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This is the API documentation for the gdtest_google_rich library.
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## Functions

Public functions


process(items: list, strict: bool = False) -> dict

Process a list of items and return a summary.

Iterates through the items, applies validation and
aggregation, and returns a summary dictionary with
counts and status information.

Args:
    items: A list of items to process. Each item should
        be a string or convertible to string.
    strict: If True, raise on invalid items instead of
        skipping them. Defaults to False.

Returns:
    A dictionary with the following keys:

    - ``"processed"`` — number of successfully processed items.
    - ``"skipped"`` — number of skipped items (0 if strict).
    - ``"status"`` — ``"complete"`` or ``"partial"``.

Raises:
    ValueError: If ``items`` is empty.
    TypeError: If an item is not convertible to string
        and ``strict`` is True.

Note:
    The processing order follows the input list order.
    Items are processed sequentially and results are
    deterministic for the same input.

Example:
    >>> process(["a", "b", "c"])
    {'processed': 3, 'skipped': 0, 'status': 'complete'}

    >>> process(["a", None, "c"], strict=False)
    {'processed': 2, 'skipped': 1, 'status': 'partial'}

Warning:
    Large lists (>10,000 items) may cause significant
    memory usage. Consider batching for large inputs.

References:
    Gang of Four, "Design Patterns", Iterator pattern.

See Also:
    ``validate``: Validate a schema before processing.

validate(schema: dict, data: dict) -> bool

Validate data against a schema dictionary.

Checks that all keys in the schema are present in data
and that value types match the schema specification.

Args:
    schema: A dictionary mapping key names to expected
        types (e.g., ``{"name": str, "age": int}``).
    data: The data dictionary to validate against
        the schema.

Returns:
    True if the data conforms to the schema.

Raises:
    KeyError: If a required key from the schema is
        missing in the data.
    TypeError: If a value in data does not match the
        expected type from the schema.

Note:
    Only top-level keys are validated. Nested dicts
    are not recursively checked.