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climate_ref_core.testing #

Test infrastructure for diagnostic testing.

This module provides: - TestCase and TestDataSpecification for defining test scenarios - YAML serialization for dataset catalogs (with paths stored separately) - Utilities for CMEC bundle and series regression validation

TestCase #

A single test case for a diagnostic.

Test cases define scenarios for testing, with data resolved via: - requests: ESGF requests to fetch data (use ref test-cases fetch) - datasets_file: Path to a pre-built catalog YAML file

Source code in packages/climate-ref-core/src/climate_ref_core/testing.py 
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@frozen
class TestCase:
    """
    A single test case for a diagnostic.

    Test cases define scenarios for testing, with data resolved via:
    - `requests`: ESGF requests to fetch data (use `ref test-cases fetch`)
    - `datasets_file`: Path to a pre-built catalog YAML file
    """

    name: str
    """Name of the test case (e.g., 'default', 'short-timeseries')."""

    description: str
    """Human-readable description of what this test case covers."""

    requests: tuple[ESGFRequest, ...] | None = None
    """Optional ESGF requests to fetch data for this test case."""

    datasets_file: str | None = None
    """Path to YAML file with dataset specification (relative to package)."""

datasets_file = None class-attribute instance-attribute #

Path to YAML file with dataset specification (relative to package).

description instance-attribute #

Human-readable description of what this test case covers.

name instance-attribute #

Name of the test case (e.g., 'default', 'short-timeseries').

requests = None class-attribute instance-attribute #

Optional ESGF requests to fetch data for this test case.

TestCasePaths #

Path resolver for test case data.

Provides access to all paths within a test case directory: - catalog.yaml: Dataset metadata (tracked in git) - catalog.paths.yaml: Local file paths (gitignored) - regression/: Regression outputs (tracked in git)

Can be constructed from: - A diagnostic + test case name (auto-resolves provider's test-data dir) - An explicit test_data_dir + diagnostic slug + test case name

Source code in packages/climate-ref-core/src/climate_ref_core/testing.py 
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@frozen
class TestCasePaths:
    """
    Path resolver for test case data.

    Provides access to all paths within a test case directory:
    - catalog.yaml: Dataset metadata (tracked in git)
    - catalog.paths.yaml: Local file paths (gitignored)
    - regression/: Regression outputs (tracked in git)

    Can be constructed from:
    - A diagnostic + test case name (auto-resolves provider's test-data dir)
    - An explicit test_data_dir + diagnostic slug + test case name
    """

    root: Path
    """The test case directory (test_data_dir / diagnostic_slug / test_case_name)."""

    @classmethod
    def from_diagnostic(cls, diagnostic: Diagnostic, test_case: str) -> TestCasePaths | None:
        """
        Create from a diagnostic, auto-resolving the provider's test-data directory.

        Returns None if the provider's test-data directory cannot be determined
        (e.g., not a development checkout).

        Parameters
        ----------
        diagnostic
            The diagnostic to get paths for
        test_case
            Test case name (e.g., 'default')
        """
        test_data_dir = _get_provider_test_data_dir(diagnostic)
        if test_data_dir is None:
            return None
        return cls(root=test_data_dir / diagnostic.slug / test_case)

    @classmethod
    def from_test_data_dir(
        cls,
        test_data_dir: Path,
        diagnostic_slug: str,
        test_case: str,
    ) -> TestCasePaths:
        """
        Create from an explicit test data directory.

        Use this when you have a test_data_dir fixture (in tests) or
        know the base path explicitly.

        Parameters
        ----------
        test_data_dir
            Base test data directory (e.g., from test fixture)
        diagnostic_slug
            The diagnostic slug
        test_case
            Test case name (e.g., 'default')
        """
        return cls(root=test_data_dir / diagnostic_slug / test_case)

    @property
    def catalog(self) -> Path:
        """Path to catalog.yaml."""
        return self.root / "catalog.yaml"

    @property
    def catalog_paths(self) -> Path:
        """Path to catalog.paths.yaml (gitignored, contains local file paths)."""
        return self.root / "catalog.paths.yaml"

    @property
    def regression(self) -> Path:
        """Path to regression/ directory."""
        return self.root / "regression"

    @property
    def manifest(self) -> Path:
        """Path to manifest.json (the regression bundle manifest, tracked in git)."""
        return self.root / "manifest.json"

    @property
    def output(self) -> Path:
        """Path to the output/ directory (gitignored; holds materialised native slots)."""
        return self.root / "output"

    def output_slot(self, label: str = "latest") -> Path:
        """
        Path to a named output slot under ``output/`` (gitignored).

