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Dictionary Comprehension in Python

Module - 5 Comprehensions in Python
Dictionary Comprehension in Python

Overview

Dictionary comprehension may be a fast way to form a modern dictionary from an existing object like a list, tuple, or dictionary ūüďĚūüďĚ. In this lesson, we'll jump more profound into dictionary comprehension, covering its syntax ūüďĖūüďĖ, how to utilize it, and a few best practices to take after.

What is Dictionary Comprehension?

Dictionary comprehension may be a valuable and flexible feature of Python that can be utilized to form a new dictionary based on an existing iterable object. This iterable object can be a list, tuple, or another lexicon. The syntax for dictionary comprehension is brief and proficient, permitting you to write code more expressively and exquisitely, which can spare you a lot of time and exertion ūüēĎ.

Using dictionary comprehension, you can quickly filter and change information from the first iterable object while developing the new dictionary ūüĒć. This could assist you in disengaging and organizing information in a way that's more important and useful. Additionally, dictionary comprehension permits you to perform complex operations on the data, such as sorting, gathering, and amassing ūüďä, with fair a couple of lines of code ūüíĽ.

In expansion, lexicon comprehension is open to more than straightforward key-value sets. You can use it to make settled word references, where each key value combined is a word reference. This will be a valuable strategy for organizing and organizing complex information progressively.

Generally, word reference comprehension is a virtual device for any Python engineer who needs to compose efficient, readable, and expressive code. It may be an effective highlight that can assist you in controlling and changing information in various ways, and it is well worth taking the time to memorize and ace.

Syntax

Dictionary comprehension has a simple and elegant syntax that consists of two parts:


new_dict = {key_expression: value_expression for variable in iterable if condition}
  • new_dict: the new dictionary you want to create.
  • key_expression: an expression that defines the key of each element in the new dictionary.
  • value_expression: an expression that defines the value of each element in the new dictionary.
  • variable: a variable that takes each value in the iterable object.
  • iterable: an iterable object, such as a list, a tuple, or another dictionary, that provides values for the variable.
  • condition (optional): a conditional statement that filters the elements in the iterable object.

The for loop and the if statement are the two fundamental building blocks of dictionary comprehension. The for loop iterates over the iterable object, and the if statement filters the elements based on a condition.

Examples

Let's see some examples of dictionary comprehension in action.

Creating a new dictionary of squared values


numbers = {'one': 1, 'two': 2, 'three': 3, 'four': 4, 'five': 5} squared_numbers = {key: value**2 for key, value in numbers.items()} 
print(squared_numbers)

In this example, we're creating a new dictionary called squared_numbers that contains the squared values of the values in the numbers dictionary.

Filtering elements in a dictionary


numbers = {'one': 1, 'two': 2, 'three': 3, 'four': 4, 'five': 5} 
even_numbers = {key: value for key, value in numbers.items() if value % 2== 0} print(even_numbers)

In this example, we're creating a new dictionary called even_numbers that contains only the key-value pairs from the numbers dictionary where the value is even.

Using a dictionary comprehension with strings


words = ['apple', 'banana', 'cherry'] 
word_lengths = {word: len(word) for word in words} 
print(word_lengths)

In this example, we're creating a new dictionary called word_lengths that contains the length of each word in the word list.

Best Practices

Here are a few best hones to take after when utilizing dictionary comprehension in your code:

  • Keep it basic: Dictionary comprehension is implied to simplify your code, so dodge utilizing complex expressions or nesting as well numerous for loops.
  • Utilize meaningful variable names: Utilize variable names that pass on the reason for the variable, so it's simpler to get what the lexicon comprehension is doing.
  • Utilize curly braces to extend readability: Utilize curly braces to encase dictionary comprehension, so it's less demanding to recognize from regular code.

Conclusion

Dictionary comprehension efficiently creates a new dictionary from an existing iterable object, such as a list or another dictionary. The syntax for dictionary comprehension is simple and elegant, allowing you to filter and transform data while constructing the new dictionaryūüďÉ.

Key Takeaways

  • Dictionary comprehension could be a Python feature that makes a new dictionary from an iterable object employing a brief syntax.
  • It permits filtering and changing data, creating nested dictionaries and helps organize and structure complex data.
  • The syntax incorporates key and value expressions, a variable for iterating through the iterable object, and an optional condition.
  • Best hones incorporate keeping it straightforward, utilizing important variable names, and utilizing curly braces for lucidness.
  • Lexicon comprehension is a fundamental tool for composing productive and expressive code.

Quiz

  1. What is dictionary comprehension? 
    1. A way to create a new dictionary from an existing iterable object  
    2. A way to update an existing dictionary 
    3. A way to delete an existing dictionary 
    4. A way to print an existing dictionary

Answer: a. A way to create a new dictionary from an existing iterable object

  1. Which of the following is a key element in dictionary comprehension? 
    1. if statement 
    2. for loop 
    3. both a and b 
    4. None of the above

Answer: c. both a and b

  1. Which of the following is a best practice to follow when using dictionary comprehension? 
    1. Use complex expressions to improve the efficiency of the code 
    2. Use variable names that are difficult to understand 
    3. Use curly braces to enclose the dictionary comprehension  
    4. Use nested for loops to create complex data structures

Answer: c. Use curly braces to enclose the dictionary comprehension

  1. Which of the following is an example of dictionary comprehension? 
    1. numbers = [1, 2, 3, 4, 5] squared_numbers = {num: num**2 for num in numbers} 
    2. numbers = {'one': 1, 'two': 2, 'three': 3} even_numbers = {key: value for key, value in numbers.items() if value % 2 == 0}  
    3. numbers = {'one': 1, 'two': 2, 'three': 3} numbers.update({'four': 4})  
    4. numbers = {'one': 1, 'two': 2, 'three': 3} del numbers['two']

Answer: b. numbers = {'one': 1, 'two': 2, 'three': 3} even_numbers = {key: value for key, value in numbers.items() if value % 2 == 0}

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