In mathematics, there’s a concept called set-builder notation, also called set comprehension. Inspired by this principle, Python offers comprehensions, too. In fact, list comprehensions are one of the defining features of Python. They allow us to create concise, readable code that outperforms the uglier alternatives like
for loops or using
We’ll first look at the most well-known type: list comprehensions. Once we’ve got a good grasp of how they work, you’ll also learn about set comprehensions and dictionary comprehensions.
A list comprehension is a language construct. It’s used to create a list based on an existing list. Sounds a little vague, I know, but after a few examples, that ‘ah-ha!’ moment will follow — trust me.
The basic syntax of a list comprehension is:
[ <expression> for item in list if <conditional> ]
if’-part is optional, as you’ll discover soon. However, we do need a list to start from. Or, more specifically, anything that is an iterator. We’ll use Python’s
range() function, which is a special type of iterator called a generator: It generates a new number on each iteration.
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Welcome to my Blog, In this article, we will learn python lambda function, Map function, and filter function.
Lambda function in python: Lambda is a one line anonymous function and lambda takes any number of arguments but can only have one expression and python lambda syntax is
Syntax: x = lambda arguments : expression
Now i will show you some python lambda function examples:
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List comprehension is used for creating lists based on iterables. It can also be described as representing for and if loops with a simpler and more appealing syntax. List comprehensions are relatively faster than for loops.
The syntax of a list comprehension is actually easy to understand. However, when it comes to complex and nested operations, it might get a little tricky to figure out how to structure a list comprehension.
In such cases, writing the loop version first makes it easier to write the code for the list comprehension. We will go over several examples that demonstrate how to convert a loop-wise syntax to a list comprehension.
Basic structure of list comprehension (image by author)
Let’s start with a simple example. We have a list of 5 integers and want to create a list that contains the squares of each item. Following is the for loop that performs this operation.
lst_a = [1, 2, 3, 4, 5] lst_b =  for i in lst_a: lst_b.append(i**2) print(lst_b) [1, 4, 9, 16, 25]
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No programming language is pretty much as diverse as Python. It enables building cutting edge applications effortlessly. Developers are as yet investigating the full capability of end-to-end Python development services in various areas.
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Programming advancement is multidimensional today. Endeavor programming requires an intelligent application with AI and ML capacities. Shopper based applications require information examination to convey a superior client experience. Netflix, Trello, and Amazon are genuine instances of such applications. Python assists with building them effortlessly.
Python can do such numerous things that developers can't discover enough reasons to admire it. Python application development isn't restricted to web and enterprise applications. It is exceptionally adaptable and superb for a wide range of uses.
Python is known for its tools and frameworks. There's a structure for everything. Django is helpful for building web applications, venture applications, logical applications, and mathematical processing. Flask is another web improvement framework with no conditions.
Web2Py, CherryPy, and Falcon offer incredible capabilities to customize Python development services. A large portion of them are open-source frameworks that allow quick turn of events.
Simple to read and compose
Python has an improved sentence structure - one that is like the English language. New engineers for Python can undoubtedly understand where they stand in the development process. The simplicity of composing allows quick application building.
The motivation behind building Python, as said by its maker Guido Van Rossum, was to empower even beginner engineers to comprehend the programming language. The simple coding likewise permits developers to roll out speedy improvements without getting confused by pointless subtleties.
Utilized by the best
Alright - Python isn't simply one more programming language. It should have something, which is the reason the business giants use it. Furthermore, that too for different purposes. Developers at Google use Python to assemble framework organization systems, parallel information pusher, code audit, testing and QA, and substantially more. Netflix utilizes Python web development services for its recommendation algorithm and media player.
Massive community support
Python has a steadily developing community that offers enormous help. From amateurs to specialists, there's everybody. There are a lot of instructional exercises, documentation, and guides accessible for Python web development solutions.
Today, numerous universities start with Python, adding to the quantity of individuals in the community. Frequently, Python designers team up on various tasks and help each other with algorithmic, utilitarian, and application critical thinking.
Python is the greatest supporter of data science, Machine Learning, and Artificial Intelligence at any enterprise software development company. Its utilization cases in cutting edge applications are the most compelling motivation for its prosperity. Python is the second most well known tool after R for data analytics.
The simplicity of getting sorted out, overseeing, and visualizing information through unique libraries makes it ideal for data based applications. TensorFlow for neural networks and OpenCV for computer vision are two of Python's most well known use cases for Machine learning applications.
Thinking about the advances in programming and innovation, Python is a YES for an assorted scope of utilizations. Game development, web application development services, GUI advancement, ML and AI improvement, Enterprise and customer applications - every one of them uses Python to its full potential.
The disadvantages of Python web improvement arrangements are regularly disregarded by developers and organizations because of the advantages it gives. They focus on quality over speed and performance over blunders. That is the reason it's a good idea to utilize Python for building the applications of the future.
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List comprehension is nothing but a shorter and crisper version of the code and also memory efficient. By using this we can either create a new list or perform some operation in an existing list.
The normal code for creating a list of 0–9 will be like
x= for i in range (10): x.append(i) print(x) [0,1,2,3,4,5,6,7,8,9]
By using list comprehension
x=[i for i in range(10)] print(x) [0,1,2,3,4,5,6,7,8,9]
As you can see the normal code is long but the code that we did using list comprehension does the job just in one line so list comprehension is preferred over the traditional method.
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Python Programming language makes everything easier and straightforward. Effective use of its built-in libraries can save a lot of time and help with faster submissions while doing Competitive Programming. Below are few such useful tricks that every Pythonist should have at their fingertips:
Below is the implementation to convert a given number into a list of digits:
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