        A slot is a self-contained, inspectable snapshot of one execute/materialise:
        the curated native set (flat, at manifest-relative paths) plus a ``regression/``
        subdirectory holding the rebuilt committed bundle and a ``.source.json`` stamp.
        ``latest`` (the default) is overwritten on every run; named slots persist so two
        runs can be diffed (e.g. ``--label before`` vs ``--label after``).

        Parameters
        ----------
        label
            Slot name. Must be a single path segment (no separators or ``..``).
        """
        return safe_path(label, self.output, label="output slot label", single_segment=True)

    @property
    def test_data_dir(self) -> Path:
        """Path to the test-data directory (parent of diagnostic slug dir)."""
        return self.root.parent.parent

    def exists(self) -> bool:
        """Check if the test case directory exists."""
        return self.root.exists()

    def create(self) -> None:
        """Create the test case directory if it doesn't exist."""
        self.root.mkdir(parents=True, exist_ok=True)

catalog property #

Path to catalog.yaml.

catalog_paths property #

Path to catalog.paths.yaml (gitignored, contains local file paths).

manifest property #

Path to manifest.json (the regression bundle manifest, tracked in git).

output property #

Path to the output/ directory (gitignored; holds materialised native slots).

regression property #

Path to regression/ directory.

root instance-attribute #

The test case directory (test_data_dir / diagnostic_slug / test_case_name).

test_data_dir property #

Path to the test-data directory (parent of diagnostic slug dir).

create() #

Create the test case directory if it doesn't exist.

Source code in packages/climate-ref-core/src/climate_ref_core/testing.py 
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def create(self) -> None:
    """Create the test case directory if it doesn't exist."""
    self.root.mkdir(parents=True, exist_ok=True)

exists() #

Check if the test case directory exists.

Source code in packages/climate-ref-core/src/climate_ref_core/testing.py 
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def exists(self) -> bool:
    """Check if the test case directory exists."""
    return self.root.exists()

from_diagnostic(diagnostic, test_case) classmethod #

Create from a diagnostic, auto-resolving the provider's test-data directory.

Returns None if the provider's test-data directory cannot be determined (e.g., not a development checkout).

Parameters:

Name Type Description Default
diagnostic Diagnostic

The diagnostic to get paths for

 required
test_case str

Test case name (e.g., 'default')

 required
Source code in packages/climate-ref-core/src/climate_ref_core/testing.py 
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@classmethod
def from_diagnostic(cls, diagnostic: Diagnostic, test_case: str) -> TestCasePaths | None:
    """
    Create from a diagnostic, auto-resolving the provider's test-data directory.

    Returns None if the provider's test-data directory cannot be determined
    (e.g., not a development checkout).

    Parameters
    ----------
    diagnostic
        The diagnostic to get paths for
    test_case
        Test case name (e.g., 'default')
    """
    test_data_dir = _get_provider_test_data_dir(diagnostic)
    if test_data_dir is None:
        return None
    return cls(root=test_data_dir / diagnostic.slug / test_case)

from_test_data_dir(test_data_dir, diagnostic_slug, test_case) classmethod #

Create from an explicit test data directory.

Use this when you have a test_data_dir fixture (in tests) or know the base path explicitly.

Parameters:

Name Type Description Default
test_data_dir Path

Base test data directory (e.g., from test fixture)

 required
diagnostic_slug str

The diagnostic slug

 required
test_case str

Test case name (e.g., 'default')

 required
Source code in packages/climate-ref-core/src/climate_ref_core/testing.py 
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@classmethod
def from_test_data_dir(
    cls,
    test_data_dir: Path,
    diagnostic_slug: str,
    test_case: str,
) -> TestCasePaths:
    """
    Create from an explicit test data directory.

    Use this when you have a test_data_dir fixture (in tests) or
    know the base path explicitly.

