Iterator

As explained in Software Design for Python Programmers

An iterator is an object or interface that provides sequential access to elements of a collection without exposing the collection's implementation.

An iterator provides sequential access to collection elements while hiding how the collection stores them. It lets one algorithm process lists, generators, dictionaries, or other sequential collections through a common interface. section 11.0 section 11.1

The design problem appears when one report algorithm must process teams whose players are stored differently. Directly handling each representation couples the report to every team implementation and makes collection changes leak into client code. section 11.1 section 11.1.3

Refactor the design around a small iterator interface:

• Define next() to advance through the sequence and return the next domain object. section 11.1.3
• Define has_next() to report whether another object remains. section 11.1.3
• Implement a concrete iterator for each collection representation, such as ListIterator, GeneratorIterator, and DictionaryIterator. section 11.1.3 section 11.1.4
• Expose an iterator property from each team while keeping its player collection hidden. section 11.1.3
• Make the client use only the iterator interface: while it.has_next(), process it.next(). section 11.1.3

Player reports across three collections

Team 1 stores players in a list, Team 2 uses a generator, and Team 3 uses a dictionary. TeamReport obtains team.iterator and prints each Player without knowing which representation supplies it. Adding or replacing a sequential collection requires an appropriate iterator rather than changes to the report algorithm. section 11.1 section 11.4

Figure 11.3 Each Team subclass is paired with an Iterator class that is appropriate for its sequential collection of Player objects. Class TeamReport delegates iterating over the various types of sequential collections to the Iterator classes ListIterator, GeneratorIterator, and DictionaryIterator. The grayed-out portions of the diagram haven’t changed logically from figure 11.1.

Use the architecture diagram to trace the pairing between each Team subclass and its collection-specific iterator, then follow TeamReport’s delegated traversal. section 11.1.3

Python’s built-in iterators can be wrapped when polymorphism must select an iterator at runtime; the pattern is most useful when the client must remain independent of collection representations. section 11.1.4

How Software Design for Python Programmers covers it

How deep it goes

Defines iterator responsibilities, concrete implementations, client delegation, and extensibility, while stopping short of broader iterator internals.

Examples

Uses baseball-team player reports backed by a list, generator, and dictionary, with ListIterator, GeneratorIterator, and DictionaryIterator.

What it assumes

Assumes familiarity with sequential collections and objects while teaching the iterator interface and its decoupling role.

What you can do after

Build it from scratch by defining an iterator interface, pairing implementations with collections, and delegating traversal to the client.

How it connects

Connects sequential collections, polymorphism, encapsulation, loose coupling, and the Visitor Design Pattern.

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Related concepts

• loopused by · A loop is a programming control-flow construct that repeatedly executes a block of instructions according to an iteration rule or continuation condition.
• data transformationproduced by · A data transformation is an operation or function that maps input data or its representation to modified data or a different representation.
• file objectincludes · A file object is a program-accessible representation of an open file or stream, including its access state and input/output operations.
• __iter__produced by · __iter__ is a Python special method that returns an iterator for an object.
• generatorincludes · A generator is a language construct or computation that produces values incrementally on demand, typically suspending and resuming while preserving its state.
• __next__has part · __next__ is a Python special method that returns an iterator’s next item or raises StopIteration when no items remain.

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