Portionwhile

Portionwhile is a term used to describe a data-processing pattern in which a program handles data in fixed-size portions, or chunks, inside a loop that continues while a condition holds. The pattern emphasizes memory efficiency and progressive results by processing only a portion of the input at a time rather than loading the entire dataset.

The concept combines the ideas of chunked processing and a while-controlled loop. In practice, portionwhile relies on a bounded processing window and on maintaining any necessary state between iterations. It is often used for streaming data, large files, or real-time analytics where loading all input into memory is impractical. The technique differs from a simple while loop by making chunk boundaries explicit and by encouraging early reporting of partial results or metrics.

Typical characteristics include a fixed or adaptive chunk size, a pointer or iterator over the input, and a per-iteration processing step. It can integrate with pipelines, enabling downstream components to begin work before the full input is read. Handling of edge cases, such as the final chunk smaller than the standard size, is an important implementation detail.

Example: given a list data and chunk_size, i starts at 0 and while i < len(data): chunk = data[i:i+chunk_size]; process(chunk); i += chunk_size.

Portionwhile is common in data engineering and software that must balance latency, throughput, and memory constraints. See also: chunked processing, streaming, incremental computation.