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Crystal Clear Explanation of Python List Comprehensions
List comprehension is a way of creating lists based on other iterables such as sets, tuples, other lists, and so on. 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 though.
The basic structure of a list comprehension is as follows.
(image by author)
It seems quite simple but might get tricky in some cases. In this article, we will start from a very simple list comprehension and steadily increase the complexity. I will clearly explain how to represent and understand highly complex list comprehensions as well.
List comprehensions are preferred over for and if loops in most cases because
- They are relatively faster than for loops.
- They are considered to be more pythonic than for loop and map function.
- The syntax of list comprehension is easier to read and understand.
Let’s start with a simple example.
words = ['data','science','machine','learning']
We want to create a list that contains of the length of each word in the words list. Let’s perform the task using both a for loop and list comprehension.
#for loop
a = []
for word in words:
a.append(len(word))
#list comprehension
b = [len(word) for word in words]
print(f"a is {a}")
print(f"b is {b}")
a is [4, 7, 7, 8]
b is [4, 7, 7, 8]
#machine-learning #data-science #artificial-intelligence #python
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Lambda, Map, Filter functions in python
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:
#python #anonymous function python #filter function in python #lambda #lambda python 3 #map python #python filter #python filter lambda #python lambda #python lambda examples #python map
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How to Convert Loops to List Comprehension in Python
Do the same but faster
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]
#python #programming #how to convert loops to list comprehension in python #convert loops #list comprehension #how to convert loops to list comprehension
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Why use Python for Software Development
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.
By areas, we mean FinTech, HealthTech, InsureTech, Cybersecurity, and that's just the beginning. These are New Economy areas, and Python has the ability to serve every one of them. The vast majority of them require massive computational abilities. Python's code is dynamic and powerful - equipped for taking care of the heavy traffic and substantial algorithmic capacities.
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.
5 Reasons to Utilize Python for Programming Web Apps
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.
Robust frameworks
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.
Progressive applications
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.
Summary
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.
#python development services #python development company #python app development #python development #python in web development #python software development
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List Comprehension
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.
#list-comprehension #lists #python #python-list-comprehension
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Python Tips and Tricks for Competitive Programming
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:
#competitive programming #python programs #python-itertools #python-library #python-list #python-list-of-lists #python-map