xr.DataArray:
         try:
             out = _safe_eval(rule, {"x": da})
         except Exception as exc:
-            raise ValueError(f"Error evaluating unit_conversion expression: {exc}") from exc
+            raise ValueError(
+                f"Error evaluating unit_conversion expression: {exc}"
+            ) from exc
         if not isinstance(out, xr.DataArray):
             raise ValueError("unit_conversion expression did not return a DataArray")
         return out
@@ -273,4 +284,6 @@ def _apply_unit_conversion(da: xr.DataArray, rule: Any) -> xr.DataArray:
         offset = rule.get("offset", 0.0)
         return da * float(scale) + float(offset)
 
-    raise TypeError("unit_conversion must be a string expression or a dict with 'scale'/'offset'")
+    raise TypeError(
+        "unit_conversion must be a string expression or a dict with 'scale'/'offset'"
+    )