    Parameters
    ----------
    test_data_dir
        Base test data directory (e.g., from test fixture)
    diagnostic_slug
        The diagnostic slug
    test_case
        Test case name (e.g., 'default')
    """
    return cls(root=test_data_dir / diagnostic_slug / test_case)

output_slot(label='latest') #

Path to a named output slot under output/ (gitignored).

A slot is a self-contained, inspectable snapshot of one execute/materialise: the curated native set (flat, at manifest-relative paths) plus a regression/ subdirectory holding the rebuilt committed bundle and a .source.json stamp. latest (the default) is overwritten on every run; named slots persist so two runs can be diffed (e.g. --label before vs --label after).

Parameters:

Name Type Description Default
label str

Slot name. Must be a single path segment (no separators or ..).

 'latest'
Source code in packages/climate-ref-core/src/climate_ref_core/testing.py 
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def output_slot(self, label: str = "latest") -> Path:
    """
    Path to a named output slot under ``output/`` (gitignored).

    A slot is a self-contained, inspectable snapshot of one execute/materialise:
    the curated native set (flat, at manifest-relative paths) plus a ``regression/``
    subdirectory holding the rebuilt committed bundle and a ``.source.json`` stamp.
    ``latest`` (the default) is overwritten on every run; named slots persist so two
    runs can be diffed (e.g. ``--label before`` vs ``--label after``).

    Parameters
    ----------
    label
        Slot name. Must be a single path segment (no separators or ``..``).
    """
    return safe_path(label, self.output, label="output slot label", single_segment=True)

TestDataSpecification #

Test data specification for a diagnostic.

Contains multiple named test cases for testing different input datasets.

Source code in packages/climate-ref-core/src/climate_ref_core/testing.py 
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@frozen
class TestDataSpecification:
    """
    Test data specification for a diagnostic.

    Contains multiple named test cases for testing different input datasets.
    """

    test_cases: tuple[TestCase, ...] = field(factory=tuple)
    """Collection of test cases for this diagnostic."""

    def get_case(self, name: str) -> TestCase:
        """
        Get a test case by name.

        Parameters
        ----------
        name
            Name of the test case to retrieve

        Returns
        -------
        TestCase
            The matching test case

        Raises
        ------
        StopIteration
            If no test case with that name exists
        """
        return next(tc for tc in self.test_cases if tc.name == name)

    def has_case(self, name: str) -> bool:
        """
        Check if a test case with the given name exists.

        Parameters
        ----------
        name
            Name of the test case to check

        Returns
        -------
        bool
            True if the test case exists
        """
        return any(tc.name == name for tc in self.test_cases)

    @property
    def case_names(self) -> list[str]:
        """Get names of all test cases."""
        return [tc.name for tc in self.test_cases]

case_names property #

Get names of all test cases.

test_cases = field(factory=tuple) class-attribute instance-attribute #

Collection of test cases for this diagnostic.

get_case(name) #

Get a test case by name.

Parameters:

Name Type Description Default
name str

Name of the test case to retrieve

 required

Returns:

Type Description
TestCase

The matching test case

Raises:

Type Description
StopIteration

If no test case with that name exists
Source code in packages/climate-ref-core/src/climate_ref_core/testing.py 
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def get_case(self, name: str) -> TestCase:
    """
    Get a test case by name.

    Parameters
    ----------
    name
        Name of the test case to retrieve

    Returns
    -------
    TestCase
        The matching test case

    Raises
    ------
    StopIteration
        If no test case with that name exists
    """
    return next(tc for tc in self.test_cases if tc.name == name)

has_case(name) #

Check if a test case with the given name exists.

Parameters:

Name Type Description Default
name str

Name of the test case to check

 required

Returns:

Type Description
bool

True if the test case exists
Source code in packages/climate-ref-core/src/climate_ref_core/testing.py 
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def has_case(self, name: str) -> bool:
    """
    Check if a test case with the given name exists.

    Parameters
    ----------
    name
        Name of the test case to check

    Returns
    -------
    bool
        True if the test case exists
    """
    return any(tc.name == name for tc in self.test_cases)

catalog_changed_since_regression(paths) #

Check if the catalog has changed since regression data was generated.

