Often when working with collections of data, you may want to find the smallest or largest item. It’s easy enough to write a function
that iterates through the items and returns the smallest or largest one, or use the builtin `min()`

, `max()`

, or `sorted()`

functions.
Another interesting way may be implementing a heap (priority) queue.

Python provides a pretty convenient module called `heapq`

that does that for you. `heapq`

comes with a cool set of inbuilt functions that you can read
more about in the docs. For this short post, I just want to show how you can easily find the smallest
and largest items in a collection

## Finding the smallest items

Find 3 of the smallest items using the `nsmallest`

function:

```
import heapq
numbers = [9, 45, 21, 4, 63, 3, 109]
print(heapq.nsmallest(3, numbers)) # [3, 4, 9]
```

Also, converting a list into a heap using the `heapify`

function automatically sets the smallest item as the first:

```
import heapq
numbers = [9, 45, 21, 4, 63, 3, 109]
heapq.heapify(numbers)
print(numbers)
# Output: [3, 4, 9, 45, 63, 21, 109]
```

You can then pop from the heap with `heappop()`

:

```
heapq.heappop(numbers) # 3
print(numbers)
# Output: [4, 45, 9, 109, 63, 21]
heapq.heappop(numbers) # 4
print(numbers)
# Output: [9, 45, 21, 109, 63]
```

## Finding the largest items

Find 3 of the largest items using the `nlargest`

function:

```
import heapq
numbers = [9, 45, 21, 4, 63, 3, 109]
print(heapq.nlargest(3, numbers)) # [109, 63, 45]
```

## A more practical example

```
import heapq
people = [
{'fname': 'John', 'lname': 'Doe', 'age': 30},
{'fname': 'Jane', 'lname': 'Doe', 'age': 25},
{'fname': 'Janie', 'lname': 'Doe', 'age': 10},
{'fname': 'Jane', 'lname': 'Roe', 'age': 22},
{'fname': 'Johnny', 'lname': 'Doe', 'age': 12},
{'fname': 'John', 'lname': 'Roe', 'age': 45}
]
oldest = heapq.nlargest(2, people, key=lambda s: s['age'])
print(oldest)
# Output: [{'fname': 'John', 'lname': 'Roe', 'age': 45}, {'fname': 'John', 'lname': 'Doe', 'age': 30}]
youngest = heapq.nsmallest(2, people, key=lambda s: s['age'])
print(youngest)
# Output: [{'fname': 'Janie', 'lname': 'Doe', 'age': 10}, {'fname': 'Johnny', 'lname': 'Doe', 'age': 12}]
```

It should be noted though that the `nsmallest(n, iterable)`

and `nlargest(n, iterable)`

functions perform best for smaller values of `n`

.
For larger values, it is more efficient to use the `sorted()`

function. Also, when `n==1`

, it is more efficient to use the builtin `min()`

and
`max()`

functions.

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