Introduction to Python looping techniques (with code)

This article brings you an introduction to Python looping skills (with code). It has certain reference value. Friends in need can refer to it. I hope it will be helpful to you.

When looping in the dictionary, use the items() method to take out the keywords and corresponding values ​​at the same time

>>> knights = {'gallahad': 'the pure', 'robin': 'the brave'}
>>> for k, v in knights.items():
...     print(k, v)
...
gallahad the pure
robin the brave

When looping in the sequence, use <span class="pre">enumerate()</span> The function can take out the index position and its corresponding value at the same time

>>> for i, v in enumerate(['tic', 'tac', 'toe']):
...     print(i, v)
...
0 tic
1 tac
2 toe

When looping in two or more sequences at the same time, you can use <span class="pre">zip()</span> The function matches the elements inside it one by one.

>>> questions = ['name', 'quest', 'favorite color']
>>> answers = ['lancelot', 'the holy grail', 'blue']
>>> for q, a in zip(questions, answers):
...     print('What is your {0}?  It is {1}.'.format(q, a))
...
What is your name?  It is lancelot.
What is your quest?  It is the holy grail.
What is your favorite color?  It is blue.

When looping a sequence in the reverse direction, first position the sequence in the forward direction, and then call the <span class="pre">reversed()</span> function

>>> for i in reversed(range(1, 10, 2)):
...     print(i)
...
7
3

If you want to press a certain To cycle through a sequence in a specified order, you can use the <span class="pre">sorted()</span> function, which can return a new sorted sequence without changing the original sequence

>>> basket = ['apple', 'orange', 'apple', 'pear', 'orange', 'banana']
>>> for f in sorted(set(basket)):
...     print(f)
...
apple
banana
orange
pear

Sometimes you may want to modify the contents of the list while python is looping. Generally speaking, it is simpler and safer to create a new list instead

>>> import math
>>> raw_data = [56.2, float('NaN'), 51.7, 55.3, 52.5, float('NaN'), 47.8]
>>> filtered_data = []
>>> for value in raw_data:
...     if not math.isnan(value):
...         filtered_data.append(value)
...
>>> filtered_data
[56.2, 51.7, 55.3, 52.5, 47.8]

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