The baseline's input hash is read from manifest.json (catalog_hash), the single coupling record; there is no separate sidecar.

Returns True if: - No regression data exists (new test case) - No manifest, or the manifest records no catalog_hash (legacy regression data) - No catalog file exists - The current catalog hash differs from the one recorded in the manifest

Parameters:

Name Type Description Default
paths TestCasePaths

TestCasePaths for the test case

 required

Returns:

Type Description
bool

True if regression should be regenerated, False otherwise
Source code in packages/climate-ref-core/src/climate_ref_core/testing.py 
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def catalog_changed_since_regression(paths: TestCasePaths) -> bool:
    """
    Check if the catalog has changed since regression data was generated.

    The baseline's input hash is read from ``manifest.json`` (``catalog_hash``),
    the single coupling record; there is no separate sidecar.

    Returns True if:
    - No regression data exists (new test case)
    - No manifest, or the manifest records no ``catalog_hash`` (legacy regression data)
    - No catalog file exists
    - The current catalog hash differs from the one recorded in the manifest

    Parameters
    ----------
    paths
        TestCasePaths for the test case

    Returns
    -------
    :
        True if regression should be regenerated, False otherwise
    """
    if not paths.regression.exists():
        return True  # No regression data, needs to run
    if not paths.catalog.exists():
        return True  # No catalog file, needs to run
    if not paths.manifest.exists():
        return True  # No manifest, needs to run

    stored_hash = Manifest.load(paths.manifest).catalog_hash
    if stored_hash is None:
        return True  # Legacy manifest without a recorded catalog hash, needs to run

    return stored_hash != get_catalog_hash(paths.catalog)

collect_test_case_params(provider) #

Collect all diagnostic/test_case pairs from a provider for parameterized testing.

Returns a list of pytest.param objects with (diagnostic, test_case_name) tuples, each with an id of "{diagnostic.slug}/{test_case.name}".

Parameters:

Name Type Description Default
provider DiagnosticProvider

The diagnostic provider to collect test cases from

 required

Returns:

Type Description
list[ParameterSet]

List of pytest.param objects for use with @pytest.mark.parametrize
Example 
from climate_ref_core.testing import collect_test_case_params
from my_provider import provider

test_case_params = collect_test_case_params(provider)


@pytest.mark.parametrize("diagnostic,test_case_name", test_case_params)
def test_my_test(diagnostic, test_case_name): ...
Source code in packages/climate-ref-core/src/climate_ref_core/testing.py 
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def collect_test_case_params(provider: DiagnosticProvider) -> list[ParameterSet]:
    """
    Collect all diagnostic/test_case pairs from a provider for parameterized testing.

    Returns a list of pytest.param objects with (diagnostic, test_case_name) tuples,
    each with an id of "{diagnostic.slug}/{test_case.name}".

    Parameters
    ----------
    provider
        The diagnostic provider to collect test cases from

    Returns
    -------
    :
        List of pytest.param objects for use with @pytest.mark.parametrize

    Example
    -------
    ```python
    from climate_ref_core.testing import collect_test_case_params
    from my_provider import provider

    test_case_params = collect_test_case_params(provider)


    @pytest.mark.parametrize("diagnostic,test_case_name", test_case_params)
    def test_my_test(diagnostic, test_case_name): ...
    ```
    """
    import pytest  # noqa: PLC0415

    params: list[ParameterSet] = []
    for diagnostic in provider.diagnostics():
        if diagnostic.test_data_spec is None:
            continue
        for test_case in diagnostic.test_data_spec.test_cases:
            params.append(
                pytest.param(
                    diagnostic,
                    test_case.name,
                    id=f"{diagnostic.slug}/{test_case.name}",
                )
            )
    return params

excluded_test_case_diagnostics() #

Diagnostic identifiers to skip when fetching or running test cases.

Reads the REF_TEST_CASES_SKIP environment variable as a comma-separated list of diagnostic slugs or provider/diagnostic pairs.

Source code in packages/climate-ref-core/src/climate_ref_core/testing.py 
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def excluded_test_case_diagnostics() -> set[str]:
    """
    Diagnostic identifiers to skip when fetching or running test cases.

