feat: add initial test framework

[SecondSkoll]

Moves to a manifest generated test framework, implements some low level fixes, and adjust some rules.

[Copilot]

Pull Request Overview

This PR introduces a data-driven test framework for Vale rules using pytest, replacing manual test files with automated testing infrastructure. The framework validates Vale linting rules against expected outcomes defined in a manifest.

Key changes:

• Implements pytest-based test infrastructure with fixtures and parametrized tests
• Adds initial test coverage for two rules (000-US-spellcheck and 500-Repeated-words)
• Updates Vale configuration to enable repeated words rule and add RST directive ignores

Reviewed Changes

Copilot reviewed 41 out of 42 changed files in this pull request and generated 4 comments.

Show a summary per file

File	Description
tests/conftest.py	Core pytest configuration providing fixtures for manifest loading, Vale execution, and result validation
tests/test_rules.py	Main test functions implementing data-driven rule validation
tests/data/manifest.yml	Test manifest defining expected behaviors for two initial rules
tests/requirements.txt	Python dependencies including pytest, pyyaml, and vale 3.13.0.0
.github/workflows/pytest.yml	GitHub Actions workflow to run tests on Python 3.10 and 3.12
vale.ini	Configuration updates: enables repeated words rule, adds RST directive token ignores
test/.md, test/.rst, test/*.html	Removal of legacy manual test files
styles/Canonical/*.yml	Rule refinements including scope changes and pattern updates
styles/config/vocabularies/Canonical/accept.txt	Added "LTS" to accepted vocabulary
getting-started.md	Documentation addition about conditionally ignoring rules

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[akcano]

the name seems misleading

[akcano]

I'd probably try to flatten or simplify exception handling, otherwise we risk drowning in these unreadable try/except/raise rollercoasters. Sometimes it's OK to let an exception fall through.

Some context:

https://x.com/karpathy/status/1976077806443569355
https://www.webpronews.com/karpathy-critiques-llms-fear-of-code-exceptions-in-rlhf-training/

[akcano]

I'd love to see a formal (and documented) JSON schema for the YAML manifest used for validation somewhere around here.

[akcano]

I suggest using Pydantic for this and the manifest, too, e.g.:

class ExpectedResult(BaseModel):
    triggers: List[str] = Field(default_factory=list)
    severity: str | None = None
    message_regex: str | None = None


class TestCase(BaseModel):
    id: str
    filetypes: List[str]
    content: str
    expect: ExpectedResult


class RuleDefinition(BaseModel):
    name: str
    cases: List[TestCase]


class Manifest(BaseModel):
    rules: List[RuleDefinition]
    
    @classmethod
    def from_yaml_dict(cls, data: dict) -> "Manifest":
        """Create Manifest from YAML structure where rules is a dict."""
        rules_dict = data.get("rules", {})
        rules = [
            {"name": rule_name, "cases": rule_data.get("cases", [])}
            for rule_name, rule_data in rules_dict.items()
        ]
        return cls(rules=rules)
    
    def iter_cases(self):
        """Iterate over all test cases with their rule names."""
        for rule in self.rules:
            for case in rule.cases:
                yield rule.name, case
    
    def get_rule_names(self) -> List[str]:
        """Return list of all rule names in the manifest."""
        return [rule.name for rule in self.rules]


def _load_manifest() -> Manifest:
    with open(MANIFEST_PATH, "r", encoding="utf-8") as f:
        data = yaml.safe_load(f) or {}
    
    try:
        return Manifest.from_yaml_dict(data)
    except ValidationError as e:
        raise ValueError(f"Manifest validation failed: {e}") from e

And so on.