# # Deque Module

## # Basic deque using

The main methods that are useful with this class are `popleft` and `appendleft`

``````from collections import deque

d = deque([1, 2, 3])
p = d.popleft()        # p = 1, d = deque([2, 3])
d.appendleft(5)        # d = deque([5, 2, 3])

``````

## # Available methods in deque

Creating empty deque:

``````dl = deque()  # deque([]) creating empty deque

``````

Creating deque with some elements:

``````dl = deque([1, 2, 3, 4])  # deque([1, 2, 3, 4])

``````

``````dl.append(5)  # deque([1, 2, 3, 4, 5])

``````

Adding element left side of deque:

``````dl.appendleft(0)  # deque([0, 1, 2, 3, 4, 5])

``````

Adding list of elements to deque:

``````dl.extend([6, 7])  # deque([0, 1, 2, 3, 4, 5, 6, 7])

``````

Adding list of elements to from the left side:

``````dl.extendleft([-2, -1])  # deque([-1, -2, 0, 1, 2, 3, 4, 5, 6, 7])

``````

Using `.pop()` element will naturally remove an item from the right side:

``````dl.pop()  # 7 => deque([-1, -2, 0, 1, 2, 3, 4, 5, 6])

``````

Using `.popleft()` element to remove an item from the left side:

``````dl.popleft()  # -1 deque([-2, 0, 1, 2, 3, 4, 5, 6])

``````

Remove element by its value:

``````dl.remove(1)  # deque([-2, 0, 2, 3, 4, 5, 6])

``````

Reverse the order of the elements in deque:

``````dl.reverse()  # deque([6, 5, 4, 3, 2, 0, -2])

``````

## # limit deque size

Use the `maxlen` parameter while creating a deque to limit the size of the deque:

``````from collections import deque
d = deque(maxlen=3)  # only holds 3 items
d.append(1)  # deque()
d.append(2)  # deque([1, 2])
d.append(3)  # deque([1, 2, 3])
d.append(4)  # deque([2, 3, 4]) (1 is removed because its maxlen is 3)

``````

The Deque is the only Python data structure with fast Queue operations. (Note `queue.Queue` isn't normally suitable, since it's meant for communication between threads.) A basic use case of a Queue is the breadth first search.

``````from collections import deque

def bfs(graph, root):
distances = {}
distances[root] = 0
q = deque([root])
while q:
# The oldest seen (but not yet visited) node will be the left most one.
current = q.popleft()
for neighbor in graph[current]:
if neighbor not in distances:
distances[neighbor] = distances[current] + 1
# When we see a new node, we add it to the right side of the queue.
q.append(neighbor)
return distances

``````

Say we have a simple directed graph:

``````graph = {1:[2,3], 2:, 3:[4,5], 4:[3,5], 5:[]}

``````

We can now find the distances from some starting position:

``````>>> bfs(graph, 1)
{1: 0, 2: 1, 3: 1, 4: 2, 5: 2}

>>> bfs(graph, 3)
{3: 0, 4: 1, 5: 1}

``````

#### # Syntax

• dq = deque() # Creates an empty deque
• dq = deque(iterable) # Creates a deque with some elements
• dq.append(object) # Adds object to the right of the deque
• dq.appendleft(object) # Adds object to the left of the deque
• dq.pop() -> object # Removes and returns the right most object
• dq.popleft() -> object # Removes and returns the left most object
• dq.extend(iterable) # Adds some elements to the right of the deque
• dq.extendleft(iterable) # Adds some elements to the left of the deque

#### # Parameters

Parameter Details
`iterable` Creates the deque with initial elements copied from another iterable.
`maxlen` Limits how large the deque can be, pushing out old elements as new are added.

#### # Remarks

This class is useful when you need an object similar to a list that allows fast append and pop operations from either side (the name `deque` stands for “double-ended queue”).

The methods provided are indeed very similar, except that some like `pop`, `append`, or `extend` can be suffixed with `left`. The `deque` data structure should be preferred to a list if one needs to frequently insert and delete elements at both ends because it allows to do so in constant time O(1).