    Reads the ``REF_TEST_CASES_SKIP`` environment variable
    as a comma-separated list of ``diagnostic`` slugs or ``provider/diagnostic`` pairs.
    """
    raw = os.environ.get("REF_TEST_CASES_SKIP", "")
    return {token.strip() for token in raw.split(",") if token.strip()}

get_catalog_hash(path) #

Get the hash stored in an existing catalog file.

Parameters:

Name Type Description Default
path Path

Path to the catalog YAML file

 required

Returns:

Type Description
str | None

The hash string if found, None if file doesn't exist or has no hash
Source code in packages/climate-ref-core/src/climate_ref_core/testing.py 
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def get_catalog_hash(path: Path) -> str | None:
    """
    Get the hash stored in an existing catalog file.

    Parameters
    ----------
    path
        Path to the catalog YAML file

    Returns
    -------
    :
        The hash string if found, None if file doesn't exist or has no hash
    """
    if not path.exists():
        return None
    with open(path) as f:
        data = yaml.safe_load(f)
    if data is None:
        return None
    hash_value = data.get("_metadata", {}).get("hash")
    return str(hash_value) if hash_value is not None else None

is_test_case_excluded(provider_slug, diagnostic_slug) #

Return True if the diagnostic is excluded via REF_TEST_CASES_SKIP.

Source code in packages/climate-ref-core/src/climate_ref_core/testing.py 
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def is_test_case_excluded(provider_slug: str, diagnostic_slug: str) -> bool:
    """Return True if the diagnostic is excluded via ``REF_TEST_CASES_SKIP``."""
    excluded = excluded_test_case_diagnostics()
    return diagnostic_slug in excluded or f"{provider_slug}/{diagnostic_slug}" in excluded

load_datasets_from_yaml(path) #

Load ExecutionDatasetCollection from a YAML file.

The YAML file structure:

cmip6:
  slug_column: instance_id
  selector:
    source_id: ACCESS-ESM1-5
  datasets:
    - instance_id: CMIP6.CMIP...
      variable_id: tas
      filename: tas_Amon_ACCESS-ESM1-5_historical_r1i1p1f1_gn_185001-201412.nc
      # ... other metadata

Paths are loaded from a separate .paths.yaml file if it exists, allowing the main catalog to be version-controlled while paths remain user-specific. Multi-file datasets have multiple rows with paths keyed by {instance_id}::{filename}.

Source code in packages/climate-ref-core/src/climate_ref_core/testing.py 
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def load_datasets_from_yaml(path: Path) -> ExecutionDatasetCollection:
    """
    Load ExecutionDatasetCollection from a YAML file.

    The YAML file structure:

    ```yaml
    cmip6:
      slug_column: instance_id
      selector:
        source_id: ACCESS-ESM1-5
      datasets:
        - instance_id: CMIP6.CMIP...
          variable_id: tas
          filename: tas_Amon_ACCESS-ESM1-5_historical_r1i1p1f1_gn_185001-201412.nc
          # ... other metadata
    ```

    Paths are loaded from a separate `.paths.yaml` file if it exists,
    allowing the main catalog to be version-controlled while paths
    remain user-specific. Multi-file datasets have multiple rows with
    paths keyed by `{instance_id}::{filename}`.
    """
    with open(path) as f:
        data = yaml.safe_load(f)

    # Load paths from separate file if it exists
    paths_file = _get_paths_file(path)
    paths_map: dict[str, str] = {}
    if paths_file.exists():
        with open(paths_file) as f:
            paths_map = yaml.safe_load(f) or {}

    collections: dict[SourceDatasetType | str, DatasetCollection] = {}

    for source_type_str, source_data in data.items():
        if source_type_str == "_metadata":
            continue  # Skip metadata section
        source_type = SourceDatasetType(source_type_str)
        selector_dict = source_data.get("selector", {})
        selector: Selector = tuple(sorted(selector_dict.items()))
        datasets_list = source_data.get("datasets", [])
        slug_column = source_data.get("slug_column", "instance_id")

