Collections

"The world is full of abandoned meanings."

– Don DeLillo, White Noise

Read this group when you want to know what the Focus DSL's .each() does underneath, or need a traversal the generated paths do not give you. Until then, you can skip it.

Single values are straightforward enough. The challenge arrives when you need to handle many of them: a discount on every price in an order means a stream, a map, a collector, and the suspicion that there must be a better way. There is. Here is the destination, before any theory: one reusable path from a league to every player's score, and a bulk update through it. Every line compiles against the real library on every build:

var everyScore = LeagueTraversals.teams()
    .andThen(TeamTraversals.players())
    .andThen(PlayerLenses.score());

League bonus = Traversals.modify(everyScore, score -> score + 5, league);
// Traversals.getAll(everyScore, league) -> [100, 90, 110, 120]
// Traversals.getAll(everyScore, bonus)  -> [105, 95, 115, 125]
// every team and player is rebuilt for you; league itself is untouched

Why this matters

A stream pipeline that rebuilds nested records is code you write again for every operation. A composed traversal is a value: define the path once and reuse it for pure updates, for queries, and (through modifyF) for validating or asynchronous passes over every element. And when a path should never write, asFold() or a Getter says so in the type, so read-only intent is checked by the compiler rather than promised in a comment.

A Traversal focuses zero or more values, and reads and writes them all. A Fold is its read-only cousin, for queries, searches and aggregates, so code that must not modify data says so in its type. A Getter reads exactly one value and never writes, and a Setter writes without reading. Optic Capabilities lists which operations each type declares, and where a Traversal's reads and writes live instead.

Pages in this group

  1. Traversals: Bulk operations on collection elements
  2. Folds: Read-only queries and monoid-based aggregation
  3. Getters: Read-only focus on a single value
  4. Setters: Write-only modification without reading
  5. Common Data Structures: Ready-made traversals for List, Map, Set and more
  6. Limiting Traversals: The first N elements, a slice, or chosen indices
  7. List Decomposition: Cons and snoc patterns for lists

Hands-On Learning

Practise this group in the Traversals & Practice Journey (28 exercises).

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