Revise use cache

.cruft.json

@@ -1,6 +1,6 @@
 {
   "template": "https://github.com/ecmwf-projects/cookiecutter-conda-package",
-  "commit": "46c5959d066cde32a3f39e51474fe8a058de4860",
+  "commit": "308afb845f02bf8e5e5af2bab993f9fc472aa04d",
   "checkout": null,
   "context": {
     "cookiecutter": {

.github/workflows/on-push.yml

@@ -22,7 +22,7 @@ jobs:
   pre-commit:
     runs-on: ubuntu-latest
     steps:
-    - uses: actions/checkout@v3
+    - uses: actions/checkout@v4
     - uses: actions/setup-python@v4
       with:
         python-version: 3.x
@@ -32,7 +32,7 @@ jobs:
     runs-on: ubuntu-latest
 
     steps:
-    - uses: actions/checkout@v3
+    - uses: actions/checkout@v4
     - name: Install conda-merge
       run: |
         $CONDA/bin/python -m pip install conda-merge
@@ -56,7 +56,7 @@ jobs:
         python-version: ['3.10', '3.11']
 
     steps:
-    - uses: actions/checkout@v3
+    - uses: actions/checkout@v4
     - name: Download combined environments
       uses: actions/download-artifact@v3
       with:
@@ -82,7 +82,7 @@ jobs:
     runs-on: ubuntu-latest
 
     steps:
-    - uses: actions/checkout@v3
+    - uses: actions/checkout@v4
     - name: Download combined environments
       uses: actions/download-artifact@v3
       with:
@@ -108,7 +108,7 @@ jobs:
     runs-on: ubuntu-latest
 
     steps:
-    - uses: actions/checkout@v3
+    - uses: actions/checkout@v4
     - name: Download combined environments
       uses: actions/download-artifact@v3
       with:
@@ -142,7 +142,7 @@ jobs:
           extra: -integration
 
     steps:
-    - uses: actions/checkout@v3
+    - uses: actions/checkout@v4
     - name: Download combined environments
       uses: actions/download-artifact@v3
       with:
@@ -174,7 +174,7 @@ jobs:
       (needs.integration-tests.result == 'success' || needs.integration-tests.result == 'skipped')
 
     steps:
-    - uses: actions/checkout@v3
+    - uses: actions/checkout@v4
     - name: Install packages
       run: |
         $CONDA/bin/python -m pip install build twine

.pre-commit-config.yaml

@@ -11,7 +11,7 @@ repos:
   - id: debug-statements
   - id: mixed-line-ending
 - repo: https://github.com/psf/black
-  rev: 23.7.0
+  rev: 23.9.1
   hooks:
   - id: black
 - repo: https://github.com/keewis/blackdoc
@@ -20,12 +20,12 @@ repos:
   - id: blackdoc
     additional_dependencies: [black==22.3.0]
 - repo: https://github.com/astral-sh/ruff-pre-commit
-  rev: v0.0.280
+  rev: v0.0.290
   hooks:
   - id: ruff
     args: [--fix, --show-fixes]
 - repo: https://github.com/executablebooks/mdformat
-  rev: 0.7.16
+  rev: 0.7.17
   hooks:
   - id: mdformat
 - repo: https://github.com/macisamuele/language-formatters-pre-commit-hooks
@@ -36,6 +36,6 @@ repos:
   - id: pretty-format-toml
     args: [--autofix]
 - repo: https://github.com/gitleaks/gitleaks
-  rev: v8.17.0
+  rev: v8.18.0
   hooks:
   - id: gitleaks

c3s_eqc_automatic_quality_control/download.py

@@ -292,7 +292,7 @@ def ensure_request_gets_cached(request: dict[str, Any]) -> dict[str, Any]:
 
 
 def _cached_retrieve(collection_id: str, request: dict[str, Any]) -> emohawk.Data:
-    with cacholote.config.set(use_cache=True, return_cache_entry=False):
+    with cacholote.config.set(return_cache_entry=False):
         return cads_toolbox.catalogue.retrieve(collection_id, request).data
 
 
@@ -401,7 +401,6 @@ def get_data(source: list[str]) -> Any:
     return emohwak_dir
 
 
-@cacholote.cacheable
 def _download_and_transform_requests(
     collection_id: str,
     request_list: list[dict[str, Any]],
@@ -525,8 +524,11 @@ def download_and_transform(
         else cached_open_mfdataset_kwargs or {}
     )
 
+    use_cache = transform_func is not None
     func = functools.partial(
-        _download_and_transform_requests,
+        cacholote.cacheable(_download_and_transform_requests)
+        if use_cache
+        else _download_and_transform_requests,
         collection_id=collection_id,
         transform_func=transform_func,
         transform_func_kwargs=transform_func_kwargs,
@@ -544,28 +546,24 @@ def download_and_transform(
             for request in request_list
         )
 
