Standardize JSON converter failures

[hbmartin]

Summary

• add an InvalidJsonError consistent with the other source-format converters
• raise it for malformed JSON and invalid PodcastIndex transcript shapes, with source-path context
• ensure bulk conversion records invalid JSON under failed instead of reporting a nonexistent output as converted
• add direct, schema-type, error-contract, and bulk-conversion regression coverage

Root cause

json_file_to_json_file logged and returned when required transcript fields were missing. Because returning normally signaled success, bulk_convert added the input to summary.converted even though no destination file had been written. Malformed JSON also exposed a lower-level JSONDecodeError instead of the converter-specific error contract used by other formats.

Impact

Callers now receive one stable JSON conversion error for malformed or schema-invalid inputs, and bulk conversion summaries accurately report those files as failures.

Validation

• uv run ruff check .
• uv run ruff format --check .
• uv run ty check podcast_transcript_convert
• uv run pyrefly check
• uv run pytest -q — 109 passed

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Review details

⚙️ Run configuration

Configuration used: Organization UI

Review profile: ASSERTIVE

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Run ID: c7dda5e6-97fe-4005-8aae-7647ff01c7ba

📥 Commits

Reviewing files that changed from the base of the PR and between 9220603 and c24beeb.

📒 Files selected for processing (5)

• podcast_transcript_convert/converters/json_to_json.py
• podcast_transcript_convert/errors.py
• tests/test_convert.py
• tests/test_errors.py
• tests/test_json.py

✨ Finishing Touches

🧪 Generate unit tests (beta)

• Create PR with unit tests
• Commit unit tests in branch codex/json-standardization

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[gemini-code-assist]

Code Review

This pull request introduces a new InvalidJsonError exception and updates the JSON-to-JSON converter to raise it when encountering invalid JSON or non-spec schemas, replacing silent skips and generic decode errors. It also adds robust type validation for the input JSON structure and updates the test suite accordingly. The review feedback suggests strengthening the schema validation further by ensuring all elements within the segments list are dictionaries, and adding a corresponding test case to verify this behavior.

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[gemini-code-assist]

While the current check ensures that segments is a list, it does not verify that the elements within the list are dictionaries. If segments contains non-dictionary elements (e.g., strings or numbers), downstream consumers expecting the standard PodcastIndex segment structure (with keys like startTime and body) will raise a TypeError when attempting to access them.

Consider adding a check to ensure all elements in segments are dictionaries.

Suggested change

	if (
	not isinstance(data, dict)
	or not isinstance(data.get("version"), str)
	or not isinstance(data.get("segments"), list)
	):
	if (
	not isinstance(data, dict)
	or not isinstance(data.get("version"), str)
	or not isinstance(data.get("segments"), list)
	or not all(isinstance(segment, dict) for segment in data["segments"])
	):

[gemini-code-assist]

To accompany the added validation for segment element types, consider adding a test case with non-dictionary elements in the segments list to verify it is correctly rejected.

@pytest.mark.parametrize(
    "data",
    [
        [],
        {"version": 1, "segments": []},
        {"version": "1.0.0", "segments": {}},
        {"version": "1.0.0", "segments": ["invalid"]},
    ],
)