Sliding window

As explained in API Design Patterns

A sliding window is a bounded set of currently active versions that advances as newer versions replace older ones.

How API Design Patterns covers it

How deep it goes

Defines four lifecycle states and illustrates their progression, but does not detail implementation mechanics.

Examples

Uses a five-version monthly timeline and a state table covering Preview, Current, Deprecated, and Deleted.

What it assumes

Assumes API users can tolerate frequent deprecations and understand that Preview code may break without stability guarantees.

What you can do after

Operate/configure an API version lifecycle with explicit stability, change, deprecation, and deletion expectations.

How it connects

Connects API versioning with deprecation policy, compatibility, security patches, and critical bug fixes.

liveBookmanning.com

Read API Design Patterns on liveBook Get the book at manning.com

Also explained in

• 

  liveBookmanning.com
  Build a Large Language Model (From Scratch)A data-sampling method that moves a fixed-size window across text to create overlapping training examples.
• 

  liveBookmanning.com
  Kafka for ArchitectsA sliding window is a stream-processing time interval defined by the timestamp difference between records being considered for a join or computation.
• 

  liveBookmanning.com
  Deep Learning with Python, Third EditionA technique that moves a fixed-size window across text or other data to create overlapping local segments.
• 

  liveBookmanning.com
  Kafka Streams in Action, Second EditionA sliding window is a fixed-duration stream-processing window whose boundaries are determined by record timestamps and whose contents change as records enter or leave.

Compare how 5 books explain sliding window →

Related concepts

• text chunkproduces · A text chunk is a bounded segment of a larger text treated as a unit for processing, storage, or retrieval.
• time windowkind of · A bounded temporal interval or event scope over which observations or events are grouped, evaluated, or processed.
• convolutionused by · Convolution is an operation that applies a kernel across an input, combining values from overlapping local regions with shared weights to produce outputs.
• tokenuses · A token is a discrete unit of text, such as a word, word fragment, character, or symbol, represented and processed as an element by a language model.
• timestampuses · A timestamp is a value representing a specific point in time, typically associated with an event, observation, or data item.

This explainer was generated by Manning's knowledge graph from the text of API Design Patterns. The section links point to the parts of the book it draws on.