Fatos Morina

Software engineering and personal development

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How to Quickly Check if 2 Strings Are Anagrams using Counter

Anagrams are strings that have the same letters but in a different order for example abc, bca, cab, acb, bac are all anagrams, since they all contain the same letters.

We can check whether two strings are anagrams in Python in different ways. One way to do that would be to use Counter from the collections module.

From the documentation:

 A Counter is a dict subclass for counting hashable objects. It is a collection where elements are stored as dictionary keys and their counts are stored as dictionary values. Counts are allowed to be any integer value including zero or negative counts. The Counter class is similar to bags or multisets in other languages.

In plain English, with Counter, we can get a dictionary that represents the frequency of elements in a list. Let us see this in an example:

 from collections import Counter
 ​
 print(Counter("Hello"))  # Counter({'l': 2, 'H': 1, 'e': 1, 'o': 1})

Now we can use Counter to quickly check whether two strings are anagrams or not:

 from collections import Counter
 ​
 ​
 def check_if_anagram(first_string, second_string):
     first_string = first_string.lower()
     second_string = second_string.lower()
     return Counter(first_string) == Counter(second_string)
 ​
 ​
 print(check_if_anagram('testinG', 'Testing'))  # True
 print(check_if_anagram('Here', 'Rehe'))  # True
 print(check_if_anagram('Know', 'Now'))  # False

We can also check whether 2 strings are anagrams using sorted():

 def check_if_anagram(first_word, second_word):
     first_word = first_word.lower()
     second_word = second_word.lower()
     return sorted(first_word) == sorted(second_word)
 ​
 print(check_if_anagram("testinG", "Testing"))  # True
 print(check_if_anagram("Here", "Rehe"))  # True
 print(check_if_anagram("Know", "Now"))  # False

That’s basically it.

I hope you find this useful.

How to Quickly Build Your Own Iterators in Python

You have probably had the chance to iterate through a list of elements in one way or another, or through elements of a set, or a dictionary. We can go through a list, a set, or a dictionary and access their elements because they are iterable objects.

An iterator is an object that contains a countable number of objects. This means that you can iterate through elements that an iterator contains.

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How to Quickly Avoid Errors when Getting Nonexisting Dictionary Elements

Dictionaries also known as maps are data structures that are used a lot in different scenarios. The process of getting an element from a dictionary can be done using an element that is not part of the dictionary which results in an error.

For example, let us take this scenario where we have a dictionary that has an element with the key name and another one with the element surname. If we want to access it using another element, such as age, we are going to see an error like the following:

 my_dictonary = {"name": "Name", "surname": "Surname"}
 print(my_dictonary["age"])  
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How to Include Multiple Conditions at Once in Python

Similar to the case of using any(), we can also use a method that allows us to check whether all conditions are met. This can also greatly reduce the complexity of the code since you do not need to use multiple and checks.

Let us see this with an example.

Let us assume that we have the following conditions where we are checking whether we have more than 50 points in each school course:

 math_points = 51
 biology_points = 78
 physics_points = 56
 history_points = 72
 ​
 my_conditions = [math_points > 50, biology_points > 50,
                  physics_points > 50, history_points > 50]

Now passing all of them means that each condition should be met. To help us with that, we can simply use all(), as can be seen in the following snippet:

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