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Python is famous for its simplicity and ease of use. This is achieved, among other things, due to the compactness of the code. At the same time, such conciseness may hide complex program logic. In this article, we will look at 5 examples of "syntactic sugar" for processing sequences, when the built-in constructs of the programming language allow you to write less and easier.
Recall that a sequence is called an iterative data structure or simply an array of elements. In Python, sequences such as list (list), string (str), tuple (tuple), dictionary (dict) or set (set) are most often used.
CREATING LISTS IN ONE LINE USING LIST COMPREHENSION
Suppose the task is to create a list whose elements are squares of integers. A beginner in programming will do this way:
squares = []
for x in range(10):
squares.append(x**2)
As a result:
result
[0, 1, 4, 9, 16, 25, 36, 49, 64, 81]
Note that range is a sequence of numbers from 0 to 10 (not inclusive), and "**" is the exponentiation operator. Now let's do the same as professional Python developers - the List comprehension construct:
squares = [x**2 for x in range(10)]
The result is the same and the code has become more efficient
[0, 1, 4, 9, 16, 25, 36, 49, 64, 81]
List comprehension can be used for complex (nested) loops. For example, let's create pairs of elements from two lists the way a beginner will do it:
first = ['a1', 'a2']; second = ['b1', 'b2']
result = []
for i in first:
for j in second :
pair = (i, j)
result.append(pair)
And now a real Python developer with a good level
result = [(i,j) for i in first for j in second]
That's how with List comprehension you can shorten the process of creating a list from 5 lines to 1. Any programmer will see in your code the hand of a real competent Python developer
CREATING DICTIONARIES USING DICT COMPREHENSION
You need to create a dictionary whose value corresponds to the square of the key. The beginner's method requires creating an empty dictionary and a loop with an element-by-element display of the key and value on the next line:
result = {}
for x in range(10):
result[x] = x**2
and result...
{0: 0, 1: 1, 2: 4, 3: 9, 4: 16, 5: 25, 6: 36, 7: 49, 8: 64, 9: 81}
Yes, we have completed the task. We are programmers. But a real Python professional will only laugh at you.
He will show you the magic
result = {x: x**2 for x in range(10)}
{0: 0, 1: 1, 2: 4, 3: 9, 4: 16, 5: 25, 6: 36, 7: 49, 8: 64, 9: 81}
Note that after x there is a colon separating the key and its value. Similar to a List comprehension, Dict comprehension can be used for nested loops. I hope you noticed that the brackets in the List and Dict comprehensions are different.
REMOVING DUPLICATES FROM THE LIST
There are duplicate items in the list, and you only need unique values. What will a beginner do? He will definitely create a new list, and in the loop, he will arrange a check for the compliance of the element with the new list. has O(N²) time complexity.:
fruits = {'apple', 'orange', 'apple', 'pear', 'orange', 'banana'}
new = []
for fruit in fruits:
if fruit not in new:
new.append(fruit)
and he will get his result
['banana', 'apple', 'pear', 'orange']
As you can see, apple and orange are no longer repeated. In the 5th line, our newcomer checks whether an item is in the new list: if there is, then adds, otherwise ignores. Our professional, who knows about sets, will surprise us again with a 1-line solution has O(N) time complexity
# List instead of set
fruits = ['apple', 'orange', 'apple', 'pear', 'orange', 'banana']
# Actually make `new` a list
new = list(set(fruits))
['banana', 'apple', 'pear', 'orange']
A set is a data structure in which each element is unique. So when you need to exclude duplicate data, use sets
Thanks kbauer, ruudvanderham, jackm767 for useful additions to the article. You can read more information about this item in the comments
IMPORTANT NOTICE!
The set does not contain duplicate elements;
The elements of the set are immutable (they cannot be changed), but the set itself is changeable, and it can be changed;
Since the elements are not indexed, the sets do not support any slicing and indexing operations.