        # Merge paths from paths file using composite key
        for dataset in datasets_list:
            instance_id = dataset.get(slug_column)
            filename = dataset.get("filename")
            if instance_id and filename:
                # Try composite key first (new format for multi-file datasets)
                composite_key = f"{instance_id}::{filename}"
                if composite_key in paths_map:
                    dataset["path"] = paths_map[composite_key]
                elif instance_id in paths_map:
                    # Fall back to simple key for backward compatibility
                    dataset["path"] = paths_map[instance_id]
            elif instance_id and instance_id in paths_map:
                # Legacy format without filename
                dataset["path"] = paths_map[instance_id]

        collections[source_type] = DatasetCollection(
            datasets=pd.DataFrame(datasets_list),
            slug_column=slug_column,
            selector=selector,
        )

    return ExecutionDatasetCollection(collections)

save_datasets_to_yaml(datasets, path, *, force=False) #

Save ExecutionDatasetCollection to a YAML file.

Paths are saved to a separate .paths.yaml file to allow the main catalog to be version-controlled while paths remain user-specific.

Multi-file datasets (e.g., time-chunked data) are stored as multiple rows, one per file. Paths are keyed by {instance_id}::{filename} to support multiple files per dataset.

By default, the catalog is only written if the content has changed (detected via hash comparison). Use force=True to always write.

The gitignored .paths.yaml sidecar is (re)generated whenever it is missing, even when the catalog content is unchanged: on a fresh checkout the version-controlled catalog.yaml exists but the local paths file does not, and run/mint need it to resolve inputs. In that case the catalog itself is left untouched (so a plain ref test-cases fetch is enough — no --force required) and only the paths file is written.

Parameters:

Name Type Description Default
datasets ExecutionDatasetCollection

The datasets to save

 required
path Path

Path to write the YAML file

 required
force bool

If True, always write the catalog even if unchanged

 False

Returns:

Type Description
bool

True if the catalog was (re)written, False if the catalog was left unchanged (the paths sidecar may still have been regenerated).
Source code in packages/climate-ref-core/src/climate_ref_core/testing.py 
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def save_datasets_to_yaml(
    datasets: ExecutionDatasetCollection,
    path: Path,
    *,
    force: bool = False,
) -> bool:
    """
    Save ExecutionDatasetCollection to a YAML file.

    Paths are saved to a separate `.paths.yaml` file to allow the main
    catalog to be version-controlled while paths remain user-specific.

    Multi-file datasets (e.g., time-chunked data) are stored as multiple rows,
    one per file. Paths are keyed by `{instance_id}::{filename}` to support
    multiple files per dataset.

    By default, the catalog is only written if the content has changed
    (detected via hash comparison). Use `force=True` to always write.

    The gitignored `.paths.yaml` sidecar is (re)generated whenever it is **missing**, even
    when the catalog content is unchanged: on a fresh checkout the version-controlled
    `catalog.yaml` exists but the local paths file does not, and `run`/`mint` need it to
    resolve inputs. In that case the catalog itself is left untouched (so a plain
    `ref test-cases fetch` is enough — no `--force` required) and only the paths file is written.

    Parameters
    ----------
    datasets
        The datasets to save
    path
        Path to write the YAML file
    force
        If True, always write the catalog even if unchanged

    Returns
    -------
    :
        True if the catalog was (re)written, False if the catalog was left unchanged
        (the paths sidecar may still have been regenerated).
    """
    new_hash = datasets.hash
    paths_file = _get_paths_file(path)

    if not force and get_catalog_hash(path) == new_hash:
        # Catalog content is unchanged. Still regenerate the gitignored paths sidecar if it
        # is missing (e.g. a fresh checkout) so run/mint can resolve inputs, but leave the
        # version-controlled catalog untouched to avoid spurious diffs.
        if paths_file.exists():
            logger.info(f"Catalog unchanged, skipping write: {path}")
        else:
            _, paths_map = _serialise_datasets(datasets)
            _write_paths_file(paths_file, paths_map)
            logger.info(f"Catalog unchanged; regenerated missing paths file: {paths_file}")
        return False

    data, paths_map = _serialise_datasets(datasets)
    path.parent.mkdir(parents=True, exist_ok=True)
    with open(path, "w") as f:
        yaml.dump(data, f, default_flow_style=False, sort_keys=False)
    _write_paths_file(paths_file, paths_map)
    logger.info(f"Saved catalog to {path} (paths: {paths_file})")
    return True

validate_cmec_bundles(diagnostic, result) #

Validate CMEC bundles in an execution result.

