## process()


Process a list of items and return a summary.


Usage


``` python
process(
    items,
    strict=False,
)
```


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


## Parameters


`items: list`  
A list of items to process. Each item should be a string or convertible to string.

`strict: bool = ``False`  
If True, raise on invalid items instead of skipping them. Defaults to False.


## Returns


`dict`  
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.


## Examples

``` python
    >>> process(["a", "b", "c"])
```

    {'processed': 3, 'skipped': 0, 'status': 'complete'}

``` python
    >>> 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.md#gdtest_google_rich.validate)  
Validate a schema before processing.