-    use_cache = transform_func is not None
-    with cacholote.config.set(use_cache=use_cache):
-        if use_cache and transform_chunks:
-            # Cache each chunk transformed
-            sources = []
-            for request in tqdm.tqdm(request_list):
-                if invalidate_cache:
-                    cacholote.delete(
-                        func.func, *func.args, request_list=[request], **func.keywords
-                    )
-                with cacholote.config.set(return_cache_entry=True):
-                    sources.append(
-                        func(request_list=[request]).result["args"][0]["href"]
-                    )
-            ds = xr.open_mfdataset(sources, **cached_open_mfdataset_kwargs)
-        else:
-            # Cache final dataset transformed
+    if use_cache and transform_chunks:
+        # Cache each chunk transformed
+        sources = []
+        for request in tqdm.tqdm(request_list):
             if invalidate_cache:
                 cacholote.delete(
-                    func.func, *func.args, request_list=request_list, **func.keywords
+                    func.func, *func.args, request_list=[request], **func.keywords
                 )
-            ds = func(request_list=request_list)
+            with cacholote.config.set(return_cache_entry=True):
+                sources.append(func(request_list=[request]).result["args"][0]["href"])
+        ds = xr.open_mfdataset(sources, **cached_open_mfdataset_kwargs)
+    else:
+        # Cache final dataset transformed
+        if invalidate_cache:
+            cacholote.delete(
+                func.func, *func.args, request_list=request_list, **func.keywords
+            )
+        ds = func(request_list=request_list)
 
     ds.attrs.pop("coordinates", None)  # Previously added to guarantee roundtrip
     return ds

c3s_eqc_automatic_quality_control/plot.py

@@ -31,8 +31,7 @@
 import plotly.graph_objs as go
 import xarray as xr
 from cartopy.mpl.geocollection import GeoQuadMesh
-from matplotlib.axes import Axes
-from matplotlib.image import AxesImage
+from matplotlib.typing import ColorType
 from xarray.plot.facetgrid import FacetGrid
 
 from . import diagnostics, utils
@@ -43,7 +42,6 @@
 }
 
 FLAGS_T = int | Iterable[int]
-COLOR_T = str | Iterable[str]
 
 
 def line_plot(
@@ -268,7 +266,7 @@ def projected_map(
     return plot_obj
 
 
-def _infer_legend_dict(da: xr.DataArray) -> dict[str, tuple[COLOR_T, FLAGS_T]]:
+def _infer_legend_dict(da: xr.DataArray) -> dict[str, tuple[ColorType, FLAGS_T]]:
     flags = list(map(int, da.attrs["flag_values"]))
     colors = da.attrs["flag_colors"].split()
     meanings = da.attrs["flag_meanings"].split()
@@ -279,17 +277,17 @@ def _infer_legend_dict(da: xr.DataArray) -> dict[str, tuple[COLOR_T, FLAGS_T]]:
     if len(flags) - len(colors) == 1:
         colors.insert(flags.index(0), "#000000")
 
-    legend_dict: dict[str, tuple[COLOR_T, FLAGS_T]] = {}
+    legend_dict: dict[str, tuple[ColorType, FLAGS_T]] = {}
     for m, c, f in zip(meanings, colors, flags, strict=True):
         legend_dict[m.replace("_", " ").title()] = (c, f)
     return legend_dict
 
 
 def lccs_map(
     da_lccs: xr.DataArray,
-    legend_dict: dict[str, tuple[COLOR_T, FLAGS_T]] | None = None,
+    legend_dict: dict[str, tuple[ColorType, FLAGS_T]] | None = None,
     **kwargs: Any,
-) -> AxesImage | FacetGrid[Any]:
+) -> Any:
     """
     Plot LCCS map.
 
@@ -346,12 +344,12 @@ def lccs_map(
 def lccs_bar(
     da: xr.DataArray,
     da_lccs: xr.DataArray,
-    labels_dict: dict[str, tuple[COLOR_T, FLAGS_T]] | None = None,
+    labels_dict: dict[str, tuple[ColorType, FLAGS_T]] | None = None,
     reduction: str = "mean",
     groupby_bins_dims: dict[str, Any] = {},
     exclude_no_data: bool = True,
     **kwargs: Any,
-) -> Axes:
+) -> Any:
     """
     Plot LCCS map.
 
@@ -424,7 +422,7 @@ def lccs_bar(
         " ".join([reduction.title(), "of", xr.plot.utils.label_from_attrs(da)]),
     )
 
-    ax = df_or_ser.plot.bar(color=colors, **kwargs)
+    ax = df_or_ser.plot.bar(color=list(colors), **kwargs)
     if groupby_bins_dims:
         ax.legend(bbox_to_anchor=(1, 1), loc="upper left")
     return ax
@@ -456,8 +454,5 @@ def seasonal_boxplot(
 
     da = da.stack(stacked_dim=da.dims)
     df = da.to_dataframe()
-    axes = df.groupby(by=da[time_dim].dt.season.values).boxplot(**kwargs)
-    for ax in axes:
-        ax.xaxis.set_ticklabels([])
 
-    return axes
+    return df.groupby(by=da[time_dim].dt.season.values).boxplot(**kwargs)

environment.yml

@@ -23,6 +23,7 @@ dependencies:
 - numpy
 - pip
 - plotly
+- pooch
 - pydantic == 1.*
 - python-dotenv
 - pyyaml

pyproject.toml

@@ -37,7 +37,6 @@ module = [
   "emohawk.*",
   "fsspec",
   "joblib",
-  "matplotlib.*",
   "plotly.*",
   "shapely",
   "sklearn.*",
@@ -48,17 +47,7 @@ module = [
 [tool.ruff]
 ignore = [
   # pydocstyle: Missing Docstrings
-  "D1",
-  # pydocstyle: numpy convention
-  "D107",
-  "D203",
-  "D212",
-  "D213",
-  "D402",
-  "D413",
-  "D415",
-  "D416",
-  "D417"
+  "D1"
 ]
 # Black line length is 88, but black does not format comments.
 line-length = 110
@@ -77,6 +66,9 @@ select = [
 ]
 target-version = "py310"
 
+[tool.ruff.pydocstyle]
+convention = "numpy"
+
 [tool.setuptools]
 packages = ["c3s_eqc_automatic_quality_control"]