Validate YAML file using schema before constructing module. (#1560)

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### Pull Request Checklist:
- [x] This PR addresses an already opened issue (for bug fixes /
features)
    - This PR fixes #1523
- [ ] Tests for the changes have been added (for bug fixes / features)
- [ ] (If applicable) Documentation has been added / updated (for bug
fixes / features)
- [x] CHANGES.rst has been updated (with summary of main changes)
- [ ] Link to issue (:issue:`number`) and pull request (:pull:`number`)
has been added

### What kind of change does this PR introduce?

* Use Yamale to validate schema before constructing module. Good news,
no error found in the test suite.

### Does this PR introduce a breaking change?


### Other information:

There was an issue raised by @tlogan2000 about indicators accepting
wrong arguments without failing. Could you post an offending example ?

CHANGES.rst

@@ -2,14 +2,15 @@
 Changelog
 =========
 
-
 v0.48 (unreleased)
 ------------------
 Contributors to this version: Juliette Lavoie (:user:`juliettelavoie`), Pascal Bourgault (:user:`aulemahal`), Trevor James Smith (:user:`Zeitsperre`), David Huard (:user:`huard`), Éric Dupuis (:user:`coxipi`).
 
 New features and enhancements
 ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
 * Added uncertainty partitioning method `lafferty_sriver` from Lafferty and Sriver (2023), which can partition uncertainty related to the downscaling method. (:issue:`1497`, :pull:`1529`).
+* Validate YAML indicators description before trying to build module. (:issue:`1523`, :pull:`1560`).
+
 
 
 v0.47.0 (2023-12-01)

docs/notebooks/extendxclim.ipynb

@@ -397,26 +397,15 @@
     "\n",
     "\n",
     "#### Validation of the YAML file\n",
-    "Using [yamale](https://github.com/23andMe/Yamale), it is possible to check if the YAML file is valid. `xclim` ships with a schema (in `xclim/data/schema.yml`) file. The file can be located with:"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": null,
-   "metadata": {},
-   "outputs": [],
-   "source": [
-    "from importlib.resources import path\n",
     "\n",
-    "with path(\"xclim.data\", \"schema.yml\") as f:\n",
-    "    print(f)"
+    "Using [yamale](https://github.com/23andMe/Yamale), it is possible to check if the YAML file is valid. `xclim` ships with a schema (in `xclim/data/schema.yml`) file. "
    ]
   },
   {
    "cell_type": "markdown",
    "metadata": {},
    "source": [
-    "And the validation can be executed either in a python session:"
+    "The validation can be executed in a python session:"
    ]
   },
   {
@@ -425,6 +414,8 @@
    "metadata": {},
    "outputs": [],
    "source": [
+    "from importlib.resources import path\n",
+    "\n",
     "import yamale\n",
     "\n",
     "with path(\"xclim.data\", \"schema.yml\") as f:\n",
@@ -437,13 +428,15 @@
    "cell_type": "markdown",
    "metadata": {},
    "source": [
-    "No errors means it passed. The validation can also be run through the command line with:\n",
+    "Or the validation can alternatively be run from the command line with:\n",
     "\n",
     "```bash\n",
     "yamale -s path/to/schema.yml path/to/module.yml\n",
     "```\n",
     "\n",
-    "#### Loading the module and computating of the indices."
+    "Note that xclim builds indicators from a yaml file, as shown in the next example, it validates it first. \n",
+    "\n",
+    "#### Loading the module and computing indicators."
    ]
   },
   {

tests/test_modules.py

@@ -61,12 +61,6 @@ def test_custom_indices(open_dataset):
     # Use the example data used in the Extending Xclim notebook for testing.
     example_path = Path(__file__).parent.parent / "docs" / "notebooks" / "example"
 
-    schema = yamale.make_schema(
-        Path(__file__).parent.parent / "xclim" / "data" / "schema.yml"
-    )
-    data = yamale.make_data(example_path / "example.yml")
-    yamale.validate(schema, data)
-
     pr = open_dataset("ERA5/daily_surface_cancities_1990-1993.nc").pr
 
     # This tests load_module with a python file that is _not_ on the PATH

xclim/core/indicator.py

@@ -85,8 +85,8 @@
 In the following, the section under `<identifier>` is referred to as `data`. When creating indicators from
 a dictionary, with :py:meth:`Indicator.from_dict`, the input dict must follow the same structure of `data`.
 
-The resulting yaml file can be validated using the provided schema (in xclim/data/schema.yml)
-and the YAMALE tool :cite:p:`lopker_yamale_2022`. See the "Extending xclim" notebook for more info.
+When a module is built from a yaml file, the yaml is first validated against the schema (see xclim/data/schema.yml)
+using the YAMALE library (:cite:p:`lopker_yamale_2022`). See the "Extending xclim" notebook for more info.
 
 Inputs
 ~~~~~~
@@ -115,6 +115,7 @@
 
 import numpy as np
 import xarray
+import yamale
 from xarray import DataArray, Dataset
 from yaml import safe_load
 
@@ -1716,6 +1717,14 @@ def build_indicator_module_from_yaml(  # noqa: C901
     with ymlpath.open(encoding=encoding) as f:
         yml = safe_load(f)
 
+    # Read schema
+    schema = yamale.make_schema(Path(__file__).parent.parent / "data" / "schema.yml")
+
+    # Validate - a YamaleError will be raised if the module does not comply with the schema.
+    yamale.validate(
+        schema, yamale.make_data(content=ymlpath.read_text(encoding=encoding))
+    )
+
     # Load values from top-level in yml.
     # Priority of arguments differ.
     module_name = name or yml.get("module", filepath.stem)