(Although this example is written using syntax introduced in version v0.5, it can work with few modifications on older versions also.)
This implementation of breadth-first search (BFS) on a graph represented with adjacency lists uses while
loops and the return
statement. The task we will solve is as follows: we have a sequence of people, and a sequence of friendships (friendships are mutual). We want to determine the degree of the connection between two people. That is, if two people are friends, we will return 1
; if one is a friend of a friend of the other, we will return 2
, and so on.
First, let’s assume we already have an adjacency list: a Dict
mapping T
to Array{T, 1}
, where the keys are people and the values are all the friends of that person. Here we can represent people with whatever type T
we choose; in this example, we will use Symbol
. In the BFS algorithm, we keep a queue of people to “visit”, and mark their distance from the origin node.
function degree(adjlist, source, dest)
distances = Dict(source => 0)
queue = [source]
# until the queue is empty, get elements and inspect their neighbours
while !isempty(queue)
# shift the first element off the queue
current = shift!(queue)
# base case: if this is the destination, just return the distance
if current == dest
return distances[dest]
end
# go through all the neighbours
for neighbour in adjlist[current]
# if their distance is not already known...
if !haskey(distances, neighbour)
# then set the distance
distances[neighbour] = distances[current] + 1
# and put into queue for later inspection
push!(queue, neighbour)
end
end
end
# we could not find a valid path
error("$source and $dest are not connected.")
end
Now, we will write a function to build an adjacency list given a sequence of people, and a sequence of (person, person)
tuples:
function makeadjlist(people, friendships)
# dictionary comprehension (with generator expression)
result = Dict(p => eltype(people)[] for p in people)
# deconstructing for; friendship is mutual
for (a, b) in friendships
push!(result[a], b)
push!(result[b], a)
end
result
end
We can now define the original function:
degree(people, friendships, source, dest) =
degree(makeadjlist(people, friendships), source, dest)
Now let’s test our function on some data.
const people = [:jean, :javert, :cosette, :gavroche, :éponine, :marius]
const friendships = [
(:jean, :cosette),
(:jean, :marius),
(:cosette, :éponine),
(:cosette, :marius),
(:gavroche, :éponine)
]
Jean is connected to himself in 0
steps:
julia> degree(people, friendships, :jean, :jean)
0
Jean and Cosette are friends, and so have degree 1
:
julia> degree(people, friendships, :jean, :cosette)
1
Jean and Gavroche are connected indirectly through Cosette and then Marius, so their degree is 3
:
julia> degree(people, friendships, :jean, :gavroche)
3
Javert and Marius are not connected through any chain, so an error is raised:
julia> degree(people, friendships, :javert, :marius)
ERROR: javert and marius are not connected.
in degree(::Dict{Symbol,Array{Symbol,1}}, ::Symbol, ::Symbol) at ./REPL[28]:27
in degree(::Array{Symbol,1}, ::Array{Tuple{Symbol,Symbol},1}, ::Symbol, ::Symbol) at ./REPL[30]:1