#python #generativeai #pythontutorial #pythonfunctions #lambdafunctions #pythonforai #machinelearning #datascience #pythoncoding #learnpython #codingtutorial #artificialintelligence… | Punyakeerthi BL

Punyakeerthi BL

5mo

Simplify Your Python Code with Lambda Functions! Have you ever needed to perform a quick calculation or sorting task in Python without writing a full function? That’s where Lambda Expressions come in — short, powerful, and perfect for one-line logic. In my latest video from the Python for Generative AI series, I break down: ✅ What lambda expressions are and why they’re called “anonymous functions” ✅ How to use them effectively for data transformations and sorting ✅ When to use lambda vs. def for cleaner, more readable code ✅ Real-world examples from data science and AI workflows Watch the video here: https://lnkd.in/g4uP2Q8H Whether you’re just starting with Python or already building AI solutions, this video will help you write smarter, cleaner, and more efficient code. If you find it helpful: 👉 Like, share, or comment your favorite use case for lambda functions 👉 Subscribe to my YouTube channel for more content on Python for Generative AI Let’s make coding simpler and smarter together. 💡 #Python #GenerativeAI #PythonTutorial #PythonFunctions #LambdaFunctions #PythonForAI #MachineLearning #DataScience #PythonCoding #LearnPython #CodingTutorial #ArtificialIntelligence #ProgrammingBasics #PythonDeveloper #PythonForBeginners #CodeSimplified #TechEducation #PythonLambda #AIProgramming #DataEngineer #DeepLearning #PythonTips #CodeSmart #PythonCodingTips #SoftwareDevelopment #PythonLearning #PythonCourse #PunyakeerthiBL

Transcript

Hello everyone, I am Punakaiki here. Welcome to my Python for generative learning series. In this series, we are focusing on Python basics that will help us to build a strong foundation for implementing generative way concepts. So let's dive in and start today's session. Today's topic is master Python Lambda functions online functions like a pro. Let us start with introduction. In this lesson, we conclude our discussion on Python functions by exploring Lambda expressions. These are another way to create. Functions in Python particularly useful for quick one of tasks. While regular functions using DFSR, versatile and widely used Lambda expressions are best when you want short inline functions without cluttering your code with extra definitions. There are commonly used in data transformations, sorting, and functional programming pipelines. So what is a Lambda expression? A Lambda expression is a small anonymous function written in one line. Unlike regular functions, Lambda functions do not have name unless you assign them to a variable or, usually used for short simple tasks, automatically return the value of expression inside them. Other names you might hear include anonymous functions, function literals, Lambda functions. Think of them as a. Invisible helper functions for quick calculations are transformations. So what is the Lambda syntax? Here you are able to see the Lambda syntax. The basic structure of Lambda expression is Lambda. Then we have parameters with colon expression. Lambda is the keyword to define the functions. Parameters are input to the function. Expression is a single line of code that is automatically returned. So let us start with example one. Here we can go for a regular function which adds 3 numbers. So here is a function. Let us take this to our code editor. And let's see the output at the definition. So what I'm doing here I'm taking. One function which has name add three with three parameters and returning the sum of that three variables. So when we call that one with three parameters it print the sum of that three values. Well now how we can include the implement the same function in Lambda function style. Here I used. Only single line. Let's see this one and understand what it is Lambda. After that we have parameters. After that we have expression. Then we are passing the values to 345. So when we get the same output in single line. Let us understand so explanation. The Lambda takes 3 parameters AB&C. The expression a + b + C is written automatically. The parenthesis at the end pass the arguments key point. Both methods give the same results but the Lambda is. Shorter and inline, suitable for one of calculations. Let us go with example 2, assigning Lambda to a variable here. First one without. What we are doing we have a variable called square which has Lambda X is equal to X to the power of 2. So when you pass the square of four it will give the. 16 that is square of 4 means whatever parameter we pass 2 square is 4 square of a number within one line. We can do this one. So with default arguments, I want to ask a default argument if any value is not passed only simply it will call then default will be used. Default value will be used for calculation. Now we have a square and Lambda X is here. X is not assigned with any variable value. Your default value will be 10. So if any value first that will be taken as square of that number. Now I'm calling without any parameter to the power of 10 is 110, square is 100 likewise. If I pass any value without default value, chi square is 25 in this way with the default value. Without default value, how we can define a Lambda and assigning that to a variable. So you can assign a Lambda to a variable just like a normal function. Default arguments work the same way as in regular functions. Best practice use DF for complex or reusable functions. Let's start with another example. Practical example sorting with Lambda. Lambda function change when used as arguments to other functions such as sort. So have a function here how it will work and let's understand the explanation later. So here is my code. So friends is the variable so this is a. Value we have allies. It's a list of values with key value pair Alice and 25 with the tuples Bob and all. Now I want to sort friends. This is the friends valuable sort keys. Key on the basis of key key is Alice. So from X colon X of 1 is Alice. It is taking. Then we are printing so Alice, Bob, Charlie. Already we are giving. So we got Bob, Alice and Charlie like that it is sorting. It is sorting on the basis of the values 202530 not on the basis of. Name how it will work. Let's see. X represents each tuple in the list. So ex is here where represent each tuple. We have then X of 1, extracts the edge from the tuple, then sort arranges the list in ascending order based on the ages. In this way, using a Lambda, we can solve the. Arguments. Next we have example 4 starting by the name length. So we can sort length of the name. So we have we have names like Alice, Bob, Charlie. So first should Bob comes then always then Charlie because the variables length is different. So what we are doing French sort K is equal to Lambda, Lambda is X and length of X of 0X of 0 is the name so we are taking that one. We are sorting and the base of length function we are using for the names. So we need to sort on the basis when we print. And automatically it start with Bob, Alice and Charlie because Bob length is shorter and Charlie's length is larger. That's why it comes at last. In this way we can sort it. How we can understand the explanation? X of 0 is the name. We will come to know that name we took. Then length of X of 0 calculates the length of each name. The list is sorted by the length of names instead of each use case. This approach is popular in data science and AI where sorting and filtering datasets quickly is. Bowman So we went through a lot of examples. Let's see best practices. Lambda expressions are best for inline use, like passing an as arguments. Assigning lambdas to variables is allowed, but many editors may suggest using DF for readability. Use regular functions, DF for complex or reusable logic. Use lambdas for short one line self-contained tasks. Wrap up Lambda expressions. At a powerful tool in Python for creating weak temporary functions, they help reduce code clutter, perform quick calculations, sort or transform data in line. While they are not used for every situation, they are an essential part of your Python toolkit, especially in data manipulation tasks. So let's recap. In this lesson you learned what Lambda Lambda expressions are and how they differ from regular functions. How to write Lambda functions with parameters. And default arguments. How to assign lambdas to variables for simple tasks. Practical uses of lambdas. Inserting list and data transformations. Best practices for when to use lambdas versus regular functions. So thank you for watching today's session. This is part of Python for generative learning series. I am Pune Kirti BL. If you found this helpful, please subscribe to my channel for more videos. Also, feel free to connect with me on LinkedIn. The link is in the description. See you in the next session. Thank you very.

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