Performs structural validation of the metric and output bundles.

Raises:

Type Description
AssertionError

If the result is not successful or bundles are invalid
Source code in packages/climate-ref-core/src/climate_ref_core/testing.py 
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def validate_cmec_bundles(diagnostic: Diagnostic, result: ExecutionResult) -> None:
    """
    Validate CMEC bundles in an execution result.

    Performs structural validation of the metric and output bundles.

    Raises
    ------
    AssertionError
        If the result is not successful or bundles are invalid
    """
    # TODO: Add content regression checks for the CMEC bundles (diagnostic.json /
    # output.json), mirroring `validate_series_regression`. These bundles are only
    # structurally validated here, so a diagnostic can change the metric/output
    # values without any regression test failing.
    # A content comparison must sanitise the regenerated bundle first via `PlaceholderMap.
    assert result.successful, f"Execution failed: {result}"

    # Validate metric bundle
    metric_bundle = CMECMetric.load_from_json(result.to_output_path(result.metric_bundle_filename))
    CMECMetric.model_validate(metric_bundle)

    # Check dimensions are a subset of diagnostic facets
    # Different data requirements may have different group_by fields,
    # so bundle dimensions vary per execution but must all be recognized facets
    bundle_dimensions = set(metric_bundle.DIMENSIONS.root["json_structure"])
    assert bundle_dimensions.issubset(set(diagnostic.facets)), (
        f"Bundle dimensions {bundle_dimensions} are not a subset of diagnostic facets {diagnostic.facets}"
    )

    # Validate output bundle
    CMECOutput.load_from_json(result.to_output_path(result.output_bundle_filename))

validate_series_regression(expected_path, actual_path, *, slug, replacements=None) #

Assert that regenerated series match the committed regression series.

If expected_path does not exist (legacy regression data without a stored series), the check is skipped.

Parameters:

Name Type Description Default
expected_path Path

Path to the committed series.json regression artifact. This file stores sanitized placeholders (e.g. <OUTPUT_DIR>).

 required
actual_path Path

Path to the freshly regenerated series.json in the output directory. This file contains expanded absolute paths.

 required
slug str

The diagnostic slug, used for error messages.

 required
replacements dict[str, str] | None

Optional real path -> placeholder mapping applied to the regenerated series before comparison, mirroring the sanitisation used when the regression data was written.

 None

Raises:

Type Description
AssertionError

If the regenerated series differ from the committed series.
Source code in packages/climate-ref-core/src/climate_ref_core/testing.py 
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def validate_series_regression(
    expected_path: Path,
    actual_path: Path,
    *,
    slug: str,
    replacements: dict[str, str] | None = None,
) -> None:
    """
    Assert that regenerated series match the committed regression series.

    If ``expected_path`` does not exist (legacy regression data without a stored series),
    the check is skipped.

    Parameters
    ----------
    expected_path
        Path to the committed ``series.json`` regression artifact. This file
        stores sanitized placeholders (e.g. ``<OUTPUT_DIR>``).
    actual_path
        Path to the freshly regenerated ``series.json`` in the output directory.
        This file contains expanded absolute paths.
    slug
        The diagnostic slug, used for error messages.
    replacements
        Optional ``real path -> placeholder`` mapping applied to the regenerated series before comparison,
        mirroring the sanitisation used when the regression data was written.

    Raises
    ------
    AssertionError
        If the regenerated series differ from the committed series.
    """
    if not expected_path.exists():
        return

    expected = SeriesMetricValue.load_from_json(expected_path)
    actual = _load_series_sanitised(actual_path, replacements or {})

    def _sorted_dump(series: list[SeriesMetricValue]) -> list[dict[str, Any]]:
        return sorted((s.model_dump(mode="json") for s in series), key=lambda s: repr(s["dimensions"]))

    assert len(actual) == len(expected), (
        f"Diagnostic {slug} produced {len(actual)} series but the committed series.json "
        f"has {len(expected)}. Regenerate the regression data with `--force-regen`."
    )
    assert _sorted_dump(actual) == _sorted_dump(expected), (
        f"Diagnostic {slug} produced series that differ from the committed series.json. "
        f"Regenerate the regression data with `--force-regen`."
    )