UNPACKING THE ITEMS FROM THE LIST
To pull an element out of the sequence, you want to use the index of the element, right? In some cases, this is correct, but Python allows you to assign each element its own variable.
x, y = (15, 5)
x
15
y
5
fruit, num, date = ['apple', 5,(2021, 11, 7)]
date
(2021, 11, 7)
LISTS SLICING IN PYTHON
In the previous example, we unpacked each item from the list. And what if you need to extract under the list? For example, there is a sequence of 5 elements, you need to take only 3 of them. This is also provided in Python:
x = [1, 2, 3, 4, 5]
result = x[:3]
result
[1, 2, 3]
A more detailed syntax looks like this:
sequence[start:stop:step]
You can omit START if you want to cut from the zero elements, END if you want to cut to the end, and STEP if your default step is 1
For example:
x = [10, 5, 13, 4, 12, 43, 7, 8]
result = x[1:6:2]
result
[5, 4, 43]
Now, knowing the syntactic sugar in Python and how to use it effectively, you can safely be called a competent Python developer
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Top comments (26)
There are errors in the part about removing duplicates.
fruits = { ... }already is a set, and so the duplicates are already discarded before reaching the loop.The output of
is not
but (order may differ)
The output you show would be obtained by
Overall, to be correct, the example would have to be changed to
Additionally, for a beginner post it would be very useful to point out that, in addition to be more concise,
has O(N) time complexity[1], while
has O(N²) time complexity.
[1] In CPython anyway, which should be using a hash-table based set implementation. Note sure though, whether the loop or the
setbased solution is faster for small numbers of elements.Under Python 3.6 and higher this one liner will also maintain the order
new = list(dict.fromkeys(fruits))and it is O(n)!
Thank you all so much) You really help all readers to become a little more literate
Interesting to know, but hard to read :/ If I'd see this in the code I wouldn't be aware, that preserving the order is an intent here.
Just adding a comment would help.
Guys, I pointed out your help in the article and asked you to pay attention to the comments) So thank you very much! Many opinions, and various practices make this article even better)
Thank you so much for the addition. Initially, my goal was just to show the difference in solutions to some problems. I will definitely add your suggestion about algorithmic complexity! And you also gave me the idea to write an article about calculating algorithmic complexity
This comment is very critical, but is not meant to be hostile.
The objective should be clarity, not brevity. Writing shorter code is good only to the extent that it makes the code more readable. "Tricks" in general tend to be obscure, make the writer feel clever, and confuse the reader. Even something like slicing's step parameter should often be explained when it's used.
I recommend people learning python read Google's python style guide to understand the reasoning, not necessarily to follow. They would not encourage a nested comprehension for product. google.github.io/styleguide/pyguid...
"a real Python professional will only laugh at you." The passages like this bother me.
Comprehensions are not dogmatically correct, and someone laughing at a beginner for not using advanced features should not be the face of "real python professionals".
With that out of the way, I think these are useful things to know.
In general I'd advise someone to learn by googling what they're trying to do (eg python remove duplicates from list), look at top answers, and consider what is clearest.
So agree. I read this article with only thought - those explicit code, which author claims as junior's often is much more readable than suggested oneliners. And claims like "a real competent Python developer code" e.t.c are controversial for me. My experience reading code of a real highly experienced and clever professionals tells me that they usually tend to the simplest and most explicit solution possible. Their code is easy to read and understand. But tricky things usually appear because of ego and lack of self confidence as a professional. Real professional developer visible by his patterns, architecture and code style, not by some tricks.
If you replace the nested for loops (plain or in a generator expression) with a call to
itertools.product, the reader will immediately see the intent.Most of the times, this carthesian product is only iterated over and above example will do. If it needs to be stored, you'll need a tuple:
Notice how each added level requires only an added argument to
product.In a post for beginners it’s probably worth mentioning that sets are unordered. If you use a set to remove duplicates you can no longer index the data. Converting back to a list may not keep the original order either (? unsure about this).
You are absolutely right. It may be worth adding the following
The set does not contain duplicate elements;
The elements of the set are immutable (they cannot be changed), but the set itself is changeable, and it can be changed;
Since the elements are not indexed, the sets do not support any slicing and indexing operations.
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Love this post, it will surely help me.
I am very happy about it! If my work helped at least 1 person, then it was not in vain and my goal was achieved)
Removing duplicate in case insensitive list.
eg fruits=['banana', 'Banana', 'Mango', 'mango', 'orange', 'OranGe']
set(map(str.lower, fruits))
will give you: {'orange', 'banana', 'mango'}
It's very simple) You are trying to change the values of the set. You forget that the values in it are immutable, so the lower case will not work. In this situation, it is necessary to bring to one register earlier
Right, but set is applied right after we lower the case for all items.
demo: online-python.com/isJQnjgrZf
Nice. But I personally prefer the beginner versions.
It seems to me that all novice developers know about generators, since they are used in all tutorials, and you will not knowingly know how to use them.
if you look at the projects on github, you can see that there are almost never such solutions or generators in the principle. I mean newbie accounts with 1 repository. They know but they don't use it