Collections and Data Structures

The Collections module contains implementations of some common data structures.

PriorityQueue

The PriorityQueue type is a basic priority queue implementation allowing for arbitrary key and priority types. Multiple identical keys are not permitted, but the priority of existing keys can be changed efficiently.

PriorityQueue{K,V}([ord])

Construct a new PriorityQueue, with keys of type K and values/priorites of type V. If an order is not given, the priority queue is min-ordered using the default comparison for V.

enqueue!(pq, k, v)

Insert the a key k into a priority queue pq with priority v.

dequeue!(pq)

Remove and return the lowest priority key from a priority queue.

peek(pq)

Return the lowest priority key from a priority queue without removing that key from the queue.

PriorityQueue also behaves similarly to a Dict so that keys can be inserted and priorities accessed or changed using indexing notation:

# Julia code
pq = Collections.PriorityQueue()

# Insert keys with associated priorities
pq["a"] = 10
pq["b"] = 5
pq["c"] = 15

# Change the priority of an existing key
pq["a"] = 0

Heap Functions

Along with the PriorityQueue type are lower level functions for performing binary heap operations on arrays. Each function takes an optional ordering argument. If not given, default ordering is used, so that elements popped from the heap are given in ascending order.

heapify(v[, ord])

Return a new vector in binary heap order, optionally using the given ordering.

heapify!(v[, ord])

In-place heapify.

isheap(v[, ord])

Return true iff an array is heap-ordered according to the given order.

heappush!(v, x[, ord])

Given a binary heap-ordered array, push a new element x, preserving the heap property. For efficiency, this function does not check that the array is indeed heap-ordered.

heappop!(v[, ord])

Given a binary heap-ordered array, remove and return the lowest ordered element. For efficiency, this function does not check that the array is indeed heap-ordered.