Python Built In Functions
Python comes with a handful of built in functions provided by the standard library. In today’s post, we will look some of them which are very useful in day to day programming.
Built-in Functions
The following list contains the functions I have used the most for the past year:
- abs
- all
- any
- divmod
- enumerate
- len
- max
- min
- range
- sum
- zip
Let’s look at each one of them in order with examples.
abs
abs is the absolute function, turning numbers to absolute values.
1
2
3
4
5
>>> a = -1
>>> a = abs(a)
>>> a
>>> 1
all
all takes an iterable and returns a boolean which is True if all elements are True, else False.
1
2
3
4
>>> a = [1, 2, None, 3, 4]
>>> all([v != None for v in a])
>>> False
any
any takes an iterable and returns a boolean which is True if any element is True, else False.
1
2
3
4
>>> a = [1, 2, None, 3, 4]
>>> any([v != None for v in a])
>>> True
divmod
divmod returns the division and the modulo in one operation.
1
2
3
4
>>> help(divmod)
divmod(x, y, /)
Return the tuple (x//y, x%y). Invariant: div*y + mod == x.
x//y would be the integral part of the division and x%y would be the modulo.
1
2
>>> divmod(5, 3)
>>> (1, 2)
enumerate
enumerate takes an iterable and returns an iterable which returns the index plus value on each iteration.
1
2
3
4
5
6
7
8
9
10
11
>>> a = ["a", "b", "c"]
>>> a
>>> ['a', 'b', 'c']
>>> for idx, ch in enumerate(a):
print(idx, ch)
0 a
1 b
2 c
len
len will return the length of an iterable. Useful for lists but also dictionaries as it would return the size of the dictionary.
1
2
3
4
5
>>> len([1, 2, 3])
>>> 3
>>> len({'a': 1, 'b': 2})
>>> 2
max
max will return the maximum value in an iterable. A common example is keeping track of the maximum value:
1
max_val = max(max_val, next_val)
min
min will return the minimum value in an iterable.
1
min_val = min(min_val, next_val)
range
range returns a sequence from the start to stop specified or if not specified from 0 till stop.
1
2
3
4
5
6
7
8
>>> list(range(0, 10))
>>> [0, 1, 2, 3, 4, 5, 6, 7, 8, 9]
>>> list(range(10))
>>> [0, 1, 2, 3, 4, 5, 6, 7, 8, 9]
>>> list(range(9, -1, -1))
>>> [9, 8, 7, 6, 5, 4, 3, 2, 1, 0]
As we can see we can also use range to return a sequence of element descreasing toward 0.
sum
sum will return the sum of all values in an iterable.
1
2
>>> sum([1, 2, 3])
>>> 6
zip
zip will combine two list stopping when the first list is exhausted.
1
2
3
4
5
6
7
8
9
10
>>> a = [1, 2, 3, 4, 5, 6]
>>> b = ["a", "b", "c"]
>>> for x, y in zip(a, b):
print(x, y)
1 a
2 b
3 c
zip combined with range is very useful to traverse diagonals starting from each corner.
For example if we imagine a matrice 4x4:
(0, 0) |
(0, 1) |
(0, 2) |
(0, 3) |
(1, 0) |
(1, 1) |
(1, 2) |
(1, 3) |
(2, 0) |
(2, 1) |
(2, 2) |
(2, 3) |
(3, 0) |
(3, 1) |
(3, 2) |
(3, 3) |
Get the diagonal from top left to bottom right:
1
2
3
4
5
6
>>> for x, y in zip(range(0, 4), range(0, 4)):
print(x, y)
0 0
1 1
2 2
3 3
Get the diagonal from top right to bottom left:
1
2
3
4
5
6
>>> for x, y in zip(range(0, 4), range(3, -1, -1)):
print(x, y)
0 3
1 2
2 1
3 0
Get the diagonal from bottom left to top right:
1
2
3
4
5
6
>>> for x, y in zip(range(3, -1, -1), range(0, 4)):
print(x, y)
3 0
2 1
1 2
0 3
Or lastly get the diagonal from bottom right to top left:
1
2
3
4
5
6
>>> for x, y in zip(range(3, -1, -1), range(3, -1 , -1)):
print(x, y)
3 3
2 2
1 1
0 0
And that concludes today’s post!
Conclusion
Today we looked at a bunch of built in functions provided by Python standard library. By making sure we are aware of those, we can reduce the complexity of our algorithm by leveraging them. I hope you liked this post and I see you on the next one!
