We can populate a new dictionary with inline key and value arguments. Still, in this example, we are creating a dictionary with indexed keys, and values are python list items using dictionary comprehension. Like List Comprehension, Dictionary Comprehension lets us to run for loop on dictionary with a single line of code. It requires a single assignment expression with at least one for statement, and following by zero or more for or if statements. There is another way of constructing a dictionary via zip that's working for both Python 2.x and 3.x. Evaluate the expression and append it into the list. I’ll give you a quick introduction to both of them so, that it becomes easy for you to understand the topic well. In the first example of this article, we have used list items as keys and value as an integer of the dictionary. Like List Comprehension, Python allows dictionary comprehensions. In the following example, we have two teams of members (keys) and their scores (values). A dictionary comprehension takes the form {key: value for (key, value) in iterable} Let’s see a example,lets assume we have … Comparing to use map or filter or nested loops to generate the same result, comprehension has more concise syntax and improved readability. For instance, to transform a nested list into a flatten list, you can make use of the list comprehension with multiple loops as per below: Python will evaluate these expressions from left to right until the innermost block is reached. With Python List comprehension, instead of having to resize the list on runtime, python will now allocate the list’s memory first, which makes it faster in this case. Program without using list comprehension (lc): The filter will give only those values which are divisible by 2. Like a list comprehension, they create a new dictionary; you can’t use them to add keys to an existing dictionary. You shall see the nested list has been transformed into a flatten list: And similarly if you have multiple sequences to be iterated through, you can have multiple for statements in your comprehension or use zip function depends on what kind of results you what to achieve: The above code would generate the output as per below: If you use zip as per below, it will generates some different results. The result will be stored in a new list resulting from evaluating the expression. To convert a list to a dictionary using the same values, you can use dictionary comprehension or the dict.fromkeys() method. Here are the top 5 benefits of using List Comprehension in Python: Less Code Required – With List Comprehension, your code gets compressed from 3-4 lines to just 1 line. Like a list comprehension, they create a new dictionary; you can’t use them to add keys to an existing dictionary. This is yet another way in which this task can be performed. For instance, below code would list out all all the ipynb files from current and its sub folder but excluding the checkpoints folder: As you can see from the above examples, the list comprehension supports to generate list of tuples, but do take note that you have to use parenthesis e.g. For instance: The only difference between list comprehension and set comprehension is the square braces “[]” changed to curly braces “{}”.  And you shall see the same result as previous example except the data type now is a set: And same as list comprehension, any iterables can be used in the set comprehension to derive a new set. Dictionary objects in python is used for mapping information as key:value pairs. In this tutorial, you are going to learn about the list and dictionary comprehension in python. dictionary = {key: value for vars in iterable} See the following code example of a dictionary comprehension. It provides a concise way to create a list. 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